WHOLE-CABIN BOARDING SIMULATION
DETERMINISTIC STRESS DATASETS FOR MULTI-REGION DEPENDENCY EVALUATION
Version: Stress Dataset Research Log v1

Purpose
-------
This document begins the final controlled validation programme for the completed
Reactive Dependency-Region Management Architecture.

The preceding architecture report is now frozen. Its final implementation
provides reactive congestion detection, persistent dependency-region lifecycle
tracking, three-tick confirmation, state-change-aware evaluation and hierarchical
dependency-region prioritisation.

The present programme does not redesign that architecture. It investigates
whether deterministic input datasets can be constructed to produce simultaneous
confirmed dependency regions and thereby exercise architectural capabilities that
rarely appeared in the conventional benchmark scenarios.

The architecture is therefore the fixed reference implementation. Dataset
construction becomes the independent variable.


======================================================================
RESEARCH BOUNDARY
======================================================================

This research does not reopen or replace the conclusions of the completed
Reactive Dependency-Region Management Architecture.

It introduces one new independent research variable:

    DETERMINISTIC STRESS DATASET CONSTRUCTION

The programme may alter deterministic passenger manifests, seat-distribution
patterns and queue ordering only when those changes are explicitly documented as
properties of the dataset under test.

It does not introduce:

- probabilistic human behaviour;
- passenger hesitation or personal judgement;
- asynchronous tick execution;
- overtaking;
- reverse aisle movement;
- aisle switching;
- movement beyond an assigned row;
- seat reassignment;
- predictive congestion management;
- advance aisle-space reservation;
- airline policy unless later isolated as a separate deterministic dataset
  variable.

The completed architecture must process each dataset without being changed to
accommodate the expected result.


======================================================================
FIXED REFERENCE ARCHITECTURE
======================================================================

The following architectural components remain enabled and unchanged throughout
this research programme:

- synchronous global movement;
- maximum one forward aisle tile per passenger per tick;
- one unique assigned seat per passenger;
- fixed serving aisle for every passenger;
- no movement beyond the assigned row;
- deterministic stand-yield-sit-reseat transactions;
- middle-bank reservation;
- dependency-aware precedence;
- adaptive rear-boundary forward yield;
- guarded forward-yield checks;
- row-bounded congestion clustering;
- persistent dependency-region lifecycle tracking;
- three-tick region confirmation;
- state-change-gated evaluation;
- deterministic hierarchical region prioritisation;
- 1,500-tick no-seat-progress stall detector;
- 30,000 maximum ticks.

Any later change to one of these components would constitute a new architecture
programme and must not be presented as a stress-dataset experiment.


======================================================================
CONTROLLED CONDITIONS
======================================================================

Within every paired experiment, the following must remain identical unless the
experiment explicitly identifies one of them as the dataset variable:

- cabin configuration;
- total seat capacity;
- occupancy rate;
- scenario seed;
- passenger count;
- entry-headway range;
- synchronous execution;
- passenger movement rules;
- seat-event prerequisites;
- blocker movement;
- yield-space rules;
- middle-bank reservation;
- dependency-region detection;
- lifecycle matching, updating and dissolution;
- confirmation threshold;
- state-change signature;
- region-priority hierarchy;
- stall and maximum-tick limits;
- output instrumentation.

Experiment 1 changes the deterministic dataset family while preserving the
entire architecture and the scenario-level cabin, occupancy, headway and seed.


======================================================================
DATASET CONSTRUCTION CONTRACT
======================================================================

A deterministic stress dataset is a reproducible passenger manifest and entry
ordering designed to increase the opportunity for demanding dependency-region
structures without modifying passenger movement after admission.

All stress datasets must obey the following rules:

1. Every passenger retains one unique assigned seat.
2. Every passenger retains one fixed serving aisle.
3. Dataset construction completes before simulation movement begins.
4. Dataset generation is reproducible from the recorded seed.
5. The boarding engine receives a completed manifest and queue; it does not know
   why a passenger was selected or ordered.
6. No stress generator may create two passengers for the same seat.
7. No generator may place a passenger directly into the aisle or a seat-event
   state.
8. No generator may alter movement speed, event duration or blocker rules.
9. No generator may guarantee or fabricate a dependency region.
10. Failure to create simultaneous regions is a valid dataset result and must be
    documented honestly.


======================================================================
NEW TERMINOLOGY
======================================================================

Deterministic Stress Dataset
----------------------------
A reproducible passenger manifest and entry-order dataset deliberately designed
to expose demanding but valid congestion structures to the frozen architecture.

Standard Deterministic Dataset
------------------------------
The established reference generator using seeded random seat selection and
independently shuffled aisle queues.

Stress Dataset Family
---------------------
A named group of deterministic datasets sharing the same construction principle,
such as row-zone concentration, blocker-prone seating or alternating aisle
admission.

Dataset Characteristic
----------------------
A measurable property of an input dataset, such as row-zone concentration,
blocker-prone seat share or left/right aisle balance.

Confirmed Region Concurrency
----------------------------
The number of dependency regions that have simultaneously survived the
three-tick confirmation threshold.

Region Competition
------------------
A tick on which more than one confirmed, state-change-eligible dependency region
requires hierarchical evaluation.

Competition Window
------------------
A continuous tick interval during which two or more confirmed dependency regions
coexist.

Priority Utilisation
--------------------
Observed use of the completed hierarchical prioritisation layer to rank genuine
simultaneous confirmed regions.

Negative Dataset Finding
------------------------
A valid result in which a stress dataset does not produce the intended region
competition. Such a result informs later dataset refinement without justifying
an architecture change.


======================================================================
RESEARCH OBJECTIVES
======================================================================

1. Construct reproducible deterministic datasets capable of producing multiple
   dependency regions within the same simulation.
2. Progress from detected-region concurrency to simultaneous confirmed-region
   concurrency.
3. Produce genuine priority competitions without modifying the completed
   architecture.
4. Identify which input characteristics increase or reduce multi-region
   dependency formation.
5. Separate dataset effects from entry headway and all movement rules.
6. Retain negative findings when apparently stressful datasets simplify rather
   than intensify congestion.
7. Build a reusable catalogue of deterministic benchmark datasets for future
   validation.
8. Complete a final controlled test of the frozen architecture.


======================================================================
EXPERIMENT 1 - BASELINE DETERMINISTIC STRESS DATASET CONSTRUCTION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit Amlani's original movement algorithm operates on an already constructed
one-dimensional occupancy dataset. The completed boarding architecture similarly
processes the manifest and aisle queues that it receives.

Experiment 1 returns to this foundational distinction. It does not change the
movement algorithm. It changes only the deterministic data supplied to that
algorithm and observes whether the same fixed architecture exposes different
congestion structures.

Purpose
-------
Establish a reusable deterministic stress-dataset generator and compare its
first conservative stress family against the standard deterministic dataset.

The first experiment is primarily a foundation and calibration experiment. It
is not required to produce simultaneous confirmed dependency regions. Its role
is to verify that:

- dataset construction is reproducible;
- the frozen architecture remains unchanged;
- paired datasets retain the same scenario-level cabin, occupancy, headway and
  seed;
- dataset characteristics are recorded explicitly;
- region-concurrency and priority evidence can be compared cleanly.

Paired Modes
------------
Each of the 30 scenarios is executed twice.

1. STANDARD DETERMINISTIC DATASET

   The reference generator selects occupied seats from a seeded shuffled seat
   catalogue and independently shuffles the left- and right-aisle queues.

2. BASELINE DETERMINISTIC STRESS DATASET

   The frozen architecture receives a reproducible composite stress manifest.
   Passenger seats are preferentially selected from two separated row zones,
   blocker-prone seats receive greater selection weight and each serving-aisle
   queue is ordered deterministically around the same two zones.

The second mode changes input data only. The architecture, movement contract,
confirmation threshold, state-change gate and priority hierarchy are identical.

Independent Variable
--------------------

    DATASET GENERATION FAMILY

- standard seeded manifest and shuffled queues; versus
- baseline deterministic two-zone stress manifest and stress-ordered queues.

Baseline Stress Family Design
-----------------------------
The first stress family uses three documented dataset characteristics:

1. TWO SEPARATED ROW ZONES

   Seats near approximately one-third and two-thirds of cabin depth receive
   greater deterministic selection weight. The separation is intended to create
   more than one local area of potential congestion rather than one continuous
   cabin-wide concentration.

2. BLOCKER-PRONE SEAT EMPHASIS

   Window and deeper seats receive greater weight than aisle-adjacent seats. This
   increases the potential for valid seated blockers without changing any seat
   event after the manifest is created.

3. DETERMINISTIC ZONE-ORIENTED QUEUE ORDER

   Each aisle queue is ordered reproducibly so passengers associated with the
   two stress zones enter under the existing headway mechanism. The generator
   does not bypass headway and does not insert passengers directly into the
   aisle.

This is intentionally a composite baseline family. Later experiments may isolate
or ablate individual characteristics after the generator and evidence model have
been validated.

Controlled Conditions
---------------------

- identical cabin configuration within each pair;
- identical occupancy rate;
- identical passenger count;
- identical entry-headway range;
- identical scenario seed;
- identical frozen architecture;
- identical synchronous tick execution;
- identical movement constraints;
- identical stall detector and maximum ticks;
- no human behaviour;
- no asynchronous execution;
- no reverse movement, overtaking, aisle switching or assigned-row overshoot.

Dataset Evidence Collected
--------------------------

- dataset family;
- row-zone concentration percentage;
- blocker-prone seat share;
- left/right aisle-assignment balance;
- passenger count and occupancy;
- entry-headway range;
- dependency regions detected;
- regions created, updated, confirmed and dissolved;
- maximum simultaneous active regions;
- regions active at termination;
- state-change evaluations suppressed and reopened;
- priority competitions;
- lower-priority deferrals;
- cluster selections and cluster-started events;
- complete cabins and passengers seated;
- simulation ticks;
- passengers remaining outside;
- residual stall family.

Experimental Hypothesis
-----------------------
A deterministic two-zone, blocker-emphasised dataset may increase spatially
separated dependency activity relative to the standard dataset. However, the
same ordering may also simplify flow by making local seat events complete more
coherently. Either result is scientifically valid.

The primary Experiment 1 question is therefore not whether the stress dataset
improves or worsens boarding. It is whether the dataset layer is reproducible,
measurable and capable of changing dependency-region evidence without changing
the architecture.

Interpretation Safeguards
-------------------------

- A faster stress run is not automatically a failed experiment.
- A slower stress run is not automatically evidence of better stress.
- More detected regions do not necessarily mean more confirmed concurrent
  regions.
- Multiple regions created at different times do not constitute simultaneous
  dependency competition.
- Priority utilisation requires genuine simultaneous confirmed eligible regions.
- The architecture must not be changed merely because the first stress family
  fails to create competition.
- Any improvement or regression in boarding outcome must be reported as a
  dataset effect.
- Composite stress characteristics must be separated in later experiments before
  causal claims are made about a single characteristic.

Primary Evaluation Order
------------------------

1. Correct experiment identity and deterministic replay.
2. Dataset-characteristic differences between paired modes.
3. Maximum simultaneous active regions.
4. Confirmed-region concurrency.
5. Genuine priority competitions and deferrals.
6. Regions created, confirmed and dissolved.
7. Cluster selections and cluster-started events.
8. Complete cabins and passengers seated.
9. Residual stall classifications.
10. Simulation ticks as a secondary measure.

Expected Outcomes
-----------------

Outcome A - Simultaneous confirmed regions appear

The baseline stress family immediately exercises hierarchical prioritisation and
provides a foundation for controlled refinement.

Outcome B - More regions appear, but not simultaneously

The generator increases congestion activity but requires stronger temporal
alignment in a later dataset.

Outcome C - Fewer regions appear

The deterministic zone ordering simplifies cabin flow. This becomes a useful
negative finding and suggests later experiments should separate seat selection
from queue ordering.

Outcome D - No meaningful difference appears

The baseline generator is too conservative. Later experiments may increase one
dataset characteristic at a time while retaining the same frozen architecture.

Diagram Plan
------------
A diagram should be considered only after results are available. A valid diagram
may compare:

- the standard dispersed manifest;
- the two separated stress zones;
- blocker-prone seat emphasis;
- left/right deterministic queues;
- observed region timelines.

The diagram must distinguish input construction from passenger movement and must
not imply that dependency regions were inserted directly into the simulation.


======================================================================
RUNNING CONCLUSIONS
======================================================================

1. The Reactive Dependency-Region Management Architecture is frozen.
2. Dataset construction is now the independent research variable.
3. Experiment 1 establishes the reusable paired stress-dataset framework.
4. The first stress family combines two separated row zones, blocker-prone seat
   emphasis and deterministic zone-oriented queue ordering.
5. Simultaneous dependency competition must arise from valid deterministic
   simulation state; it must not be manufactured by changing the architecture.
6. Human behaviour, asynchronous execution, backward movement, overtaking,
   aisle switching and assigned-row overshoot remain excluded.
7. Negative dataset findings are retained as evidence for later refinement.
8. Future experiments should isolate individual stress characteristics after the
   baseline generator has been validated.



======================================================================
EXPERIMENT 1 FINDINGS - BASELINE DETERMINISTIC STRESS DATASET CONSTRUCTION
======================================================================

Execution Summary
-----------------
Experiment 1 completed 30 deterministic paired scenarios (60 executions) using
the same fixed architecture, cabin characteristics, occupancy, headway and
scenario seeds in each pair.

The standard dataset and baseline composite stress dataset each completed 27 of
30 cabins. However, the internal evidence differed substantially.

Overall Paired Result
---------------------

- Standard-dataset average completion: 99.71%.
- Composite stress-dataset average completion: 96.82%.
- Standard complete cabins: 27 of 30.
- Composite stress complete cabins: 27 of 30.
- Improved stress pairs: 3.
- Unchanged pairs: 24.
- Worse stress pairs: 3.
- Standard total passengers seated: 7,649.
- Composite stress total passengers seated: 7,391.
- Net seated-passenger difference: -258.
- Standard dependency regions detected: 37.
- Composite stress dependency regions detected: 13.
- Standard regions reaching confirmation: 22.
- Composite stress regions reaching confirmation: 9.
- Standard cluster selections: 25.
- Composite stress cluster selections: 6.
- Standard cluster-started events: 31.
- Composite stress cluster-started events: 15.
- Genuine priority competitions: 0 in both modes.

Principal Findings
------------------

1. The dataset-generation layer was successfully separated from the architecture.

Both paired modes used the frozen Reactive Dependency-Region Management
Architecture. The experiment therefore confirmed that manifests and aisle queues
can be varied reproducibly without changing movement, clustering, lifecycle,
confirmation, state-change gating or prioritisation.

2. The composite stress family did not create multi-region competition.

No simultaneous confirmed-region priority competition occurred. The dataset
therefore did not yet exercise the hierarchical prioritisation layer.

3. The composite stress family reduced dependency-region activity.

The stress mode produced 13 detected regions compared with 37 under the standard
dataset, and only 9 confirmed regions compared with 22. Cluster selections and
cluster-started events were also lower.

4. Deterministic concentration can simplify flow rather than intensify it.

The combination of two row zones, blocker-prone seat weighting and zone-oriented
queue ordering appears to have created more coherent local seating sequences in
many scenarios. This reduced the fragmented dependency activity that the stress
family was intended to increase.

5. Boarding outcome alone is not a sufficient stress measure.

Both modes completed 27 cabins, yet the stress mode seated 258 fewer passengers
across the three incomplete cases. Conversely, three standard stalls converted
to complete stress runs. The mixed result confirms that completion must be read
alongside region creation, confirmation and competition evidence.

6. The negative result provides a clear experimental refinement.

Because Experiment 1 changed row concentration, blocker-prone seat share and
queue ordering together, no single characteristic can be identified as the
cause of reduced region activity. The next experiment should isolate row-zone
concentration while returning seat-depth weighting and queue ordering to the
standard deterministic method.

Experiment 1 Conclusion
-----------------------
The reusable deterministic stress-dataset framework is validated. The first
composite family did not produce simultaneous dependency competition and often
simplified congestion structure. This is retained as a valid negative dataset
finding. Experiment 2 will isolate row-zone concentration as the sole dataset
variable.


======================================================================
EXPERIMENT 2 - CONTROLLED ROW-ZONE CONCENTRATION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit Amlani's original movement algorithm processes the occupancy dataset it is
given without changing the rules of movement in response to how that dataset was
constructed. Experiment 2 follows the same separation by changing only where
assigned seats are concentrated before movement begins.

Purpose
-------
Determine whether two separated row zones, by themselves, increase spatially
separated dependency activity when blocker-prone seat weighting and specialised
queue ordering are removed.

Paired Modes
------------
Each of the 30 scenarios is executed twice using identical cabin configuration,
occupancy, passenger count, headway, scenario seed and frozen architecture.

1. STANDARD DETERMINISTIC DATASET

   Occupied seats are selected from a seeded shuffled seat catalogue. Left- and
   right-aisle queues are independently shuffled.

2. CONTROLLED ROW-ZONE CONCENTRATION DATASET

   Occupied seats are selected preferentially from two separated row zones near
   one-third and two-thirds of cabin depth. All seat positions inside those zones
   receive equal treatment; window and deep seats receive no additional weight.
   Left- and right-aisle queues are independently shuffled exactly as in the
   standard mode.

Independent Variable
--------------------

    ROW-ZONE CONCENTRATION

- dispersed seeded seat selection; versus
- deterministic concentration around two separated row zones.

Removed Experiment 1 Composite Variables
----------------------------------------

The following Experiment 1 characteristics are deliberately removed:

- blocker-prone seat emphasis;
- zone-oriented queue ordering;
- blocker-first queue tie-breaking.

This permits a narrower causal interpretation of any change in region evidence.

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin, occupancy and passenger count within each pair;
- identical entry-headway range;
- identical scenario seed;
- independently shuffled aisle queues in both modes;
- identical seat-event and blocker rules;
- synchronous execution;
- no backward movement, overtaking, aisle switching or assigned-row overshoot;
- no human behaviour or asynchronous execution.

Evidence Collected
------------------

- row-zone concentration percentage;
- blocker-prone seat share as a diagnostic control;
- aisle-assignment balance;
- dependency regions detected;
- regions created, confirmed and dissolved;
- maximum simultaneous active regions;
- confirmed-region concurrency;
- priority competitions and lower-priority deferrals;
- cluster selections and starts;
- complete cabins and passengers seated;
- residual stall family;
- simulation ticks as a secondary measure.

Experimental Hypothesis
-----------------------
If separated spatial concentration is sufficient to create independent local
congestion, the row-concentrated dataset should increase concurrent region
activity despite retaining standard shuffled queue order. If region activity
remains lower, row concentration itself may promote coherent completion rather
than competition.

Interpretation Safeguards
-------------------------

- Two row zones do not constitute two dependency regions.
- Regions created at different times do not constitute concurrency.
- A priority competition requires simultaneous confirmed and eligible regions.
- Changes in blocker-prone seat share must be reported, even though no explicit
  blocker weighting is used.
- The architecture must not be changed to force the expected result.
- A negative result will motivate a later isolated seat-depth or admission-order
  experiment rather than reopening the architecture.

Primary Evaluation Order
------------------------

1. Dataset identity and deterministic execution.
2. Row-zone concentration difference.
3. Maximum simultaneous active and confirmed regions.
4. Genuine priority competitions.
5. Regions detected and confirmed.
6. Cluster selections and starts.
7. Complete cabins and seated totals.
8. Residual stall families.
9. Simulation ticks as a secondary measure.

Diagram Plan
------------
A later diagram may compare dispersed seat selection with two separated row
concentration zones while showing that both modes retain independently shuffled
left- and right-aisle queues. It must not depict dependency regions as inserted
or guaranteed by the dataset generator.


======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 1
======================================================================

1. The frozen architecture remains the fixed reference implementation.
2. Experiment 1 validated the reusable deterministic dataset layer.
3. The first composite stress family reduced rather than increased region
   activity and produced no priority competition.
4. Composite dataset variables must now be separated before causal claims are
   made.
5. Experiment 2 isolates row-zone concentration and restores standard shuffled
   queue ordering and neutral seat-depth selection.
6. Simultaneous dependencies must emerge from valid deterministic state.
7. Human behaviour, asynchronous execution and movement-rule changes remain
   excluded.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v2 - EXPERIMENT 2 DESIGN
======================================================================

======================================================================
EXPERIMENT 2 FINDINGS - CONTROLLED ROW-ZONE CONCENTRATION
======================================================================

Purpose Reviewed
----------------
Experiment 2 isolated deterministic row-zone concentration from the composite
stress variables introduced in Experiment 1. Both paired modes retained the
frozen Reactive Dependency-Region Management Architecture, independently
shuffled aisle queues, neutral seat-depth selection and identical movement
rules. Only the spatial distribution of occupied rows changed.

Overall Paired Result
---------------------

- Scenario pairs: 30.
- Scenario executions: 60.
- Standard average completion: 99.71%.
- Row-concentration average completion: 98.92%.
- Improved row-concentration pairs: 2.
- Unchanged pairs: 22.
- Worse row-concentration pairs: 6.
- Net seated-passenger difference: -75.
- Standard complete cabins: 27 of 30.
- Row-concentration complete cabins: 24 of 30.
- Standard stalls converted to complete cabins: 2.
- Standard dependency regions: 37.
- Row-concentration dependency regions: 36.
- Standard confirmed regions: 22.
- Row-concentration confirmed regions: 13.
- Standard priority competitions: 0.
- Row-concentration priority competitions: 7.
- Maximum simultaneous active regions: 2 in both modes.

Principal Findings
------------------

1. Row-zone concentration changed congestion geometry without consistently
   increasing overall dependency-region volume.

The row-concentrated datasets produced almost the same total number of detected
regions as the standard datasets, but fewer regions reached confirmation. This
shows that spatial concentration can change the persistence and timing of
congestion even when total region counts remain similar.

2. The isolated variable produced both beneficial and harmful outcomes.

Two standard stalls converted to complete cabins, while six paired scenarios
seated fewer passengers under row concentration. The result therefore does not
support row concentration as a generally beneficial or generally harmful
boarding arrangement.

3. Genuine simultaneous-region competition was observed.

Unlike the previous benchmark and Experiment 1, the row-concentration datasets
produced seven priority competitions. This is the first direct evidence within
the stress-dataset programme that deterministic manifest construction alone can
exercise the hierarchical prioritisation layer of the frozen architecture.

4. Concurrency did not require human behaviour or asynchronous ticks.

The priority competitions emerged under synchronous deterministic movement,
fixed headway rules and unchanged architecture. Dataset geometry alone was
sufficient to create overlapping confirmed-region eligibility.

5. Row concentration is therefore a useful stress component, but not a complete
   causal explanation.

Because row concentration also changed which seats happened to be selected, the
next experiment must isolate seat-depth distribution directly while restoring
dispersed row selection. This will determine whether blocker-prone seats increase
confirmed-region activity independently of row concentration.

Experiment 2 Conclusion
-----------------------
Controlled row-zone concentration is supported as a valid deterministic stress
variable. It generated the first seven genuine priority competitions without
changing the frozen architecture, human behaviour or synchronous execution.
However, its mixed completion effects and reduced confirmation count show that
it should be treated as one stress-building component rather than a complete
solution for repeatable multi-region generation.


======================================================================
EXPERIMENT 3 - CONTROLLED BLOCKER-PRONE SEAT CONCENTRATION
======================================================================

Connection to the Completed Architecture
----------------------------------------
The Reactive Dependency-Region Management Architecture remains frozen. This
experiment changes only the manifest's seat-depth distribution so that the
existing blocker, yield-space and seat-event rules are exercised more often.
The architecture is not informed that a stress dataset is in use and receives
only the completed deterministic passenger manifest.

Purpose
-------
Determine whether deterministic concentration of window and deep inner seats
increases persistent blocker-dependent seat events, confirmed dependency regions
and simultaneous priority competitions when row selection and aisle queues
remain dispersed.

Controlled-Variable Clarification
---------------------------------
Increasing the probability of blocker-prone assigned seats does not alter a
controlled movement variable. The following remain controlled and unchanged:

- the definition of a blocker;
- the stand-yield-sit-reseat transaction;
- the number of yield tiles required by a given seat event;
- blocker movement direction;
- synchronous tick execution;
- passenger movement speed;
- entry-headway range;
- clustering, lifecycle, confirmation, gating and prioritisation rules.

The assigned-seat distribution is intentionally the independent dataset
variable in Experiment 3. Therefore individual seat assignments cannot remain
identical between the two paired modes; instead, cabin type, occupancy,
passenger count, headway, scenario seed and all architecture and movement rules
remain controlled. This distinction is essential to the new research programme,
where dataset construction is the subject under investigation.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

   Occupied seats are selected from a seeded shuffled catalogue. Left- and
   right-aisle queues are independently shuffled.

2. CONTROLLED BLOCKER-PRONE SEAT CONCENTRATION DATASET

   Occupied seats are selected preferentially by deterministic blocker potential.
   Window seats and deep inner seats are selected before easier aisle-side seats.
   Rows remain dispersed through seeded tie-breaking, and both aisle queues are
   independently shuffled exactly as in the standard mode.

Independent Variable
--------------------

    ASSIGNED-SEAT DEPTH DISTRIBUTION

- seeded neutral seat selection; versus
- deterministic concentration of blocker-prone window and deep inner seats.

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin configuration within each pair;
- identical occupancy rate and passenger count;
- identical entry-headway range;
- identical scenario seed;
- dispersed row selection in both modes;
- independently shuffled aisle queues in both modes;
- unchanged seat-event, blocker and yield-space rules;
- synchronous execution;
- no backward movement, overtaking, aisle switching or assigned-row overshoot;
- no human behaviour or asynchronous execution.

Evidence Collected
------------------

- blocker-prone seat share;
- row-zone concentration as a diagnostic control;
- aisle-assignment balance;
- single- and multiple-blocker seat events;
- temporary aisle reoccupations;
- dependency regions detected;
- regions created, confirmed and dissolved;
- maximum simultaneous active regions;
- priority competitions and lower-priority deferrals;
- cluster selections and starts;
- complete cabins and passengers seated;
- residual stall family;
- simulation ticks as a secondary measure.

Experimental Hypothesis
-----------------------
If blocker-prone seat depth is an important contributor to independent congestion
zones, the concentrated dataset should increase multiple-blocker events,
confirmed dependency regions or priority competitions while row concentration
remains near the standard distribution. A null result would indicate that seat
depth alone is insufficient and that later experiments should combine it with
spatial or admission-pattern stress.

Interpretation Safeguards
-------------------------

- More window seats do not automatically constitute more dependency regions.
- More blocker events do not automatically constitute simultaneous regions.
- A priority competition requires simultaneous confirmed and eligible regions.
- Row-zone concentration must remain a diagnostic control and be reported.
- Different seat assignments are the intended independent-variable change, not
  a breach of the movement contract.
- The architecture must not be modified to force the expected outcome.
- Any worse completion outcome must be reported honestly as a dataset effect.

Primary Evaluation Order
------------------------

1. Dataset identity and deterministic execution.
2. Blocker-prone seat-share difference.
3. Row-zone concentration control.
4. Multiple-blocker events and temporary aisle reoccupations.
5. Confirmed regions and maximum simultaneous regions.
6. Genuine priority competitions.
7. Cluster selections and starts.
8. Complete cabins and seated totals.
9. Residual stall families.
10. Simulation ticks as a secondary measure.

Diagram Plan
------------
A later diagram may compare neutral seat selection with deterministic
window/deep-seat concentration across dispersed rows. It must show that seat-event
rules remain unchanged and must not depict blockers, dependency regions or
priority competitions as inserted directly by the dataset generator.


======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 2
======================================================================

1. The frozen architecture remains the fixed reference implementation.
2. Experiment 1 established the reusable deterministic dataset layer.
3. Experiment 2 generated seven genuine priority competitions through row-zone
   concentration alone.
4. Simultaneous dependencies therefore do not require human behaviour or
   asynchronous execution.
5. Row concentration produced mixed boarding outcomes and fewer confirmed
   regions overall, so it remains a stress component rather than a complete
   benchmark solution.
6. Experiment 3 isolates assigned-seat depth while restoring dispersed row
   selection and standard shuffled queues.
7. Seat-event rules remain controlled; only the deterministic seat-assignment
   distribution changes.
8. No passenger may pass the assigned row or move backwards.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v3 - EXPERIMENT 3 DESIGN
======================================================================


======================================================================
EXPERIMENT 3 FINDINGS - CONTROLLED BLOCKER-PRONE SEAT CONCENTRATION
======================================================================

Purpose Reviewed
----------------
Experiment 3 isolated deterministic assigned-seat depth while restoring dispersed
row selection and independently shuffled aisle queues. The completed Reactive
Dependency-Region Management Architecture remained frozen. The independent
variable was the proportion of window and deep inner seats selected into the
passenger manifest.

Execution Summary
-----------------
Thirty paired scenarios were executed, producing sixty deterministic runs.

Across the complete batch:

- Standard average completion: 99.71%.
- Blocker-prone dataset average completion: 98.96%.
- Improved blocker-prone pairs: 3 of 30.
- Unchanged pairs: 22 of 30.
- Worse blocker-prone pairs: 5 of 30.
- Net seated-passenger difference: -55.
- Standard complete cabins: 27 of 30.
- Blocker-prone complete cabins: 25 of 30.
- Standard dependency regions: 37.
- Blocker-prone dependency regions: 45.
- Standard confirmed regions: 22.
- Blocker-prone confirmed regions: 34.
- Standard cluster selections: 25.
- Blocker-prone cluster selections: 36.
- Standard cluster-started events: 31.
- Blocker-prone cluster-started events: 41.
- Blocker-prone priority competitions: 6.
- Standard priority competitions: 0.

Principal Findings
------------------

1. Seat-depth concentration produced stronger dependency evidence than row
   concentration alone.

The blocker-prone dataset increased detected regions from 37 to 45, confirmed
regions from 22 to 34, cluster selections from 25 to 36 and cluster-started
events from 31 to 41. This supports assigned-seat depth as a meaningful
component of deterministic congestion construction.

2. Genuine hierarchical priority competition was exercised.

Six priority competitions occurred in the blocker-prone dataset. Scenario 19
provided the clearest evidence: two simultaneously active regions reached
confirmation, twelve region rankings were recorded across six competitions, and
the hierarchy selected between left- and right-aisle regions using the completed
deterministic priority score.

3. More blocker-prone seats did not produce a uniform outcome.

Three scenarios improved, twenty-two remained unchanged and five became worse.
Scenario 4 converted a standard rear-boundary stall at 200/204 into a complete
204/204 cabin, while Scenario 7 changed from complete boarding to 209/216 with a
mixed dependency residual. The result confirms that dependency topology, rather
than blocker count alone, controls the final congestion pattern.

4. The dataset changed the geometry of dependency formation.

The blocker-prone manifest produced linked row-event chains, yield-tile
occupancy dependencies, deeper critical-blocker trees and longer-lived confirmed
regions in selected scenarios. In other scenarios, the changed seat geometry
removed a previous bottleneck. Seat-depth concentration therefore changes the
structure and timing of dependencies rather than merely increasing their number.

5. Simultaneous dependencies require spatial separation as well as blocker
   density.

Although six priority competitions were observed, most blocker-prone scenarios
still contained only one active confirmed region at a time. The next experiment
should therefore retain blocker-prone seat depth but deliberately distribute it
across two separated aisle-specific row zones.

6. The frozen architecture remained controlled.

No passenger moved backwards, passed the assigned row, overtook another
passenger, changed aisle or changed assigned seat. Entry headway, synchronous
execution, seat-event prerequisites, blocker movement, lifecycle confirmation,
state-change gating and hierarchical prioritisation were unchanged.

Scientific Interpretation
-------------------------
Experiment 3 establishes Dependency Topology as a central concept for the new
research programme.

Dependency Topology is the spatial arrangement of blocker-dependent seat events
and the resulting dependency chains within a deterministic boarding dataset.
The findings demonstrate that topology cannot be inferred from blocker density
alone. A larger blocker-prone share increases the opportunity for dependencies,
but their independence, coexistence and final effect depend upon where those
seat events occur and how the two aisle flows encounter them.

Experiment 3 Conclusion
-----------------------
Controlled blocker-prone seat concentration is supported as a stronger stress
component than row-zone concentration alone. It increased region and
intervention evidence and produced six genuine hierarchy competitions. However,
it did not reliably create two independent congestion zones. The next experiment
therefore constructs an explicit dual-aisle dependency topology while preserving
the frozen architecture and ordinary deterministic movement rules.


======================================================================
NEW TERMINOLOGY FOR EXPERIMENT 4
======================================================================

Dependency Topology
-------------------
The spatial arrangement of blocker-dependent seat events and their resulting
dependency chains within a deterministic boarding dataset.

Independent Congestion Zone
---------------------------
A locally formed dependency region that remains structurally separate from
another active dependency region, allowing both to coexist without being one
continuous aisle chain.

Dual-Aisle Dependency Topology
------------------------------
A deterministic manifest design that concentrates blocker-prone assigned seats
around two separated row bands, one primarily served by each aisle, while
leaving movement and congestion-management rules unchanged.

Topology Competition
--------------------
A genuine hierarchical priority competition arising because two independently
formed confirmed regions are simultaneously eligible for evaluation.


======================================================================
EXPERIMENT 4 - DUAL-AISLE DEPENDENCY TOPOLOGY CONSTRUCTION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit Amlani's original algorithm investigates how the arrangement of occupied
positions changes movement opportunities within a one-dimensional dataset.
Experiment 4 retains that principle but varies the deterministic input geometry
across two aisle datasets. The completed movement and congestion-management
architecture remains fixed; only the assigned-seat topology supplied to it
changes.

Planned Purpose
---------------
Determine whether a deliberately separated dual-aisle seat topology can produce
more repeatable simultaneous confirmed dependency regions than blocker-prone
seat concentration alone.

Paired Modes
------------
Each scenario is executed twice using the same cabin, occupancy, entry headway,
scenario seed and frozen architecture.

1. STANDARD DETERMINISTIC DATASET

   Seats are selected using the established seeded shuffle and both aisle queues
   are independently shuffled.

2. DUAL-AISLE DEPENDENCY TOPOLOGY DATASET

   Blocker-prone assigned seats are preferentially selected around two separated
   row bands. The earlier band is primarily associated with the left aisle and
   the later band with the right aisle. Middle-bank seats are assigned
   deterministically toward the nearer side of the topology. Both entry queues
   remain independently shuffled.

Only manifest topology changes. The generator does not insert congestion,
create a region directly or determine which region the hierarchy must select.

Independent Variable
--------------------

    DUAL-AISLE SPATIAL DEPENDENCY TOPOLOGY

- standard dispersed deterministic seat selection; versus
- blocker-prone seats distributed across two separated aisle-specific row bands.

Controlled Conditions
---------------------

- completed Reactive Dependency-Region Management Architecture;
- reactive congestion detection;
- persistent lifecycle tracking;
- three-tick lifecycle confirmation;
- state-change-gated evaluation;
- hierarchical region prioritisation;
- cabin configuration and occupancy within each pair;
- scenario seed and entry-headway range;
- synchronous global movement;
- one forward aisle tile per passenger per tick;
- assigned-seat integrity;
- no movement beyond the assigned row;
- no backward movement, overtaking or aisle switching;
- unchanged seat-event, blocker, yield-space and reservation rules;
- independently shuffled entry queues.

Dataset Construction Contract
-----------------------------

1. Two separated target row bands are derived deterministically from cabin size.
2. Left-served blocker-prone seats receive preference around the earlier band.
3. Right-served blocker-prone seats receive preference around the later band.
4. Middle-bank seats use deterministic side assignment only in the topology
   dataset so that the two intended zones remain spatially distinct.
5. Passenger IDs, assigned seats and queue order remain deterministic under the
   scenario seed.
6. The generator does not pre-create region objects or alter runtime movement.
7. A priority competition is counted only when the frozen architecture observes
   two confirmed and eligible regions naturally during execution.

New Evidence Collected
----------------------

- blocker-prone seat share;
- row-zone concentration as a diagnostic control;
- aisle-assignment balance;
- dependency regions created and confirmed;
- maximum simultaneous active regions;
- scenarios containing two active regions;
- priority competitions;
- hierarchical selections;
- left- and right-aisle priority wins;
- lower-priority deferrals;
- cluster selections and starts;
- complete cabins and passengers seated;
- residual stall families;
- simulation ticks as a secondary measure.

Experimental Hypothesis
-----------------------
If simultaneous region competition depends upon spatial separation as well as
blocker density, the dual-aisle topology dataset should produce more scenarios
with two active confirmed regions and more priority competitions than either the
standard dataset or blocker-prone concentration alone.

A null result would indicate that admission timing or another deterministic
interaction is required in addition to seat topology.

Interpretation Safeguards
-------------------------

- The dataset creates favourable input geometry, not congestion objects.
- Two target zones do not prove that two dependency regions will form.
- More active regions do not automatically mean both are confirmed or eligible.
- Priority competitions must be recorded only by the frozen runtime hierarchy.
- Deterministic middle-bank side assignment is part of dataset construction and
  does not permit aisle switching during simulation.
- Any improved or worse boarding result must be reported as a topology effect.
- The architecture must not be modified to force simultaneous dependencies.

Primary Evaluation Order
------------------------

1. Dataset identity and deterministic replay.
2. Maximum simultaneous active regions.
3. Number of genuine priority competitions.
4. Regions ranked and hierarchical selections.
5. Left/right priority wins and lower-ranked deferrals.
6. Confirmed regions and region lifetimes.
7. Cluster selections and starts.
8. Complete cabins and seated totals.
9. Residual stall families.
10. Simulation ticks as a secondary measure.

Diagram Plan
------------
A later diagram may show two separated row bands, one associated primarily with
left-aisle blocker-prone seating and one with right-aisle blocker-prone seating.
It must clearly distinguish dataset geometry from runtime dependency regions and
must not imply that congestion, confirmation or priority is inserted in advance.


======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 3
======================================================================

1. The frozen architecture remains the fixed reference implementation.
2. Experiment 1 established the reusable deterministic dataset layer.
3. Experiment 2 demonstrated that row concentration can create genuine priority
   competition but does not consistently increase confirmed-region evidence.
4. Experiment 3 increased dependency regions, confirmations, cluster activity
   and produced six genuine priority competitions.
5. Blocker density alone does not determine the resulting dependency topology.
6. Experiment 4 retains blocker-prone depth but separates it across two
   aisle-specific row bands.
7. Simultaneous dependencies remain runtime observations, not objects inserted by
   the dataset generator.
8. No passenger may pass the assigned row or move backwards.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v4 - EXPERIMENT 4 DESIGN
======================================================================


======================================================================
EXPERIMENT 4 FINDINGS - DUAL-AISLE DEPENDENCY TOPOLOGY CONSTRUCTION
======================================================================

Purpose Reviewed
----------------
Experiment 4 tested whether two spatially separated, aisle-specific bands of
blocker-prone assigned seats could cause independent dependency regions to coexist
under the completed and frozen architecture.

The experiment changed deterministic manifest topology only. Passenger movement,
entry-headway ranges, synchronous ticks, seat-event rules, clustering, lifecycle
tracking, confirmation, state-change gating and hierarchical prioritisation were
unchanged.

Overall Paired Result
---------------------

- Scenario pairs: 30.
- Standard average completion: 99.71%.
- Dual-aisle topology average completion: 99.81%.
- Improved topology pairs: 3.
- Unchanged pairs: 26.
- Worse topology pairs: 1.
- Net additional passengers seated: +3.
- Standard complete cabins: 27.
- Dual-aisle topology complete cabins: 29.
- Standard dependency regions: 37.
- Dual-aisle topology dependency regions: 7.
- Standard confirmed regions: 22.
- Dual-aisle topology confirmed regions: 6.
- Standard cluster selections: 25.
- Dual-aisle topology cluster selections: 6.
- Priority competitions in either mode: 0.

Principal Findings
------------------

1. Spatial separation alone did not create sustained multi-region competition.

The two deterministic row bands did not produce a genuine priority competition.
Although the intended zones existed in the manifest, the frozen architecture did
not observe two confirmed and simultaneously eligible regions during execution.

2. The topology frequently simplified rather than intensified congestion.

Region creation fell from 37 in the standard datasets to 7 in the topology
datasets. Confirmed regions fell from 22 to 6. This indicates that organising
blocker-prone seats into coherent aisle-specific bands can cause seat events to
resolve in orderly local sequences instead of producing independent sustained
congestion.

3. Boarding outcomes changed in both directions.

Three topology pairs improved and one became worse. Scenario 4 converted a
rear-boundary stall to complete boarding, while Scenario 26 changed from complete
boarding to a 323/342 rear-boundary stall. Scenario 29 converted a 258/274 mixed
residual stall to complete boarding. These contrasting outcomes confirm that
manifest topology changes dependency geometry rather than applying a uniformly
positive or negative pressure.

4. High blocker-prone seat share is not sufficient evidence of congestion.

Several topology datasets recorded very high blocker-prone seat shares while
producing no dependency region at all. Blocker potential becomes consequential
only when admission order, aisle occupancy and seat-event timing combine to make
temporary yield space unavailable.

5. The null priority result identifies the next missing component.

Experiment 4 created spatially separated zones but did not align their active
lifetimes. One zone could form and resolve before the second became confirmed.
The next controlled variable should therefore be temporal overlap between the
left- and right-aisle stress zones, while preserving the existing headway ranges
and frozen movement architecture.

Experiment 4 Conclusion
-----------------------
Dual-aisle dependency topology is not supported as a sufficient standalone method
for producing simultaneous confirmed dependency regions. It remains a useful
spatial component, but the evidence indicates that spatial independence must be
combined with deterministic temporal alignment before the hierarchy can be
reliably exercised.


======================================================================
DISCUSSION - WHY CONGESTION IS BEING DELIBERATELY CREATED
======================================================================

The present programme may initially appear to contradict the preceding
architecture research. The earlier work introduced row-bounded clustering and
reactive dependency-region management to alleviate bottlenecks, whereas the
current work deliberately constructs datasets more likely to produce them.

The objectives are complementary. A completed congestion-management architecture
cannot be fully evaluated unless the benchmark environment produces sufficiently
rich and independent congestion structures. The stress datasets do not create
congestion for operational benefit and do not insert congestion objects into the
simulation. They create controlled deterministic input conditions under which
congestion may arise naturally through the unchanged movement and seat-event
rules.

Once simultaneous confirmed regions can be reproduced reliably, the frozen
hierarchy can be tested on the larger question: which independent congestion
region should receive evaluation first, and whether that prioritisation releases
more of the cabin or avoids a deeper residual stall.


======================================================================
RESEARCH POSITION - FIRST-PRINCIPLES BOARDING EVIDENCE
======================================================================

This research deliberately examines aircraft boarding before introducing airline
boarding policies or probabilistic human-behaviour assumptions. It begins with
seat ownership, aisle occupancy, blocker movement and temporary yield-space
requirements, and develops congestion from those deterministic first principles.

This does not claim that policy or behavioural research is unnecessary. It
establishes a controlled mechanical foundation beneath those later layers. By
first identifying how seat-event dependencies form, evolve and interact, future
policy or behavioural studies can be interpreted against known congestion
mechanisms rather than treating boarding time as an unexplained final outcome.

The overall programme therefore contains three connected levels:

1. Volumes 1 and 2 explain how deterministic cabin congestion forms.
2. The Reactive Dependency-Region Management Architecture explains how that
   congestion is detected, retained, confirmed and prioritised.
3. The Deterministic Stress Dataset programme constructs controlled evidence
   capable of challenging the completed architecture.


======================================================================
EXPERIMENT 5 - DUAL-AISLE DEPENDENCY TIMING ALIGNMENT
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original people-movement algorithm acts upon the occupancy state present
at each deterministic execution step. Experiment 5 preserves that movement
contract while changing only when two deterministic passenger subsets are
presented to the frozen cabin architecture.

The dataset does not delay a passenger in response to observed congestion and
does not predict a future bottleneck. Queue order is constructed before the run
from the scenario seed. Runtime movement then proceeds under the unchanged
synchronous rules.

Planned Purpose
---------------
Determine whether temporal alignment of the two spatial stress zones created in
Experiment 4 can increase the overlap of their dependency-region lifecycles and
thereby produce genuine hierarchical priority competitions.

Paired Modes
------------
Each scenario is executed twice using the same cabin, occupancy, entry-headway
range and scenario seed.

1. STANDARD DETERMINISTIC DATASET

   The established seeded manifest and independently shuffled aisle queues.

2. DUAL-AISLE DEPENDENCY TIMING ALIGNMENT DATASET

   The dual-zone blocker-prone manifest is retained. Each aisle queue is then
   deterministically ordered so passengers associated with its target stress
   band enter during corresponding early waves. The numerical entry-headway range
   remains identical to the paired standard run.

Independent Variable
--------------------

    PRE-RUN TEMPORAL ALIGNMENT OF AISLE-SPECIFIC STRESS ZONES

The experiment changes deterministic queue construction, which is an authorised
dataset variable in this research programme. It does not change admission
headway, movement speed or runtime scheduling.

Controlled Conditions
---------------------

- frozen Experiment 23 congestion-management architecture;
- identical cabin configuration and occupancy;
- identical scenario seed;
- identical entry-headway range;
- one assigned seat per passenger;
- fixed serving aisle after manifest creation;
- synchronous global execution;
- maximum one forward aisle tile per passenger per tick;
- no backward movement, overtaking or aisle switching;
- unchanged blocker, yield-space and middle-bank reservation rules;
- unchanged clustering, lifecycle, confirmation, gating and priority rules;
- unchanged stall detector and maximum tick limit.

Timing-Alignment Contract
-------------------------

1. Two separated target row bands are derived deterministically from cabin size.
2. Blocker-prone seats remain concentrated around their aisle-specific bands.
3. Within each aisle queue, target-band and blocker-prone passengers receive an
   earlier deterministic queue score.
4. Left and right queues are scored independently using corresponding target
   bands so their stress waves can overlap.
5. Entry-headway values are not reduced or bypassed.
6. No passenger order changes after simulation begins.
7. No region is inserted, extended or held alive by the dataset generator.
8. A competition is counted only when the frozen runtime architecture observes
   two confirmed and eligible regions simultaneously.

New Evidence Collected
----------------------

- dependency regions created and confirmed;
- maximum simultaneous active regions;
- priority competitions and lower-priority deferrals;
- hierarchical selections and left/right wins;
- region-lifecycle overlap;
- cluster selections and cluster-started events;
- complete cabins and seated totals;
- residual stall families;
- simulation ticks as a secondary comparison.

Experimental Hypothesis
-----------------------
If Experiment 4 failed primarily because its two spatial zones activated at
different times, deterministic queue alignment should increase lifecycle overlap
and create more genuine priority competitions without changing the architecture
or entry-headway mechanism.

A null result would indicate that spatial and temporal alignment remain
insufficient and that a later dataset may need controlled admission density or a
more explicit multi-wave construction.

Interpretation Safeguards
-------------------------

- Queue alignment is fixed before execution and is not reactive passenger
  behaviour.
- Synchronous ticks remain unchanged.
- Headway remains a controlled scenario characteristic.
- The dataset does not hold passengers to preserve an active region.
- More congestion is not automatically a successful result; the primary target
  is independent simultaneous confirmed regions.
- Any deterioration in boarding completion must be reported as a dataset cost.
- Priority competition must not be inferred from two designed row bands; it must
  be measured by the frozen architecture.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Maximum simultaneous active and confirmed regions.
3. Hierarchical selections and lower-priority deferrals.
4. Region-lifecycle overlap evidence.
5. Confirmed regions and region lifetimes.
6. Cluster selections and starts.
7. Complete cabins and seated totals.
8. Residual stall classifications.
9. Simulation ticks as a secondary measure.

Diagram Plan
------------
A later diagram may show two pre-run deterministic entry queues feeding separated
left- and right-aisle target bands during corresponding time windows. The diagram
must distinguish planned dataset timing from runtime dependency detection and
must not imply asynchronous execution, passenger holding or inserted congestion.

======================================================================
EXPERIMENT 5 FINDINGS - DUAL-AISLE DEPENDENCY TIMING ALIGNMENT
======================================================================

Execution Summary
-----------------
Experiment 5 completed 30 deterministic paired scenarios, producing 60 scenario
executions. Both paired modes used the frozen Experiment 23 architecture,
identical cabin configuration, occupancy, entry-headway range and scenario seed.
Only the pre-run construction of the dual-aisle entry queues changed.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Timing-alignment average completion: 99.85%.
- Average change: +0.14 percentage points.
- Improved pairs: 3 of 30.
- Unchanged pairs: 24 of 30.
- Worse pairs: 3 of 30.
- Net additional passengers seated: +8.
- Standard complete cabins: 27.
- Timing-alignment complete cabins: 27.
- Standard dependency regions: 37.
- Timing-alignment dependency regions: 6.
- Standard confirmed regions: 22.
- Timing-alignment confirmed regions: 6.
- Standard cluster selections: 25.
- Timing-alignment cluster selections: 5.
- Standard cluster-started events: 31.
- Timing-alignment cluster-started events: 4.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Deterministic timing changed outcomes in both directions.

The timing-alignment dataset converted three standard stalls to complete cabins,
but it also introduced three new incomplete outcomes. This confirms that
temporal dataset construction is a genuine stress variable rather than a
one-directional improvement mechanism.

2. Timing could remove a previously stable congestion structure.

Scenario 4 changed from a 200/204 rear-boundary lock to complete boarding.
Scenario 29 changed from a 258/274 mixed residual dependency to complete
boarding. These cases demonstrate that deterministic queue timing can alter the
dependency topology sufficiently to prevent an otherwise stable stall.

3. Timing could also create new linked row-event chains.

Scenario 5 changed from complete boarding to 233/235 with a linked row-event
chain. Scenario 30 changed from complete boarding to 286/288 with another linked
row-event chain. The timing dataset therefore created distinct deterministic
dependencies even though movement rules and entry-headway ranges were unchanged.

4. Broad timing alignment simplified dependency-region activity overall.

Despite the mixed outcome changes, dependency regions fell from 37 to 6 and
confirmed regions fell from 22 to 6. Cluster selections and cluster-started
events also reduced sharply. The aligned queues frequently produced orderly
local seat-event sequences rather than two sustained independent congestion
zones.

5. No hierarchical competition occurred.

The central objective was not achieved. Priority competitions remained zero,
showing that spatial separation plus broad temporal alignment was still
insufficient to create two simultaneously confirmed and eligible regions.

6. The result supports a more constructive two-wave design.

The next dataset should not merely bring both aisle zones forward at similar
times. It should first seed potential seated blockers in each target zone and
then introduce deeper-seat passengers behind them, creating the prerequisites
for independent blocker-dependent congestion on both aisles.

Scientific Interpretation
-------------------------
Experiment 5 confirms that time is a separate deterministic component of
dependency topology. However, simply aligning two broad stress waves does not
guarantee simultaneous dependency regions. The internal order of passengers
within each wave is equally important because congestion requires a specific
sequence: blockers must become seated before later passengers require access to
deeper seats.

This finding preserves the first-principles nature of the programme. No runtime
behaviour was added and no passenger was held in response to congestion. The
evidence arose solely from deterministic pre-run dataset construction.

Experiment 5 Conclusion
-----------------------
Dual-aisle timing alignment is supported as an influential dataset variable but
not as a sufficient standalone method for exercising hierarchical region
priority. The next experiment should use deterministic blocker-seeding and
dependency-trigger waves on both aisles to construct a stronger opportunity for
simultaneous confirmed regions.


======================================================================
DISCUSSION - FROM TIMING ALIGNMENT TO CONSTRUCTIVE CONVERGENCE
======================================================================

The first five stress experiments demonstrate that congestion does not arise
from a single variable in isolation. Row concentration, blocker-prone seat
distribution, spatial separation and timing can each alter the outcome, but the
desired multi-region state requires these elements to occur in the correct
causal order.

For a blocker-dependent row event to form, an aisle-side or intermediate
passenger must first become seated. A later passenger assigned to a deeper seat
must then reach the same row while the required temporary yield tiles are
occupied or otherwise unavailable. To create two independent regions, this
sequence must occur in two separated aisle-specific zones during overlapping
lifecycle windows.

Experiment 6 therefore remains a dataset experiment rather than an architectural
or behavioural intervention. It constructs the causal prerequisites before the
run begins but allows the frozen movement engine to determine whether genuine
congestion actually forms.


======================================================================
EXPERIMENT 6 - CONSTRUCTIVE DEPENDENCY CONVERGENCE
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original people-movement algorithm operates on explicit occupancy states
and deterministic scan order. Experiment 6 applies the same principle to dataset
construction by arranging two pre-run occupancy sequences:

1. passengers likely to become seated blockers;
2. passengers whose deeper seats may later require those blockers to yield.

The movement engine remains unchanged. The dataset creates only the initial
ordering conditions from which the original deterministic architecture may
produce congestion naturally.

Planned Purpose
---------------
Determine whether a deterministic two-wave sequence on each aisle can produce
two independent blocker-dependent congestion regions whose confirmed lifecycles
overlap sufficiently to activate the frozen hierarchical prioritisation layer.

Paired Modes
------------
Each scenario is executed twice with the same cabin, occupancy, entry-headway
range and scenario seed.

1. STANDARD DETERMINISTIC DATASET

   The established seeded manifest with independently shuffled aisle queues.

2. CONSTRUCTIVE DEPENDENCY CONVERGENCE DATASET

   The dual-zone manifest is retained. Each aisle queue is divided
   deterministically into:

   - Wave A: target-zone passengers seated close to the serving aisle, intended
     only to establish potential blockers through normal boarding;
   - Wave B: target-zone passengers assigned to deeper seats, arriving after
     Wave A and therefore capable of generating blocker-dependent seat events;
   - remaining passengers, admitted afterwards under the same headway rules.

Left and right aisle waves are constructed independently but use corresponding
target zones, giving both dependency structures an opportunity to converge in
time.

Independent Variable
--------------------

    PRE-RUN BLOCKER-SEEDING AND DEPENDENCY-TRIGGER WAVE ORDER

This is a deterministic dataset variable. It does not modify seat-event rules,
passenger movement, runtime scheduling or architectural priority.

Controlled Conditions
---------------------

- frozen Experiment 23 congestion-management architecture;
- identical cabin configuration and occupancy;
- identical scenario seed;
- identical entry-headway range;
- one unique assigned seat per passenger;
- fixed serving aisle after manifest creation;
- synchronous global execution;
- maximum one forward aisle tile per passenger per tick;
- no backward movement, overtaking or aisle switching;
- no movement beyond the assigned row;
- unchanged blocker, yield-space and middle-bank reservation rules;
- unchanged clustering, lifecycle, confirmation, gating and hierarchy;
- unchanged stall detector and maximum tick limit;
- no behavioural assumptions or asynchronous execution.

Constructive Convergence Contract
---------------------------------

1. Two separated target row bands are derived from cabin size.
2. The manifest retains deterministic blocker-prone occupancy around both bands.
3. Wave A contains target-band passengers closest to their serving aisle.
4. Wave B contains target-band passengers assigned to deeper seats.
5. Wave A is ordered before Wave B independently on each aisle.
6. The same numerical entry-headway range remains active.
7. No passenger is delayed after execution begins to preserve the waves.
8. No seated blocker is artificially inserted.
9. No congestion region is inserted, extended or protected.
10. A priority competition is recorded only when the frozen runtime architecture
    observes multiple confirmed and eligible regions simultaneously.

New Evidence Collected
----------------------

- dependency regions created and confirmed;
- maximum simultaneous active regions;
- simultaneous confirmed-region competitions;
- hierarchical selections and lower-priority deferrals;
- left/right priority wins and priority ties;
- region lifetimes and overlap;
- blocker-dependent seat-event attempts;
- single- and multiple-blocker seat events;
- cluster selections and cluster-started events;
- complete cabins and seated totals;
- residual stall families;
- simulation ticks as a secondary measure.

Experimental Hypothesis
-----------------------
If the absence of priority competition in Experiment 5 resulted from an
incorrect within-wave causal order, seating potential blockers before deeper-seat
passengers should create more persistent independent dependencies and increase
the probability of simultaneous confirmed-region competition.

A null result would indicate that queue-wave construction alone remains
insufficient and that later work may need a more narrowly targeted benchmark
catalogue or controlled variation in admission density.

Interpretation Safeguards
-------------------------

- Wave order is fixed before execution.
- Wave A does not guarantee that a passenger becomes a blocker.
- Wave B does not guarantee that a seat event becomes blocked.
- The runtime architecture remains solely responsible for detecting regions.
- Headway remains unchanged within each paired scenario.
- No passenger is held because a region has or has not formed.
- More incomplete cabins are a dataset cost, not automatically a success.
- The primary success criterion is genuine simultaneous confirmed-region
  competition, not congestion volume alone.
- Zero competitions must be reported honestly.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Maximum simultaneous active and confirmed regions.
3. Hierarchical selections and lower-priority deferrals.
4. Confirmed-region lifecycle overlap.
5. Regions created, confirmed and dissolved.
6. Blocker-dependent and multiple-blocker seat-event evidence.
7. Cluster selections and starts.
8. Complete cabins and seated totals.
9. Residual stall classifications.
10. Simulation ticks as a secondary measure.

Diagram Plan
------------
A later diagram may show matching left- and right-aisle target zones with Wave A
aisle-side passengers entering first and Wave B deeper-seat passengers following.
The diagram must show that congestion is an observed runtime result rather than
an inserted dataset object and must not imply passenger holding, asynchronous
execution or changed headway.

======================================================================
EXPERIMENT 6 FINDINGS - CONSTRUCTIVE DEPENDENCY CONVERGENCE
======================================================================

Execution Summary
-----------------
Experiment 6 completed 30 deterministic paired scenarios, producing 60 scenario
executions. Both paired modes used the frozen Experiment 23 architecture,
identical cabin configuration, occupancy, scenario seed and entry-headway range.
Only deterministic pre-run manifest and aisle-queue construction changed.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Constructive-convergence average completion: 99.93%.
- Average change: +0.22 percentage points.
- Improved pairs: 3 of 30.
- Unchanged pairs: 26 of 30.
- Worse pairs: 1 of 30.
- Net additional passengers seated: +17.
- Standard complete cabins: 27.
- Constructive-convergence complete cabins: 29.
- Standard dependency regions: 37.
- Constructive-convergence dependency regions: 1.
- Standard confirmed regions: 22.
- Constructive-convergence confirmed regions: 1.
- Standard cluster selections: 25.
- Constructive-convergence cluster selections: 0.
- Standard cluster-started events: 31.
- Constructive-convergence cluster-started events: 0.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Constructive wave ordering changed deterministic outcomes substantially.

The dataset converted Scenarios 4, 17 and 29 from incomplete standard outcomes
to complete cabins. Scenario 29 recovered 16 passengers, changing from 258/274
to 274/274. These results confirm that pre-run causal ordering can alter the
resulting dependency topology without changing movement or architecture.

2. The same ordering also created a new dependency family.

Scenario 10 changed from complete boarding to 337/342 and terminated with a
MOVING_PASSENGER_YIELD_CHAIN. The trigger passenger, moving yield-tile occupant
and downstream waiting row event formed a persistent deterministic chain. This
shows that the dataset is a genuine stress variable rather than a general
boarding improvement.

3. The intended blocker-seeding sequence usually simplified the cabin.

Across the complete batch, dependency regions fell from 37 to 1 and confirmed
regions fell from 22 to 1. The causal ordering generally allowed aisle-side
passengers to sit and deeper-seat passengers to follow in an orderly sequence,
thereby removing many naturally occurring conflicts instead of creating two
independent congestion zones.

4. The central multi-region objective remained unmet.

No priority competition, hierarchical selection or lower-priority deferral was
recorded. Experiment 6 therefore did not produce two simultaneously confirmed
and eligible dependency regions.

5. The limiting factor is now lifecycle overlap rather than congestion creation.

Experiments 2-6 have demonstrated that deterministic datasets can create,
remove and transform congestion. The remaining challenge is narrower: two
independent regions must form and remain active during overlapping lifecycle
windows. Increasing blocker frequency alone is not sufficient.

Scientific Interpretation
-------------------------
Experiment 6 provides strong first-principles evidence that the internal causal
order of a boarding manifest affects dependency topology. Potential blockers,
rearward aisle occupancy and deeper-seat arrivals do not combine mechanically;
their precise order determines whether a dependency forms, resolves quickly or
becomes a persistent yield chain.

The experiment also guards against a misleading assumption: deliberately
seating blockers first does not necessarily intensify congestion. In many cases
it regularises seat access and reduces region formation. A useful multi-region
stress dataset must therefore create both a blocked event and a sufficiently
long-lived local yield-space conflict.

Experiment 6 Conclusion
-----------------------
Constructive dependency convergence is supported as an influential deterministic
dataset technique, but it is rejected as a sufficient method for exercising the
hierarchical prioritisation layer. The next experiment should target the natural
lifetime of two independent regions by creating local downstream yield-corridor
pressure around both aisle-specific target bands.


======================================================================
DISCUSSION - WHY REGION LIFETIME NOW BECOMES THE PRIMARY VARIABLE
======================================================================

The preceding experiments initially asked how independent congestion zones could
be created. Experiment 6 narrows the problem further. The frozen hierarchy can
only compare two regions if both have passed detection and confirmation and are
still eligible at the same tick. Two regions that occur sequentially do not
constitute a priority competition, even if both are individually significant.

The next experiment therefore does not preserve regions artificially and does
not modify lifecycle thresholds. Instead, it changes only the pre-run dataset so
that each target zone contains a natural source of downstream yield-space
pressure. Potential blockers enter first, passengers assigned just beyond the
target zone then occupy the rear corridor, and deeper-seat trigger passengers
follow. If a dependency forms, the occupied corridor may allow it to persist
long enough for the independent region on the other aisle to reach confirmation.

This remains a first-principles dataset investigation. The architecture does not
know which passengers belong to a wave, no passenger is held after execution
begins, and no region is extended by code once it forms.


======================================================================
EXPERIMENT 7 - DUAL-REGION DEPENDENCY LIFECYCLE EXTENSION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original people-movement algorithm represents flow through explicit
occupancy states and deterministic ordering. Experiment 7 uses the same idea at
the dataset level: two independent passenger sequences are constructed so that
normal forward movement may create persistent occupancy dependencies around two
separated row bands.

The passenger movement algorithm remains unchanged. The experiment controls only
which assigned passengers appear earlier in each deterministic aisle queue.

Planned Purpose
---------------
Determine whether local downstream yield-corridor pressure can extend the
natural lifetime of two independently formed dependency regions sufficiently to
produce simultaneous confirmed-region competition.

Paired Modes
------------
Each scenario is executed twice with the same cabin, occupancy, entry-headway
range and scenario seed.

1. STANDARD DETERMINISTIC DATASET

   The established seeded manifest with independently shuffled aisle queues.

2. DUAL-REGION LIFECYCLE EXTENSION DATASET

   Two separated aisle-specific target bands are retained. Each serving-aisle
   queue is constructed in four deterministic phases:

   - Phase 0: target-band passengers close to the serving aisle, capable of
     becoming seated blockers through normal movement;
   - Phase 1: passengers assigned just beyond the target band, capable of
     occupying the downstream/rear yield corridor;
   - Phase 2: deeper-seat target-band passengers, capable of triggering
     blocker-dependent row events;
   - Phase 3: adjacent-row reinforcement passengers, capable of sustaining
     local occupancy pressure while the independent aisle region forms.

Independent Variable
--------------------

    PRE-RUN DUAL-REGION YIELD-CORRIDOR PRESSURE ORDER

This is a deterministic dataset variable. It does not modify runtime movement,
seat-event rules, lifecycle thresholds or architectural priority.

Controlled Conditions
---------------------

- frozen Experiment 23 congestion-management architecture;
- identical cabin configuration and occupancy;
- identical scenario seed;
- identical numerical entry-headway range;
- one unique assigned seat per passenger;
- fixed serving aisle after manifest creation;
- synchronous global execution;
- maximum one forward aisle tile per passenger per tick;
- no backward movement, overtaking or aisle switching;
- no movement beyond the assigned row;
- unchanged blocker, yield-space and middle-bank reservation rules;
- unchanged clustering, lifecycle, confirmation, gating and hierarchy;
- unchanged stall detector and maximum tick limit;
- no human behaviour or asynchronous execution.

Lifecycle-Extension Contract
----------------------------

1. Two target bands are derived deterministically from cabin size.
2. Potential blockers are placed before the local trigger passengers.
3. Rear-corridor passengers are assigned seats beyond each target band and move
   under the ordinary forward-only rules.
4. Deeper-seat triggers then approach the target rows.
5. Adjacent reinforcement passengers follow.
6. The ordering is fixed before tick 1.
7. No passenger is held or released in response to runtime congestion.
8. No dependency region is inserted, protected or artificially prolonged.
9. Confirmation age and lifecycle rules remain unchanged.
10. A competition is recorded only by the frozen runtime hierarchy.

New Evidence Collected
----------------------

- maximum simultaneous active regions;
- regions reaching confirmation;
- priority competitions;
- regions ranked and hierarchical selections;
- lower-priority evaluations deferred;
- left/right priority wins and ties;
- largest region lifetime;
- region updates and dissolutions;
- yield-tile occupied failures;
- multiple-blocker seat events;
- moving-passenger yield chains;
- complete cabins and seated totals;
- residual stall families;
- simulation ticks as a secondary measure.

Experimental Hypothesis
-----------------------
If insufficient lifecycle overlap prevented hierarchical activation in
Experiment 6, deterministic downstream yield-corridor pressure should allow at
least some independently formed regions to persist while a second region reaches
confirmation.

A null result would indicate that the benchmark requires either more narrowly
constructed scenario-specific datasets or a controlled study of admission
density. It would not justify changing lifecycle thresholds or inserting regions.

Interpretation Safeguards
-------------------------

- More congestion is not automatically a successful result.
- A long-lived single region does not satisfy the multi-region objective.
- Two active regions do not count unless the frozen hierarchy regards them as
  confirmed and simultaneously eligible.
- Rear-boundary locks must be distinguished from genuine multi-region overlap.
- Wave labels exist only in pre-run construction and are invisible to runtime.
- Entry-headway values remain those selected for the paired scenario.
- No runtime intervention may be introduced to preserve a region.
- Zero competitions must be reported honestly.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Hierarchical selections and lower-priority deferrals.
3. Maximum simultaneous active and confirmed regions.
4. Largest region lifetime and lifecycle overlap evidence.
5. Regions created, confirmed and dissolved.
6. Yield-corridor and blocker-dependent evidence.
7. Cluster selections and starts.
8. Complete cabins and seated totals.
9. Residual stall classifications.
10. Simulation ticks as a secondary measure.

Diagram Plan
------------
A later diagram may show two separated target bands, each with a seated-blocker
wave, a downstream corridor-pressure wave and a deeper-seat trigger wave. It
must make clear that all ordering is defined before execution and that the
runtime architecture alone determines whether regions form and overlap.

======================================================================
EXPERIMENT 7 FINDINGS - DUAL-REGION DEPENDENCY LIFECYCLE EXTENSION
======================================================================

Execution Summary
-----------------
Experiment 7 completed 30 deterministic paired scenarios, producing 60 scenario
executions. Both modes used the frozen Experiment 23 architecture, the same
scenario seed, cabin, occupancy and entry-headway range. Only deterministic
pre-run queue construction changed.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Lifecycle-extension average completion: 99.89%.
- Improved pairs: 3 of 30.
- Unchanged pairs: 25 of 30.
- Worse pairs: 2 of 30.
- Net additional passengers seated: +11.
- Standard complete cabins: 27.
- Lifecycle-extension complete cabins: 28.
- Standard dependency regions: 37.
- Lifecycle-extension dependency regions: 5.
- Standard confirmed regions: 22.
- Lifecycle-extension confirmed regions: 5.
- Standard cluster selections: 25.
- Lifecycle-extension cluster selections: 5.
- Standard cluster-started events: 31.
- Lifecycle-extension cluster-started events: 5.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. The lifecycle-extension ordering did not extend multi-region lifetimes.

Although the dataset was designed to preserve independent congestion, it reduced
dependency-region creation from 37 to 5 and confirmed regions from 22 to 5.
The structured phases therefore simplified most dependency evolution rather than
keeping two regions alive simultaneously.

2. Additional deterministic order frequently regularised boarding.

The dataset again converted several difficult standard outcomes into complete
boarding, including the established Scenario 4 rear-boundary lock. This confirms
that orderly causal sequencing can remove congestion even when the intention is
to preserve it.

3. Some adverse outcomes remained possible.

Two paired scenarios became worse, showing that the dataset was not simply an
optimisation policy. It genuinely altered dependency topology, but those adverse
cases still formed isolated rather than competing confirmed regions.

4. No hierarchical competition occurred.

Priority competitions and lower-priority deferrals remained zero. The completed
hierarchy therefore still had no occasion to choose between two simultaneously
confirmed eligible regions.

5. Lifecycle duration cannot be increased merely by adding broader reinforcement.

The additional corridor and adjacent-row phases often allowed dependencies to
resolve cleanly before a second independent region matured. More deterministic
structure therefore reduced the phenomenon under investigation.

Scientific Interpretation
-------------------------
Experiment 7 demonstrates that making a dependency sequence longer or more
ordered is not equivalent to extending the lifetime of a detected dependency
region. The runtime region exists only while the actual unresolved occupancy and
seat-event prerequisites remain present. Pre-run ordering that improves causal
flow may therefore shorten or prevent the region even when more passengers are
assigned around the target zone.

The evidence shifts the research question from increasing dependency volume to
preserving causal independence. Two regions must be allowed to form without
shared middle-bank activity, broad queue ordering or downstream passengers
inadvertently resolving one another.

Experiment 7 Conclusion
-----------------------
Dual-region lifecycle extension is not supported as a reliable method for
producing simultaneous confirmed-region competition. The next experiment should
isolate the causal domains of the two candidate regions, using aisle-specific
outer-bank bands and postponing shared middle-bank activity until after the
independent structures have had an opportunity to form.


======================================================================
DISCUSSION - ORDER, LIFETIME AND CAUSAL INDEPENDENCE
======================================================================

Experiments 5-7 show that deterministic order can both create and remove
congestion. Timing alignment, blocker-first construction and lifecycle
reinforcement all changed outcomes, but increasingly ordered datasets often
became easier for the cabin to process.

This is scientifically important. A dependency region is not a permanent object
inserted by the dataset. It is a temporary runtime consequence of unresolved
seat-event prerequisites and occupied aisle space. If the dataset organises
passengers too efficiently, the architecture correctly observes no region.

The next step is therefore not to add more passengers or more phases. It is to
separate the two causal systems. Each aisle should receive its own outer-bank
target band, while shared middle-bank passengers are delayed in the pre-run
manifest. Any resulting regions must still arise naturally through the frozen
movement and seat-event rules.


======================================================================
EXPERIMENT 8 - INDEPENDENT REGION ISOLATION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original people-movement algorithm reasons from local occupancy and
explicit movement constraints. Experiment 8 applies the same principle by
constructing two independent local input domains before execution. The left and
right aisle target bands are separated, and their early passengers are drawn
only from the corresponding outer seat banks.

The movement engine does not know that the bands are experimental objects. It
continues to process ordinary passenger IDs, occupied aisle tiles and seat-event
requirements exactly as before.

Planned Purpose
---------------
Determine whether isolating two aisle-specific outer-bank dependency ecosystems
allows both regions to form and remain confirmed simultaneously without merging,
resolving one another or relying upon shared middle-bank interactions.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

   The established seeded manifest and independently shuffled aisle queues.

2. INDEPENDENT REGION ISOLATION DATASET

   Two separated target bands are retained. For each aisle independently:

   - potential blockers in that aisle's outer bank enter first;
   - deeper-seat passengers in the same outer-bank band follow;
   - adjacent outer-bank reinforcement follows;
   - remaining passengers from that outer bank are admitted;
   - middle-bank and other shared passengers enter later.

Independent Variable
--------------------

    PRE-RUN ISOLATION OF TWO AISLE-SPECIFIC OUTER-BANK CAUSAL DOMAINS

Controlled Conditions
---------------------

- frozen Experiment 23 congestion-management architecture;
- identical cabin configuration, occupancy and scenario seed;
- identical entry-headway range;
- synchronous deterministic execution;
- one unique assigned seat per passenger;
- no runtime holding, inserted congestion or artificial region persistence;
- no backward movement, overtaking or aisle switching;
- no passenger moving beyond the assigned row;
- unchanged blocker, yield-space and middle-bank rules;
- unchanged clustering, lifecycle confirmation, state-change gating and
  hierarchical prioritisation;
- unchanged stall detector and maximum tick limit;
- no human-behaviour assumptions.

Isolation Contract
------------------

1. Left and right target bands remain spatially separated.
2. Early left-band passengers use only the left outer bank.
3. Early right-band passengers use only the right outer bank.
4. Middle-bank passengers are excluded from the early isolation phases.
5. Potential blockers enter before deeper-seat triggers in each isolated band.
6. No passenger is held after execution begins.
7. Numerical entry-headway ranges remain unchanged.
8. The runtime architecture alone decides whether a dependency region exists.
9. A competition is counted only when multiple confirmed eligible regions
   coexist under the frozen hierarchy.

Primary Evidence
----------------

- dependency regions created and confirmed;
- maximum simultaneous active regions;
- priority competitions;
- hierarchical selections and lower-priority deferrals;
- left/right priority wins and ties;
- region lifetimes and simultaneous overlap;
- single- and multiple-blocker seat events;
- middle-bank reservation activity;
- cluster selections and cluster-started events;
- complete cabins and seated totals;
- residual stall families;
- simulation ticks as a secondary measure.

Experimental Hypothesis
-----------------------
If shared middle-bank activity and broad queue reinforcement were prematurely
resolving or coupling the two candidate regions, isolating the early outer-bank
causal domains should increase the probability that left and right confirmed
regions coexist.

A null result would indicate that the present benchmark generator cannot
reliably create simultaneous regions through general distribution rules alone.
A later phase may then require a small catalogue of explicitly selected,
deterministic stress manifests rather than further broad generator changes.

Interpretation Safeguards
-------------------------

- Isolation is a pre-run dataset property, not a runtime policy.
- Delaying middle-bank passengers does not change their assigned seats.
- No region is inserted or protected.
- More incomplete cabins are not automatically a successful result.
- The primary criterion remains genuine simultaneous confirmed-region
  competition.
- Zero competitions must be documented without reinterpretation.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Maximum simultaneous active and confirmed regions.
3. Hierarchical selections and lower-priority deferrals.
4. Region-lifecycle overlap.
5. Regions created, confirmed and dissolved.
6. Blocker-dependent seat-event evidence.
7. Cluster selections and starts.
8. Complete cabins and seated totals.
9. Residual stall classifications.
10. Simulation ticks.

Diagram Plan
------------
A later diagram may show two separated outer-bank row bands, one attached to
each aisle, with shared middle-bank passengers placed in a later admission
layer. The diagram must not imply physical barriers, runtime holding or modified
movement rules.

======================================================================
EXPERIMENT 8 FINDINGS - INDEPENDENT REGION ISOLATION
======================================================================

Execution Summary
-----------------
Experiment 8 completed 30 deterministic paired scenarios, producing 60 scenario
executions. The frozen Experiment 23 architecture, scenario seed, cabin,
occupancy and entry-headway range remained identical in each pair. Only the
pre-run isolation of the two aisle-specific causal domains changed.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Independent-isolation average completion: 100.00%.
- Improved pairs: 3 of 30.
- Unchanged pairs: 27 of 30.
- Worse pairs: 0 of 30.
- Net additional passengers seated: +22.
- Standard complete cabins: 27.
- Isolation complete cabins: 30.
- Standard dependency regions: 37.
- Isolation dependency regions: 4.
- Standard confirmed regions: 22.
- Isolation confirmed regions: 4.
- Standard cluster selections: 25.
- Isolation cluster selections: 5.
- Standard cluster-started events: 31.
- Isolation cluster-started events: 5.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Independent isolation produced complete boarding in all 30 stress executions.

The dataset converted all three incomplete standard outcomes to complete cabins,
including the recurring Scenario 4 rear-boundary lock. It introduced no new
incomplete outcome.

2. Isolation strongly suppressed dependency formation.

Dependency regions fell from 37 to 4 and confirmed regions fell from 22 to 4.
The early outer-bank separation therefore prevented most blocker/yield
interactions rather than preserving two independent congestion ecosystems.

3. Multiple-blocker activity was reduced in many scenarios.

The detailed reports show that the isolation ordering frequently allowed
aisle-side and intermediate passengers to seat before deeper-seat arrivals
created a sustained queue. The resulting seat events were simpler and failed
less often.

4. No hierarchical competition occurred.

Priority competitions and lower-priority deferrals remained zero. The hierarchy
again had no occasion to rank two simultaneously confirmed eligible regions.

5. Excessive causal separation is effectively an optimisation.

Although designed as a stress dataset, the isolation manifest behaved like a
highly orderly boarding policy. It removed the interactions required for
dependency regions to form.

Scientific Interpretation
-------------------------
Experiment 8 demonstrates that independent regions cannot be obtained merely by
separating aisle-specific passenger groups. Dependency regions require enough
interaction to create blocked seat-event prerequisites, but not so much coupling
that the regions merge or resolve one another.

The broad generator has therefore reached a practical limit. Repeated global
ordering rules either simplify boarding or create isolated single-region
outcomes. The next stage should move from one universal stress generator to a
small deterministic catalogue of explicitly defined benchmark topologies.

Experiment 8 Conclusion
-----------------------
Independent Region Isolation is rejected as a method for producing simultaneous
confirmed-region competition. It is retained as evidence that deterministic
manifest design can eliminate known stalls and that excessive isolation removes
the phenomenon under study.


======================================================================
DISCUSSION - WHY A BENCHMARK CATALOGUE IS NOW REQUIRED
======================================================================

Experiments 1-8 systematically tested broad deterministic variables: row
concentration, blocker-prone seats, spatial separation, timing, constructive
waves, lifecycle reinforcement and causal isolation.

The evidence now shows that no single general ordering rule reliably produces
the rare multi-region state. Broad rules tend either to regularise boarding or
to generate one dominant local dependency.

A benchmark catalogue is therefore scientifically preferable. Each catalogue
family can represent a named dependency topology while the runtime architecture
remains frozen. This follows normal algorithm-evaluation practice: rare
architectural capabilities are tested with reproducible constructed instances
rather than waiting for random workloads to produce them.


======================================================================
EXPERIMENT 9 - DETERMINISTIC DEPENDENCY BENCHMARK CATALOGUE
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original algorithm separates deterministic input construction from
occupancy-based execution. Experiment 9 preserves that separation. The benchmark
catalogue defines only the starting passenger order; Amit's movement logic and
the frozen dependency-region architecture decide every runtime state.

Planned Purpose
---------------
Determine whether a small reproducible catalogue of distinct deterministic
dependency topologies can exercise a wider range of architectural behaviour than
one universal stress generator, including genuine simultaneous confirmed-region
competition.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

2. DETERMINISTIC DEPENDENCY BENCHMARK CATALOGUE

   The 30 scenarios cycle through five reproducible benchmark families:

   A. Isolated outer-bank blocker/trigger topology.
   B. Tightly localised simultaneous-confirmation candidate.
   C. Separated long-chain topology with adjacent reinforcement.
   D. Controlled interaction topology with delayed middle-bank participation.
   E. Mixed topology retaining limited seeded variation.

Independent Variable
--------------------

    NAMED DETERMINISTIC BENCHMARK TOPOLOGY FAMILY

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin, occupancy, seed and entry-headway range;
- synchronous deterministic execution;
- unchanged passenger movement and seat-event rules;
- no runtime holding or inserted dependency region;
- no backward movement, overtaking or aisle switching;
- no passenger movement beyond the assigned row;
- unchanged lifecycle confirmation and hierarchy thresholds;
- no behavioural or asynchronous variables.

Benchmark Catalogue Contract
----------------------------

1. Each scenario is assigned one of five families deterministically.
2. Left and right target rows remain reproducible.
3. Potential blockers precede deeper-seat triggers within each family.
4. Middle-bank participation differs by family but is always pre-run.
5. No family changes runtime movement.
6. No family guarantees that a region will form.
7. A successful hierarchy test requires genuine simultaneous confirmed eligible
   regions observed by the frozen architecture.

Primary Evidence
----------------

- priority competitions and lower-priority deferrals;
- maximum simultaneous active regions;
- regions created and confirmed;
- hierarchical selections;
- left/right wins and ties;
- region lifetimes;
- cluster selections and starts;
- residual stall families;
- complete cabins and seated totals;
- family-specific outcome patterns.

Experimental Hypothesis
-----------------------
A catalogue containing several narrowly constructed topologies should provide
better architectural coverage than a single broad generator. At least one
family may produce genuine simultaneous confirmed-region competition even if
other families simplify boarding or remain null.

A complete null result would establish that the present movement model and
region detector require an explicitly hand-authored minimal benchmark instance
rather than family-level manifest rules.

Interpretation Safeguards
-------------------------

- Catalogue families are test instances, not proposed airline policies.
- Better completion is secondary to architectural coverage.
- More congestion alone is not success.
- No runtime state is inserted or protected.
- Family-level null results remain valid evidence.
- Priority competition must be reported exactly as recorded.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Family producing the competition.
3. Maximum simultaneous active and confirmed regions.
4. Hierarchical selections and deferrals.
5. Region lifetimes and overlap.
6. Dependency and cluster evidence.
7. Residual stall topology.
8. Completion and seated totals.
9. Tick counts.

Diagram Plan
------------
A later diagram may present the five benchmark families as separate cabin
miniatures with their left/right target bands and blocker/trigger ordering.
The figure must make clear that these are deterministic test manifests rather
than runtime barriers or airline boarding policies.

======================================================================
EXPERIMENT 9 FINDINGS - DETERMINISTIC DEPENDENCY BENCHMARK CATALOGUE
======================================================================

Execution Summary
-----------------
Experiment 9 completed 30 deterministic paired scenarios, producing 60 scenario
executions. The full experiment was executed twice. The repeated run reproduced
the same principal outcomes, confirming deterministic replay.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Catalogue average completion: 99.93%.
- Improved pairs: 3 of 30.
- Unchanged pairs: 26 of 30.
- Worse pairs: 1 of 30.
- Net additional passengers seated: +17.
- Standard complete cabins: 27.
- Catalogue complete cabins: 29.
- Standard dependency regions: 37.
- Catalogue dependency regions: 3.
- Standard confirmed regions: 22.
- Catalogue confirmed regions: 3.
- Standard cluster selections: 25.
- Catalogue cluster selections: 2.
- Standard cluster-started events: 31.
- Catalogue cluster-started events: 2.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. The catalogue produced reproducible named benchmark behaviour.

The second complete execution reproduced the same principal scenario outcomes,
including the Scenario 4 conversion from rear-boundary lock to complete boarding
and the absence of hierarchical competition.

2. The catalogue successfully produced confirmed dependency regions.

Three catalogue regions reached lifecycle confirmation. This establishes that
narrowly defined benchmark families can produce architecture-visible dependency
objects rather than merely changing total boarding time.

3. The catalogue remained an effective stall-removal mechanism.

Scenario 4 again changed from 200/204 with a persistent rear-boundary lock to
204/204 complete boarding. The catalogue therefore altered the causal topology
enough to remove a known deterministic failure.

4. One adverse catalogue outcome remained.

One paired scenario became incomplete, demonstrating that the catalogue was not
simply an optimisation policy. It could expose a different dependency family
while preserving deterministic execution.

5. No simultaneous confirmed-region competition occurred.

Despite three confirmed regions across the run, they appeared as isolated
events. Priority competitions and lower-priority deferrals remained zero.

Scientific Interpretation
-------------------------
Experiment 9 is supported as a deterministic benchmark generator but remains
incomplete as a hierarchy stress generator. Its strongest contribution is the
demonstration that named topology families can reproducibly create confirmed
regions and convert a genuine stall to success.

However, family-level ordering still specifies only statistical conditions from
which a dependency may emerge. It does not define the intended dependency graph
with sufficient precision to guarantee two concurrent confirmed structures.

Experiment 9 Conclusion
-----------------------
The Deterministic Dependency Benchmark Catalogue is retained as a valid research
instrument. The next experiment should move from broad topology families to an
explicit two-chain dependency specification in which the intended blocker roots,
deep-seat triggers and downstream yield-space occupants are defined before
execution.


======================================================================
DISCUSSION - FROM BENCHMARK FAMILIES TO EXPLICIT TOPOLOGY
======================================================================

Experiments 1-9 show that simultaneous dependency regions are not produced
reliably by increasing congestion probability alone. Row density, seat depth,
timing, isolation and benchmark families can all change outcomes, but the
required graph remains rare.

Experiment 10 therefore changes the level of specification. Instead of defining
a family likely to produce dependencies, it defines two intended local chains:

    potential blocker root
            |
    second blocker
            |
    deep-seat trigger
            |
    downstream yield-space pressure

One chain is constructed for each aisle at separated target rows. The graph is
not inserted into the runtime architecture. It is translated into passenger
assignments and pre-run queue order, after which the frozen movement engine must
either realise or reject the intended topology naturally.


======================================================================
EXPERIMENT 10 - EXPLICIT DETERMINISTIC DEPENDENCY TOPOLOGY GENERATOR
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original algorithm begins with explicit data and then applies local,
deterministic occupancy rules. Experiment 10 follows the same principle. The
input generator names the intended dependency components, but the original
movement and seat-event logic remains solely responsible for creating the actual
runtime state.

Planned Purpose
---------------
Determine whether two explicitly specified and spatially separated dependency
chains can become confirmed simultaneously and activate the frozen hierarchical
prioritisation layer.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

2. EXPLICIT DETERMINISTIC DEPENDENCY TOPOLOGY DATASET

   Each aisle receives one target row containing:

   - an aisle-side potential blocker;
   - a second potential blocker;
   - a deeper-seat trigger passenger;
   - downstream outer-bank passengers capable of occupying required yield space;
   - one adjacent-row deep-seat reinforcement;
   - limited delayed middle-bank participation.

Independent Variable
--------------------

    EXPLICIT PRE-RUN TWO-CHAIN DEPENDENCY TOPOLOGY SPECIFICATION

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin, occupancy, seed and entry-headway range;
- synchronous deterministic execution;
- unchanged movement and seat-event rules;
- no runtime passenger holding;
- no inserted dependency region;
- no artificial confirmation or lifecycle extension;
- no backward movement, overtaking or aisle switching;
- no movement beyond the assigned row;
- no human-behaviour or asynchronous variables.

Explicit Topology Contract
--------------------------

1. One target chain is defined for each aisle.
2. The target rows are spatially separated.
3. Potential blockers enter before the corresponding deep-seat trigger.
4. Downstream corridor occupants follow early enough to create natural
   yield-space pressure.
5. Adjacent-row reinforcement may extend each local chain.
6. Middle-bank passengers enter only after the outer-chain components.
7. No runtime state is forced.
8. The architecture must detect, confirm and rank any resulting regions itself.
9. Success requires genuine simultaneous confirmed eligible regions.

Primary Evidence
----------------

- priority competitions;
- lower-priority deferrals;
- maximum simultaneous active regions;
- regions confirmed on left and right aisles;
- hierarchical selections and priority wins;
- region overlap duration;
- intended-chain realisation count;
- cluster selections and starts;
- residual stall family;
- complete cabins and seated totals.

Experimental Hypothesis
-----------------------
Explicitly naming both blocker roots, deep-seat triggers and downstream
yield-space pressure should provide more reliable causal coverage than broad
benchmark families. At least one paired scenario may therefore produce two
simultaneously confirmed eligible dependency regions.

A null result would demonstrate that manifest and queue order alone cannot
realise the required graph under the present movement model. That would justify
closing the broad dataset-generator line and documenting the hierarchy as
architecturally valid but not naturally exercised by the available first-
principles boarding model.

Interpretation Safeguards
-------------------------

- The topology is an input specification, not a runtime intervention.
- Intended chains may fail to materialise.
- A single confirmed region is not hierarchy validation.
- More stalls are not automatically successful evidence.
- Repeated deterministic replay must remain exact.
- Zero competitions must be reported without reinterpretation.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Simultaneous confirmed left/right regions.
3. Hierarchical selections and deferrals.
4. Region overlap duration.
5. Intended-chain realisation.
6. Confirmed and dissolved regions.
7. Cluster evidence.
8. Stall topology.
9. Completion and tick counts.

Diagram Plan
------------
A later diagram may show two separated chains, one attached to each aisle, with
blocker roots, deep-seat triggers and downstream yield-pressure passengers.
The diagram must state that the graph is an intended deterministic input
topology and is not inserted into runtime state.

======================================================================
EXPERIMENT 10 FINDINGS - EXPLICIT DETERMINISTIC DEPENDENCY TOPOLOGY
======================================================================

Execution Summary
-----------------
Experiment 10 completed 30 deterministic paired scenarios, producing 60 scenario
executions. Both modes retained the frozen Experiment 23 architecture and the
same cabin, occupancy, scenario seed and entry-headway range.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Explicit-topology average completion: 99.93%.
- Improved pairs: 3 of 30.
- Unchanged pairs: 26 of 30.
- Worse pairs: 1 of 30.
- Net additional passengers seated: +17.
- Standard complete cabins: 27.
- Explicit-topology complete cabins: 29.
- Standard dependency regions: 37.
- Explicit-topology dependency regions: 1.
- Standard confirmed regions: 22.
- Explicit-topology confirmed regions: 1.
- Standard cluster selections: 25.
- Explicit-topology cluster selections: 0.
- Standard cluster-started events: 31.
- Explicit-topology cluster-started events: 0.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Explicit topology did not realise the intended two-chain graph.

The generator named potential blockers, deep-seat triggers and downstream
pressure, but the runtime architecture detected only one region across the
entire topology mode. No pair of confirmed eligible regions coexisted.

2. Strong pre-run specification again regularised boarding.

The explicit ordering converted three standard incomplete outcomes to improved
results, including the recurring Scenario 4 rear-boundary lock. Twenty-nine of
thirty topology cabins completed successfully.

3. Dependency formation was almost completely suppressed.

Regions fell from 37 to 1 and confirmed regions from 22 to 1. No cluster
selection or cluster-started event occurred in topology mode. The prescribed
sequence therefore removed most of the interactions required for dependencies
to emerge.

4. The hierarchy remained unexercised.

Priority competitions and lower-priority deferrals remained zero. This is not a
failure of the hierarchy; the required simultaneous confirmed inputs were never
presented to it.

5. Dependency regions are supported as emergent deterministic objects.

The evidence from Experiments 8-10 shows a consistent pattern: greater global
control over passenger order creates cleaner causal flow and fewer dependency
regions. A dependency graph cannot simply be written into the manifest and
assumed to appear at runtime.

Scientific Interpretation
-------------------------
Experiment 10 establishes a practical upper boundary for global pre-run
specification. Even an explicit two-chain design remains only an intended input
topology. Under the unchanged movement engine, passengers may seat cleanly
before the proposed blockers and triggers become mutually dependent.

The next experiment should therefore retain the natural standard manifest and
most of its seeded queue order, changing only a few local relationships. This
preserves emergence while allowing controlled tests of sensitivity around rows
where blocker-dependent events are plausible.

Experiment 10 Conclusion
------------------------
The Explicit Deterministic Dependency Topology Generator is rejected as a
reliable hierarchy stress generator. It is retained as evidence that excessive
pre-run control suppresses dependency formation and can remove known stalls.


======================================================================
DISCUSSION - RETURNING FROM PRESCRIPTION TO PERTURBATION
======================================================================

Experiments 8-10 progressively increased deterministic control: causal
isolation, benchmark families and explicit dependency chains. Dependency-region
coverage decreased as control increased.

Experiment 11 therefore does not prescribe a graph. It begins with the standard
seeded manifest and shuffled aisle queues, then applies only a few local,
reproducible transpositions around two target row windows. This is analogous to
a sensitivity test: the cabin remains natural except for a narrowly bounded
change whose consequences can be attributed clearly.


======================================================================
EXPERIMENT 11 - CONTROLLED DETERMINISTIC DEPENDENCY PERTURBATION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original algorithm evaluates local occupancy changes without globally
rewriting the complete state. Experiment 11 adopts the same principle at the
dataset layer. The standard deterministic queue is preserved and only a small
number of local passenger relationships are perturbed.

Planned Purpose
---------------
Determine whether minimal deterministic changes around two separated row
windows preserve natural dependency formation while increasing the probability
that two confirmed regions overlap.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

2. CONTROLLED DETERMINISTIC DEPENDENCY PERTURBATION DATASET

   The same standard passenger manifest and serving-aisle assignments are used.
   Each aisle queue begins with seeded random shuffling. At most four local
   blocker/deep-seat relationships are then adjusted around one target row.

Independent Variable
--------------------

    SMALL PRE-RUN LOCAL QUEUE PERTURBATIONS

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical passenger manifest, cabin, occupancy and scenario seed;
- identical serving-aisle assignment;
- identical entry-headway range;
- synchronous deterministic execution;
- unchanged movement and seat-event rules;
- no runtime holding or inserted region;
- no backward movement, overtaking or aisle switching;
- no movement beyond the assigned row;
- no behavioural or asynchronous variables.

Perturbation Contract
---------------------

1. The standard manifest is retained.
2. Each aisle begins with normal seeded shuffling.
3. Changes are limited to two narrow row windows.
4. Only adjacent local swaps and one displacement of at most two positions are
   permitted per aisle.
5. No seat, row or serving aisle is changed.
6. Most queue positions remain untouched.
7. No perturbation occurs after execution begins.
8. The frozen architecture alone determines whether regions form.

Primary Evidence
----------------

- priority competitions and deferrals;
- maximum simultaneous active regions;
- confirmed left/right region overlap;
- regions created and confirmed;
- cluster selections and starts;
- sensitivity of known standard region scenarios;
- residual stall families;
- complete cabins and seated totals;
- tick counts as secondary evidence.

Experimental Hypothesis
-----------------------
Minimal local perturbations should preserve more natural interaction than the
explicit topology generator. They may therefore retain ordinary dependency
formation while shifting the timing of two local structures enough to create
simultaneous confirmed-region competition.

A null result would support closure of the general dataset-construction line:
it would show that neither broad ordering nor narrowly bounded queue
perturbation can reliably exercise the hierarchy under the present model.

Interpretation Safeguards
-------------------------

- Perturbations are input sensitivity tests, not airline policies.
- No dependency graph is prescribed.
- A single confirmed region is not hierarchy validation.
- Improved completion is secondary to architectural coverage.
- More congestion is not automatically success.
- Zero competitions must be reported exactly.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Simultaneous confirmed left/right regions.
3. Hierarchical selections and deferrals.
4. Region-overlap duration.
5. Regions created and confirmed.
6. Cluster evidence.
7. Stall topology.
8. Completion and tick counts.

Diagram Plan
------------
A later diagram may show a mostly unchanged shuffled queue with only two or
three highlighted local transpositions around each target row. It must not
suggest runtime passenger holding or a prescribed dependency graph.

======================================================================
EXPERIMENT 11 FINDINGS - CONTROLLED DETERMINISTIC DEPENDENCY PERTURBATION
======================================================================

Execution Summary
-----------------
Experiment 11 completed 30 deterministic paired scenarios, producing 60 scenario
executions. The frozen Experiment 23 architecture, cabin, occupancy, scenario
seed and entry-headway range remained unchanged. Only small bounded pre-run
queue perturbations were introduced.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Perturbation average completion: 99.71%.
- Improved pairs: 0 of 30.
- Unchanged pairs: 30 of 30.
- Worse pairs: 0 of 30.
- Net passenger difference: 0.
- Standard complete cabins: 27.
- Perturbation complete cabins: 27.
- Standard dependency regions: 37.
- Perturbation dependency regions: 36.
- Standard confirmed regions: 22.
- Perturbation confirmed regions: 21.
- Standard cluster selections: 25.
- Perturbation cluster selections: 24.
- Standard cluster-started events: 31.
- Perturbation cluster-started events: 29.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Minimal perturbation preserved the natural dependency landscape.

Unlike Experiments 8-10, the perturbation dataset did not suppress region
formation globally. Aggregate dependency and confirmation counts remained close
to the standard baseline.

2. Small changes could reveal new confirmed structure locally.

Scenario 3 changed from no detected region under the standard dataset to one
confirmed region, one cluster selection and one cluster-started event under the
perturbation dataset.

3. Scenario 4 produced richer evidence without changing the stall outcome.

The standard run produced one confirmed rear-boundary region. The perturbation
run produced two regions and two confirmations, with one cluster selection and
one cluster start, while retaining the same 200/204 rear-boundary lock.

4. Two confirmed regions did not imply a priority competition.

Scenario 4 demonstrated that multiple regions may be created and confirmed at
different times. Priority competition remained zero because the confirmed,
eligible lifecycles did not overlap sufficiently for hierarchical arbitration.

5. Minimal perturbation behaved as a probe rather than an optimisation.

Completion, seated totals and all paired outcomes were unchanged. The
perturbations exposed different internal region evidence without broadly making
boarding easier or harder.

Scientific Interpretation
-------------------------
Experiment 11 marks an important transition. Dependency regions were no longer
being manufactured through broad manifest ordering. Instead, small deterministic
changes revealed sensitivity in naturally emerging dependency structures.

The remaining limitation is temporal overlap. The architecture can observe more
than one confirmed region within a scenario, but not at the same eligible moment.

Experiment 11 Conclusion
------------------------
Controlled deterministic perturbation is supported as a valid scientific probe.
Experiment 12 should preserve this minimal-intervention philosophy while aligning
the queue depth of the two local perturbation windows so their region lifecycles
have a greater opportunity to overlap.


======================================================================
EXPERIMENT 12 - DUAL-WINDOW PERTURBATION OVERLAP ALIGNMENT
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's algorithm retains deterministic local occupancy logic while allowing the
input ordering to be altered independently. Experiment 12 preserves the standard
seeded queues and applies only bounded local swaps plus a small pre-run
cross-aisle queue-depth alignment.

Planned Purpose
---------------
Determine whether two minimally perturbed local windows can mature during
overlapping lifecycle periods and produce genuine hierarchical competition.

Independent Variable
--------------------

    BOUNDED CROSS-AISLE ALIGNMENT OF TWO LOCAL PERTURBATION WINDOWS

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin, occupancy, scenario seed and headway range;
- synchronous deterministic execution;
- unchanged movement, seat-event, lifecycle and hierarchy rules;
- no runtime holding;
- no inserted or protected region;
- no backward movement, overtaking or aisle switching;
- no movement beyond the assigned row;
- no behavioural or asynchronous variables.

Experiment Contract
-------------------

1. Both aisle queues begin with the standard seeded shuffle.
2. At most six adjacent local swaps are permitted per aisle.
3. One deep trigger may move by no more than four local queue positions.
4. Cross-aisle trigger alignment may move one trigger by no more than three
   positions.
5. No seat, row or aisle assignment changes.
6. No runtime admission delay is introduced.
7. Success requires genuine simultaneous confirmed eligible regions.

Primary Evaluation Order
------------------------

1. Priority competitions.
2. Simultaneous confirmed-region overlap.
3. Hierarchical selections and deferrals.
4. Left/right priority wins and ties.
5. Confirmed regions and region lifetimes.
6. Cluster selections and starts.
7. Completion and residual stall families.
8. Tick counts.

Experimental Hypothesis
-----------------------
If Experiment 11 failed only because its confirmed regions matured at different
times, weak cross-aisle queue-depth alignment should increase lifecycle overlap
without suppressing natural dependency formation.

A null result would indicate that local queue depth alone is insufficient and
that explicit region-overlap instrumentation may be required before designing
further datasets.

======================================================================
EXPERIMENT 12 FINDINGS - DUAL-WINDOW PERTURBATION OVERLAP ALIGNMENT
======================================================================

Execution Summary
-----------------
Experiment 12 completed 30 deterministic paired scenarios, producing 60
executions. Both modes retained the frozen Experiment 23 architecture, identical
scenario seeds, cabin configuration, occupancy and entry-headway ranges. Only
bounded pre-run queue perturbations changed.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Overlap-alignment average completion: 99.71%.
- Improved pairs: 0 of 30.
- Unchanged pairs: 30 of 30.
- Worse pairs: 0 of 30.
- Net passenger difference: 0.
- Complete cabins: 27 in both modes.
- Standard dependency regions: 37.
- Overlap-alignment dependency regions: 35.
- Standard confirmed regions: 22.
- Overlap-alignment confirmed regions: 20.
- Standard cluster selections: 25.
- Overlap-alignment cluster selections: 23.
- Standard cluster-started events: 31.
- Overlap-alignment cluster-started events: 28.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Dual-window alignment preserved overall boarding outcomes.

Every paired scenario seated the same number of passengers in both modes. The
perturbation therefore changed local dependency structure without changing the
overall completion family.

2. Scenario 3 again exposed hidden dependency structure.

The standard execution produced no dependency region. The overlap-alignment
dataset produced two regions, one confirmed region, one cluster selection and
one cluster-started event. This reproduces the Experiment 11 finding that small
deterministic changes can reveal architecture-visible dependencies.

3. The rear-boundary lock remained unchanged.

Scenario 4 retained the same 200/204 rear-boundary stall, dependency-chain length
of four and 1500 ticks without seating progress. The overlap alignment neither
resolved nor deepened the final stable lock.

4. Some naturally occurring evidence was suppressed.

Scenario 5 decreased from two standard regions and one confirmed region to one
unconfirmed region. Across the complete benchmark, regions, confirmations and
cluster activity all decreased slightly.

5. No lifecycle competition occurred.

The two local windows did not mature as simultaneously confirmed eligible
regions. Priority competitions and lower-priority deferrals remained zero.

Scientific Interpretation
-------------------------
Experiment 12 confirms that bounded temporal alignment is insufficient to turn
separate local dependency events into hierarchy competition. Minimal
perturbations can reveal hidden regions, but attempting to align their queue
depths may also suppress naturally occurring evidence.

The result suggests that the missing variable is not simply the distance between
two deep triggers in their entry queues. The two candidate structures must share
a reproducible causal motif while remaining physically independent.

Experiment 12 Conclusion
------------------------
Dual-Window Perturbation Overlap Alignment is retained as evidence that local
dependency structures are sensitive to small deterministic ordering changes.
However, it is rejected as a reliable method for producing simultaneous
confirmed-region competition.


======================================================================
DISCUSSION - FROM WINDOW ALIGNMENT TO EMPIRICAL MOTIF MIRRORING
======================================================================

Experiments 11 and 12 established that natural dependency regions should be
revealed rather than fully prescribed. Experiment 13 therefore avoids another
broad ordering rule and avoids inventing an abstract dependency graph.

Instead, it selects a small motif from ordinary passengers already present in
the standard deterministic manifest:

    shallow potential blocker
    second potential blocker
    deeper-seat trigger
    downstream aisle-pressure passenger

The same type of motif is selected independently for both aisles and placed at a
shared pre-run queue depth. Every other passenger retains the original seeded
relative order. The experiment therefore tests whether an empirically grounded
natural motif can be mirrored across two independent aisle domains.


======================================================================
EXPERIMENT 13 - EMPIRICAL NATURAL-DEPENDENCY MOTIF MIRRORING
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original algorithm depends upon local occupancy relationships rather than
global behavioural assumptions. Experiment 13 follows that principle by
selecting small local passenger motifs from the existing deterministic manifest.
The movement algorithm remains unchanged and must decide whether either motif
actually becomes a dependency region.

Planned Purpose
---------------
Determine whether mirroring the same naturally plausible dependency motif on
both aisles, at a comparable queue depth, produces simultaneous confirmed
regions without prescribing runtime state.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

2. EMPIRICAL NATURAL-DEPENDENCY MOTIF MIRRORING DATASET

   The standard seeded queues are retained except for one small motif per aisle.
   Each available motif contains:

   - a shallow potential blocker near the target row;
   - a second potential blocker;
   - a deeper-seat trigger;
   - an optional downstream passenger capable of contributing aisle pressure.

Independent Variable
--------------------

    MIRRORED PRE-RUN PLACEMENT OF TWO NATURAL PASSENGER MOTIFS

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin, occupancy, seed and entry-headway range;
- unchanged seat assignments and serving aisles;
- synchronous deterministic execution;
- unchanged movement, blocker and yield-space rules;
- no runtime holding or adaptive admission;
- no inserted dependency region;
- no artificial confirmation or lifecycle extension;
- no backward movement, overtaking or aisle switching;
- no passenger moving beyond the assigned row;
- no behavioural assumptions.

Motif-Mirroring Contract
------------------------

1. Both motifs are selected from passengers already present in the standard
   seeded manifest.
2. No passenger changes seat, row or serving aisle.
3. All non-motif passengers retain their relative seeded order.
4. Each motif contains at least three members before it is moved.
5. Motifs are inserted at one shared deterministic queue depth.
6. No runtime state is monitored to maintain alignment.
7. The frozen architecture alone detects and confirms any region.
8. A hierarchy success requires simultaneous confirmed eligible regions.

New Evidence
------------

- motif size on each aisle;
- natural and mirrored queue depth;
- left/right regions created and confirmed;
- maximum simultaneous active regions;
- priority competitions and deferrals;
- hierarchical selections and aisle wins;
- region overlap duration;
- cluster selections and starts;
- complete cabins and seated totals;
- residual stall families.

Experimental Hypothesis
-----------------------
If the rare hierarchy state depends upon two comparable natural causal motifs
maturing at similar times, empirical motif mirroring should create stronger
cross-aisle lifecycle overlap than general queue-window alignment.

A null result would indicate that even empirically grounded manifest motifs
cannot reliably exercise the hierarchy under the present first-principles model.

Interpretation Safeguards
-------------------------

- A motif is a pre-run passenger-order pattern, not a dependency region.
- The selected passengers may seat without forming congestion.
- Identical motif structure does not guarantee identical runtime timing.
- A single confirmed region is not hierarchy validation.
- More stalls are not automatically successful evidence.
- Zero competitions must be reported exactly.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Simultaneous confirmed left/right regions.
3. Hierarchical selections and deferrals.
4. Region overlap duration.
5. Regions created and confirmed.
6. Cluster selections and starts.
7. Completion and stall family.
8. Tick counts.

Diagram Plan
------------
A later diagram may show one four-passenger motif on each aisle at comparable
queue depth. It must state that the passengers are selected from the ordinary
manifest and that no runtime region is inserted.

======================================================================
EXPERIMENT 13 FINDINGS - EMPIRICAL NATURAL-DEPENDENCY MOTIF MIRRORING
======================================================================

Execution Summary
-----------------
Experiment 13 completed 30 deterministic paired scenarios, producing 60
executions. Both modes retained the frozen Experiment 23 architecture, identical
scenario seeds, cabin configuration, occupancy and entry-headway ranges. The
motif dataset moved only small passenger groups already present in the standard
manifest.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Motif-mirroring average completion: 99.71%.
- Improved pairs: 0 of 30.
- Unchanged pairs: 30 of 30.
- Worse pairs: 0 of 30.
- Net passenger difference: 0.
- Complete cabins: 27 in both modes.
- Standard dependency regions: 37.
- Motif-mirroring dependency regions: 35.
- Standard confirmed regions: 22.
- Motif-mirroring confirmed regions: 21.
- Standard cluster selections: 25.
- Motif-mirroring cluster selections: 25.
- Standard cluster-started events: 31.
- Motif-mirroring cluster-started events: 30.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Motif mirroring preserved all paired completion outcomes.

Every paired scenario seated the same number of passengers. The method therefore
changed local dependency evidence without acting as a broad optimisation or
degradation policy.

2. Scenario 4 produced two confirmed regions.

The standard rear-boundary lock contained one region and one confirmed region.
The motif dataset retained the same 200/204 final stall but produced two regions,
two confirmed regions, one cluster selection and one cluster-started event.

3. Multiple confirmations still did not overlap as eligible competitors.

Scenario 4 is the clearest evidence that the remaining limitation is no longer
region creation or confirmation count. The two confirmed regions matured at
different decision points, so priority competitions and deferrals remained zero.

4. Scenario 19 increased confirmed and selected activity.

The standard execution produced five regions, two confirmed regions and two
cluster selections. Motif mirroring retained five regions but increased
confirmations to three, cluster selections to four and cluster-started events to
five. This shows that natural motifs can enrich lifecycle evidence without
changing the completed outcome.

5. Several scenarios remained exactly reproducible.

Scenarios including 2, 6, 17, 29 and 30 retained the same dependency totals and
outcome families. The motif mechanism therefore did not destabilise the complete
benchmark.

6. The established stall families remained intact.

Scenario 4 retained the four-passenger rear-boundary lock. Scenario 17 retained
a two-passenger rear-boundary lock. Scenario 29 retained the large mixed residual
dependency. Motif mirroring exposed additional lifecycle evidence but did not
artificially remove these first-principles failures.

Scientific Interpretation
-------------------------
Experiment 13 demonstrates that empirically plausible natural motifs are more
effective than fully prescribed topologies at preserving and sometimes
increasing confirmed dependency evidence. However, equal queue depth is not
equal lifecycle timing. The farther target row requires additional aisle travel,
and each motif may also experience different local seat-event delays.

The remaining research question is therefore precise: can two natural motifs be
placed at different pre-run queue depths so that their estimated maturation
opportunities coincide, without any runtime monitoring or intervention?

Experiment 13 Conclusion
------------------------
Empirical Natural-Dependency Motif Mirroring is supported as a stable probe of
dependency-region formation. It produced multiple confirmed regions in a
difficult deterministic scenario but did not activate hierarchy competition.
The next experiment should compensate for target-row travel distance when
placing the two motifs.


======================================================================
DISCUSSION - CONFIRMATION COUNT VERSUS MATURATION COINCIDENCE
======================================================================

A total of two or more confirmed regions within one execution does not establish
hierarchical competition. The regions must be confirmed and eligible at the
same architecture decision point.

Experiment 14 therefore does not change confirmation thresholds, lifecycle
rules or runtime scheduling. It estimates each motif's pre-run maturation
opportunity using two fixed components:

    queue admission depth
    plus
    aisle travel distance to the target row

The farther motif is placed earlier in its queue and the nearer motif later.
This compensates for deterministic travel distance while leaving all runtime
occupancy interactions untouched.


======================================================================
EXPERIMENT 14 - NATURAL-MOTIF LIFECYCLE MATURATION SYNCHRONISATION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's algorithm advances passengers through explicit occupancy states one tile
at a time. Experiment 14 uses that same movement principle to estimate pre-run
arrival opportunity: a passenger assigned farther along the aisle requires more
deterministic movement steps before reaching the target row.

The estimate affects only initial queue placement. Amit's movement engine and
the frozen region architecture remain solely responsible for all runtime states.

Planned Purpose
---------------
Determine whether travel-distance-compensated placement of two natural passenger
motifs causes their dependency regions to mature during the same architecture
decision window.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

2. NATURAL-MOTIF LIFECYCLE MATURATION SYNCHRONISATION DATASET

   The standard seeded queues are retained except for one natural motif per
   aisle. Each motif contains up to four existing passengers:

   - shallow potential blocker;
   - second potential blocker;
   - deeper-seat trigger;
   - optional downstream aisle-pressure passenger.

Independent Variable
--------------------

    TRAVEL-DISTANCE-COMPENSATED PRE-RUN MOTIF QUEUE DEPTH

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin, occupancy, seed and entry-headway range;
- unchanged seats, rows and serving aisles;
- unchanged synchronous execution;
- unchanged movement, blocker and yield-space rules;
- unchanged confirmation and hierarchy thresholds;
- no runtime holding or adaptive admission;
- no inserted region or artificial lifecycle persistence;
- no backward movement, overtaking or aisle switching;
- no behavioural assumptions.

Maturation-Synchronisation Contract
-----------------------------------

1. Both motifs are selected from the standard seeded manifest.
2. All non-motif passengers retain their seeded relative order.
3. A shared estimated arrival target is calculated before execution.
4. Estimated arrival equals queue depth plus target-row travel distance.
5. The farther motif is admitted earlier and the nearer motif later.
6. Queue depths remain bounded within the central half of each aisle queue.
7. No runtime state is read to adjust either motif.
8. The architecture alone decides whether regions form, confirm or compete.
9. Success requires genuine simultaneous confirmed eligible regions.

New Evidence
------------

- natural motif depth and adjusted depth per aisle;
- estimated left/right arrival opportunity;
- maximum simultaneous active regions;
- simultaneous confirmed-region competitions;
- hierarchical selections and deferrals;
- left/right priority wins and ties;
- regions created, confirmed and dissolved;
- region lifetime and overlap;
- cluster selections and starts;
- completion and residual stall family.

Experimental Hypothesis
-----------------------
If Experiment 13 failed because equal queue depth ignored different aisle travel
distances, deterministic distance compensation should increase the probability
that both natural motifs mature within the same decision window.

A null result would indicate that maturation timing is governed primarily by
local occupancy interactions rather than queue depth plus travel distance.

Interpretation Safeguards
-------------------------

- The arrival estimate is approximate and fixed before execution.
- No passenger is held to preserve synchronisation.
- A motif may seat without producing a region.
- Two confirmed regions at separate times do not validate the hierarchy.
- More stalls are not automatically successful evidence.
- Zero competitions must be documented exactly.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Simultaneous confirmed left/right regions.
3. Hierarchical selections and lower-priority deferrals.
4. Maximum simultaneous active regions.
5. Region overlap duration.
6. Regions created and confirmed.
7. Cluster selections and starts.
8. Completion and stall family.
9. Tick counts.

Diagram Plan
------------
A later diagram may show the farther motif placed earlier and the nearer motif
placed later, with both projected toward one estimated maturation window. The
diagram must state that this is a pre-run estimate and not runtime control.

======================================================================
EXPERIMENT 14 FINDINGS - NATURAL-MOTIF LIFECYCLE MATURATION SYNCHRONISATION
======================================================================

Execution Summary
-----------------
Experiment 14 completed 30 deterministic paired scenarios, producing 60
executions. Both modes retained the frozen Experiment 23 architecture, identical
scenario seeds, cabin configuration, occupancy and entry-headway ranges. The
experimental mode changed only the bounded pre-run queue depth of two natural
passenger motifs.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Synchronised average completion: 99.71%.
- Improved pairs: 0 of 30.
- Unchanged pairs: 30 of 30.
- Worse pairs: 0 of 30.
- Net passenger difference: 0.
- Complete cabins: 27 in both modes.
- Standard dependency regions: 37.
- Synchronised dependency regions: 35.
- Standard confirmed regions: 22.
- Synchronised confirmed regions: 21.
- Standard cluster selections: 25.
- Synchronised cluster selections: 25.
- Standard cluster-started events: 31.
- Synchronised cluster-started events: 30.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Travel-distance compensation preserved all paired outcomes.

Every paired scenario seated the same number of passengers and retained the same
completion or stall family. The experiment therefore altered lifecycle evidence
without destabilising the benchmark.

2. Scenario 4 again produced two confirmed regions.

The synchronised mode retained the 200/204 rear-boundary lock but produced two
regions, two confirmations, one cluster selection and one cluster-started event,
compared with one confirmed region in the standard execution.

3. Multiple confirmations remained temporally separate.

Despite two confirmations in Scenario 4, priority competitions and lower-
priority deferrals remained zero. The regions were not simultaneously confirmed
and eligible at one hierarchy decision point.

4. Scenario 5 remained stable.

Both modes produced two regions, one confirmed region, one selection and one
cluster-started event. The synchronised mode increased lifecycle updates slightly
without changing the completed outcome.

5. Queue depth plus travel distance is an incomplete maturation model.

The absence of hierarchy competition indicates that local seat events, aisle
occupancy, blocker release and middle-bank interactions dominate the actual
maturation timing after entry.

Scientific Interpretation
-------------------------
Experiment 14 rules out a straightforward deterministic explanation in which
different target-row travel distances alone prevent lifecycle coincidence.
Pre-run synchronisation can preserve and enrich dependency evidence, but it
cannot control the many local interactions that determine when a region confirms
and how long it remains eligible.

The next experiment should therefore stop attempting to equalise two motifs.
Instead, it should construct two deliberately different natural environments so
that one region develops slowly and persistently while the other develops more
quickly. Such lifecycle diversity may create an overlap window without runtime
holding.

Experiment 14 Conclusion
------------------------
Natural-Motif Lifecycle Maturation Synchronisation is retained as a stable
negative result. It preserved multiple confirmed-region evidence but did not
activate hierarchy competition. The next investigation should vary local
dependency growth characteristics rather than queue-entry timing.


======================================================================
DISCUSSION - FROM SYNCHRONISATION TO LIFECYCLE DIVERSITY
======================================================================

Experiments 11-14 progressively investigated discovery, queue-window alignment,
natural motif mirroring and travel-distance compensation. The findings show that
two regions do not need identical starting conditions. They need overlapping
eligible lifetimes.

Experiment 15 therefore introduces deterministic asymmetry:

    one heavier, blocker-rich and reinforced motif
    one lighter, lower-pressure motif

Both motifs remain natural passenger groups selected from the seeded manifest.
The heavier environment is expected to develop more slowly and persist longer;
the lighter environment may mature earlier and dissolve sooner. Their different
rates may create an overlap that equalised motifs failed to produce.


======================================================================
EXPERIMENT 15 - DETERMINISTIC DEPENDENCY LIFECYCLE DIVERSITY
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original algorithm evaluates local occupancy and dependency conditions
rather than imposing global behaviour. Experiment 15 retains this principle by
constructing two different local input environments while leaving the movement
engine unchanged.

The left motif is blocker-rich and reinforced. The right motif is deliberately
lighter. Any difference in lifecycle growth must arise through ordinary
deterministic occupancy transitions.

Planned Purpose
---------------
Determine whether two natural dependency motifs with deliberately different
local growth characteristics create overlapping confirmed-region lifetimes and
activate the frozen hierarchy.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

2. DETERMINISTIC DEPENDENCY LIFECYCLE DIVERSITY DATASET

   The standard seeded queues are retained except for two natural motifs:

   - Heavy motif: shallow blocker, second blocker, deep trigger, downstream
     pressure passenger and adjacent reinforcement.
   - Light motif: shallow blocker, deep trigger and limited downstream pressure.

Independent Variable
--------------------

    DETERMINISTIC DIFFERENCE IN LOCAL DEPENDENCY-GROWTH ENVIRONMENT

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin, occupancy, seed and entry-headway range;
- unchanged seats, rows and serving aisles;
- synchronous deterministic execution;
- unchanged movement, blocker and yield-space rules;
- unchanged confirmation and hierarchy thresholds;
- no runtime holding or adaptive admission;
- no inserted region or artificial lifecycle persistence;
- no backward movement, overtaking or aisle switching;
- no behavioural assumptions.

Lifecycle-Diversity Contract
----------------------------

1. Both motifs are selected from passengers already present in the standard
   seeded manifest.
2. The heavy and light motifs are inserted at one shared deterministic depth.
3. All non-motif passengers retain their seeded relative order.
4. The heavy motif contains more blocker and reinforcement components.
5. The light motif contains fewer local pressure components.
6. No runtime state is read or used to preserve either region.
7. The architecture alone determines whether the motifs form regions.
8. Success requires simultaneous confirmed eligible regions.

New Evidence
------------

- heavy and light motif sizes;
- regions created and confirmed by aisle;
- maximum simultaneous active regions;
- priority competitions and deferrals;
- hierarchical selections and aisle wins;
- region lifetimes and overlap duration;
- cluster selections and starts;
- completion and residual stall family;
- tick counts.

Experimental Hypothesis
-----------------------
If identical or synchronised motifs fail because their lifecycle windows rise and
fall together or miss one another narrowly, deterministic lifecycle diversity
may allow a persistent heavy region to overlap a faster light region.

A null result would indicate that queue-manifest construction alone cannot
reliably produce the hierarchy state under the current first-principles model.

Interpretation Safeguards
-------------------------

- Heavy and light describe input composition, not guaranteed runtime behaviour.
- No region is inserted, delayed or protected.
- More congestion is not automatically a successful result.
- A single confirmed region is not hierarchy validation.
- Completion remains secondary to genuine competition evidence.
- Zero competitions must be reported exactly.

Primary Evaluation Order
------------------------

1. Genuine priority competitions.
2. Simultaneous confirmed left/right regions.
3. Hierarchical selections and lower-priority deferrals.
4. Maximum simultaneous active regions.
5. Region overlap duration.
6. Regions created and confirmed.
7. Cluster selections and starts.
8. Completion and stall family.
9. Tick counts.

Diagram Plan
------------
A later diagram may contrast a heavy five-passenger motif with a lighter three-
passenger motif at the same queue depth. The figure must state that these are
pre-run natural passenger groups and not runtime dependency objects.

======================================================================
EXPERIMENT 15 FINDINGS - DETERMINISTIC DEPENDENCY LIFECYCLE DIVERSITY
======================================================================

Execution Summary
-----------------
Experiment 15 completed 30 deterministic paired scenarios, producing 60
executions. Both modes retained the frozen Experiment 23 architecture, identical
scenario seeds, cabin configuration, occupancy and entry-headway ranges. The
experimental mode changed only the composition and placement of one heavy and
one light natural motif.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Lifecycle-diversity average completion: 99.71%.
- Improved pairs: 0 of 30.
- Unchanged pairs: 30 of 30.
- Worse pairs: 0 of 30.
- Net passenger difference: 0.
- Complete cabins: 27 in both modes.
- Standard dependency regions: 37.
- Lifecycle-diversity dependency regions: 36.
- Standard confirmed regions: 22.
- Lifecycle-diversity confirmed regions: 21.
- Standard cluster selections: 25.
- Lifecycle-diversity cluster selections: 25.
- Standard cluster-started events: 31.
- Lifecycle-diversity cluster-started events: 31.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. Lifecycle diversity preserved every paired completion outcome.

All paired scenarios seated identical passenger totals and retained the same
completion or residual-stall families. The heavy/light construction therefore
did not destabilise the frozen movement engine.

2. Scenario 3 revealed a new confirmed dependency region.

The standard execution produced no dependency region. The diversity dataset
produced two regions, one confirmed region, one cluster selection and one
cluster-started event while still completing all 342 passengers.

3. Scenario 4 reverted to one persistent confirmed region.

Unlike Experiments 13 and 14, the diversity dataset did not produce a second
confirmed region in the established rear-boundary-lock scenario. Both modes
retained one region, one confirmation and the same 200/204 final outcome.

4. Aggregate dependency evidence remained effectively unchanged.

Regions decreased only from 37 to 36, confirmations from 22 to 21, while cluster
selections and starts were preserved. Heavy/light motif asymmetry therefore
redistributed local evidence rather than creating lifecycle overlap.

5. No hierarchy competition occurred.

Priority competitions and lower-priority deferrals remained zero. Different
local motif composition did not produce two simultaneously confirmed eligible
regions.

Scientific Interpretation
-------------------------
Experiment 15 demonstrates that lifecycle diversity can expose hidden local
dependency evidence, as shown by Scenario 3, but does not reliably create an
overlap window. Changing motif composition remains a passenger-order technique.
It does not provide a distinct temporal admission layer above the movement
engine.

The evidence therefore supports a transition from passenger-level manifest
manipulation to a deterministic admission-window architecture. This creates a
new input layer while preserving the policy-neutral movement and dependency
systems beneath it.

Experiment 15 Conclusion
------------------------
Deterministic Dependency Lifecycle Diversity is retained as a stable negative
result. The experiment preserved outcomes and revealed one additional local
dependency case, but it did not activate hierarchical arbitration. Further motif
refinement is unlikely to answer the remaining question.


======================================================================
RESEARCH INTERPRETATION - WHY BOARDING POLICY WAS POSTPONED
======================================================================

Real-World Operational Order
----------------------------
In real airline operations, the boarding policy is applied before passengers
enter the aircraft. The airline may assign sections, groups, priorities or other
admission rules, and the resulting passenger stream is then processed by the
cabin.

Scientific Modelling Order
--------------------------
This research deliberately used the opposite order. It first established a
policy-neutral deterministic movement backbone and then studied:

- aisle occupancy;
- seat blockers;
- dependency formation;
- persistent region lifecycles;
- confirmation;
- hierarchy;
- cluster resolution.

Introducing section boarding at the beginning would have made it difficult to
separate intrinsic movement effects from policy-created effects. A rear-first or
zone-based stream could have suppressed, concentrated or relocated dependencies
before the underlying architecture was understood.

Consensus from the Evidence
---------------------------
The evidence supports two valid orders for two different purposes:

For scientific architecture research:

    deterministic movement foundation
        -> dependency analysis
        -> lifecycle and hierarchy
        -> boarding-policy evaluation

For an operational airline simulator:

    airline boarding policy
        -> deterministic admission queue
        -> movement engine
        -> dependency analysis and resolution

These orders are not contradictory. Boarding policy selects the inputs; the
validated deterministic engine processes them.

What the Current Simulator Models
---------------------------------
The simulator provides a first-principles representation of:

- deterministic passenger admission;
- forward, row-bounded aisle movement;
- local occupancy;
- seat-access blockers;
- temporary aisle reoccupation;
- middle-bank coordination;
- dependency-region formation and resolution.

It does not claim to model every real-world behavioural or operational factor.
Human hesitation, conversations, variable baggage handling, instruction
non-compliance, family behaviour and airline commercial priorities remain
outside this architecture.

Future Policy Layer
-------------------
Section boarding, rear-to-front boarding, front-to-back boarding, WilMA,
reverse-pyramid methods and commercial boarding groups should later be treated
as interchangeable deterministic admission strategies above the frozen engine.

This separation allows future policy studies to compare not only total boarding
time but also dependency-region count, confirmation, lifetime, cluster activity,
hierarchy use and residual stall family.


======================================================================
DISCUSSION - THE BRIDGE FROM FOUNDATION TO POLICY
======================================================================

The completed work does not lack a boarding policy. It establishes the layer
that boarding policies require.

Experiment 16 creates the architectural bridge:

    deterministic admission windows
        -> passenger movement
        -> dependency formation
        -> confirmation
        -> hierarchy
        -> cluster resolution

The windows are not yet rear, middle or front cabin sections. They preserve the
ordinary seeded passenger order and introduce only deterministic release
boundaries. Future work can replace the neutral windows with operational
boarding groups without modifying the movement engine.


======================================================================
EXPERIMENT 16 - DETERMINISTIC ADMISSION-WINDOW ARCHITECTURE
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original people-movement algorithm processes explicit occupancy inputs
through deterministic local rules. Experiment 16 adds a separate deterministic
admission layer above that backbone.

The admission layer decides when a passenger becomes eligible to enter. Amit's
movement engine still decides whether the entry tile is free and how the
passenger advances thereafter.

Planned Purpose
---------------
Determine whether neutral deterministic admission windows can produce temporal
separation between passenger cohorts while preserving the policy-free movement
architecture and all controlled variables.

This experiment also establishes the reusable interface through which later
airline boarding policies can be introduced.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

   Passengers use the established seeded aisle queues and ordinary controlled
   entry headway.

2. DETERMINISTIC ADMISSION-WINDOW DATASET

   The same seeded aisle queues are divided into three consecutive cohorts.
   Passengers retain their original relative order. Cohorts two and three receive
   fixed pre-run release ticks.

Independent Variable
--------------------

    DETERMINISTIC COHORT RELEASE WINDOW

Controlled Conditions
---------------------

- frozen Experiment 23 architecture;
- identical cabin, occupancy, seed and passenger assignments;
- identical seeded relative queue order;
- identical numerical entry-headway ranges;
- synchronous deterministic execution;
- unchanged movement, blocker and yield-space rules;
- unchanged clustering, lifecycle confirmation and hierarchy;
- no row-based or seat-based airline policy;
- no runtime congestion response;
- no adaptive release;
- no backward movement, overtaking or aisle switching;
- no behavioural assumptions.

Admission-Window Contract
-------------------------

1. Each aisle queue is divided into three consecutive cohorts.
2. Passenger relative order is unchanged.
3. Window membership depends only on seeded queue position.
4. Release ticks are calculated before execution.
5. Release ticks use cohort size, controlled headway and a fixed deterministic
   pause.
6. A released passenger must still wait for an empty entry tile.
7. No passenger is held after entering the aircraft.
8. Windows do not correspond to front, middle or rear cabin sections.
9. No runtime dependency state can alter a release tick.
10. The frozen movement architecture remains unchanged beneath the new layer.

New Evidence
------------

- cohort release ticks;
- passengers admitted from each window;
- ticks waiting for window release;
- dependency regions created and confirmed;
- maximum simultaneous active regions;
- priority competitions and deferrals;
- cluster selections and starts;
- complete cabins and seated totals;
- residual stall families;
- total and average waiting ticks.

Experimental Hypothesis
-----------------------
Neutral deterministic admission windows may create lifecycle separation that
continuous admission and local motif manipulation could not produce. They may
also reveal whether temporal cohort boundaries suppress or preserve dependency
formation.

The primary architectural objective is not immediate optimisation. It is to
validate a clean admission interface above the frozen movement engine.

Interpretation Safeguards
-------------------------

- Admission windows are architecture, not an airline recommendation.
- Cohorts are based on queue position, not cabin section.
- Better boarding time is secondary to architectural evidence.
- Waiting outside due to a release gate must remain segregated from congestion.
- No policy conclusion may be inferred from this experiment alone.
- Zero hierarchy competitions must be reported exactly.

Primary Evaluation Order
------------------------

1. Correct separation of admission-window and congestion evidence.
2. Genuine priority competitions.
3. Simultaneous confirmed regions.
4. Hierarchical selections and deferrals.
5. Regions created and confirmed.
6. Cluster selections and starts.
7. Completion and residual stall family.
8. Waiting time and tick count.

Future Policy Compatibility
---------------------------
After validation, the admission-window layer can support later deterministic
policies by changing only cohort membership and release order, including:

- rear-to-front sections;
- front-to-back sections;
- window-middle-aisle ordering;
- reverse-pyramid ordering;
- airline-specific boarding groups.

Those future policies remain separate experiments and require operational
interpretation beyond the present architecture.

======================================================================
EXPERIMENT 16 FINDINGS - DETERMINISTIC ADMISSION-WINDOW ARCHITECTURE
======================================================================

Execution Summary
-----------------
Experiment 16 completed 30 deterministic paired scenarios, producing 60
executions. Both modes retained the frozen Experiment 23 movement and dependency
architecture, identical scenario seeds, cabin configuration, occupancy,
passenger assignments, seeded relative queue order and numerical entry-headway
ranges. The experimental mode added three fixed queue-position release windows.

Overall Paired Result
---------------------

- Standard average completion: 99.71%.
- Admission-window average completion: 99.71%.
- Improved pairs: 0 of 30.
- Unchanged pairs: 30 of 30.
- Worse pairs: 0 of 30.
- Net passenger difference: 0.
- Complete cabins: 27 in both modes.
- Standard dependency regions: 37.
- Admission-window dependency regions: 37.
- Standard confirmed regions: 22.
- Admission-window confirmed regions: 22.
- Standard cluster selections: 25.
- Admission-window cluster selections: 25.
- Standard cluster-started events: 31.
- Admission-window cluster-started events: 31.
- Priority competitions: 0 in both modes.

Principal Findings
------------------

1. The admission-window interface was implemented without changing the engine.

The experimental dataset successfully inserted deterministic release gates above
the ordinary entry-tile and movement logic. Passengers still entered only when
the entry tile was free, and every in-cabin rule remained frozen.

2. Queue-position windows produced complete behavioural equivalence.

Across all 30 pairs, completion, dependency-region totals, confirmations,
cluster activity and residual stall families were unchanged. Many scenarios
also retained identical tick counts.

3. Scenario 4 reproduced the exact rear-boundary lock.

Both modes stalled at 200/204 with the same four-passenger chain, critical
blocker, insufficient rear yield space and persistent confirmed region.

4. Temporal separation alone did not alter local dependency topology.

The windows delayed later portions of the same seeded queue but did not change
which destination rows and seat-access demands were grouped together. The
movement engine therefore encountered essentially the same critical local
interactions.

5. No hierarchy competition occurred.

Priority competitions and lower-priority deferrals remained zero. Neutral timing
windows did not produce simultaneous confirmed eligible regions.

Scientific Interpretation
-------------------------
Experiment 16 validates the admission layer as a clean architectural bridge, but
rejects queue-position timing alone as a meaningful dependency variable in the
tested form.

The evidence suggests that the spatial composition of each admitted cohort is
more important than a release delay applied to an otherwise unchanged passenger
sequence. Airlines commonly influence this composition through sections, zones
or seat categories. The next experiment should therefore structure cohorts by
aircraft geography while preserving deterministic execution and the frozen
movement engine.

Experiment 16 Conclusion
------------------------
The Deterministic Admission-Window Architecture is supported as a reusable
interface above the first-principles movement engine. Its neutral queue-position
windows produced no material behavioural change, establishing a clean baseline
for geographically structured admission.


======================================================================
RESEARCH INTERPRETATION - TIMING VERSUS SPATIAL COMPOSITION
======================================================================

Experiment 15 altered local passenger motifs without producing hierarchy
competition. Experiment 16 altered admission timing without changing the
passengers grouped together, and produced exact behavioural equivalence.

Together, these results distinguish two variables:

    when passengers become eligible to enter
    which destination regions coexist in an admitted cohort

The evidence indicates that the second variable is now the stronger candidate.
A timing gate cannot substantially change dependency topology when the same
spatial mix eventually reaches the same critical rows in the same relative
order.

This does not invalidate the admission-window layer. It clarifies its role.
The layer is the interface through which future cohort definitions can be
changed while the deterministic movement and dependency engines remain fixed.


======================================================================
DISCUSSION - THE FIRST POLICY-NEUTRAL GEOGRAPHIC BRIDGE
======================================================================

Experiment 17 is not presented as a recommendation that airlines should board
rear-to-front. It is a controlled topology experiment.

Its purpose is to determine whether grouping passengers by destination region
changes dependency evidence where neutral timing windows did not. The selected
rear-middle-front order is a deterministic stress dataset and a bridge toward
later policy comparisons.

If the geographic dataset changes outcomes, the evidence will show that boarding
policy can influence dependency formation through spatial composition. If it
does not, the architecture will have ruled out another major admission-level
explanation.


======================================================================
EXPERIMENT 17 - DETERMINISTIC GEOGRAPHIC ADMISSION COHORTS
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original movement algorithm remains the lower-level deterministic engine.
Experiment 17 changes only the order in which destination-row groups are made
eligible for entry.

After entry, every passenger remains row-bounded and follows the same occupancy,
blocker, seat-event and dependency rules.

Planned Purpose
---------------
Determine whether deterministic cohorts based on destination geography alter
dependency-region formation, lifecycle confirmation, residual stalls or
hierarchy utilisation compared with the standard seeded queue.

Paired Modes
------------

1. STANDARD DETERMINISTIC DATASET

2. DETERMINISTIC GEOGRAPHIC COHORT DATASET

   Each aisle's seeded passenger list is divided into:

   - rear third;
   - middle third;
   - front third.

   Cohorts are admitted rear, then middle, then front. Seeded relative order is
   preserved inside each cohort.

Independent Variable
--------------------

    DESTINATION-ROW GEOGRAPHIC COHORT MEMBERSHIP AND RELEASE ORDER

Controlled Conditions
---------------------

- frozen Experiment 23 movement and dependency architecture;
- identical cabin, occupancy, seed and passenger assignments;
- identical serving-aisle assignments;
- seeded relative order preserved inside every cohort;
- identical numerical entry-headway ranges;
- synchronous deterministic execution;
- unchanged movement, blocker and yield-space rules;
- unchanged clustering, lifecycle confirmation and hierarchy;
- no runtime congestion response;
- no adaptive release;
- no backward movement, overtaking or aisle switching;
- no behavioural assumptions.

Geographic-Cohort Contract
--------------------------

1. Row thirds are calculated deterministically from cabin length.
2. Rear passengers enter before middle passengers.
3. Middle passengers enter before front passengers.
4. Relative seeded order is unchanged inside each cohort.
5. Fixed release ticks are calculated before execution.
6. A released passenger still requires an empty entry tile.
7. No passenger is held after entering the aircraft.
8. No runtime dependency state changes cohort release.
9. The dataset is a research stress condition, not an airline recommendation.
10. The frozen architecture alone determines all dependency evidence.

New Evidence
------------

- passenger count in each geographic cohort;
- cohort release ticks;
- outside waiting attributable to release gates;
- dependency regions created and confirmed;
- maximum simultaneous active regions;
- priority competitions and deferrals;
- cluster selections and starts;
- completion and residual stall family;
- total and average waiting ticks.

Experimental Hypothesis
-----------------------
If spatial composition is the dominant admission-level variable, rear-middle-
front cohorts should produce measurably different dependency topology from the
standard seeded queue even though movement and entry-headway rules remain
unchanged.

A null result would show that broad row geography alone is also insufficient and
that later policy research must investigate seat category, narrower zones or
combined spatial rules.

Interpretation Safeguards
-------------------------

- This is not yet a commercial boarding-policy recommendation.
- Faster completion is not sufficient evidence of a better policy.
- Outside release-gate waiting must remain separate from in-cabin congestion.
- Geographic ordering may suppress as well as create dependency regions.
- A single confirmed region is not hierarchy validation.
- Zero competitions must be reported exactly.

Primary Evaluation Order
------------------------

1. Correct geographic cohort and release-gate operation.
2. Change in dependency-region topology.
3. Genuine priority competitions.
4. Simultaneous confirmed regions.
5. Hierarchical selections and deferrals.
6. Cluster selections and starts.
7. Completion and residual stall family.
8. Waiting time and tick count.

Future Policy Compatibility
---------------------------
The same admission interface can later test:

- front-to-back sections;
- smaller rear-to-front zones;
- window-middle-aisle groups;
- reverse-pyramid cohorts;
- airline-specific group definitions.

Those later studies should compare operational performance and dependency
evidence separately.


======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 16
======================================================================

1. The frozen movement and dependency architecture remains unchanged.
2. Experiment 16 validated a separate deterministic admission interface.
3. All 30 paired outcomes and architecture metrics were unchanged.
4. Queue-position timing alone did not change dependency topology.
5. Scenario 4 reproduced the identical rear-boundary lock.
6. Priority competitions remained zero.
7. Spatial cohort composition is now the stronger candidate variable.
8. Experiment 17 uses rear-middle-front destination-row cohorts.
9. The geographic dataset is a stress condition, not a policy recommendation.
10. No passenger may move backwards or beyond the assigned row.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v17 - EXPERIMENT 17 DESIGN
======================================================================

======================================================================
EXPERIMENT 17 - OFFICIAL FINDINGS
======================================================================

Execution Status
----------------
The full deterministic verification run completed all 30 paired scenarios
(60 executions). The standard and geographic modes used identical cabins,
occupancy, seeds, passenger assignments, serving aisles, numerical headways,
movement rules, dependency rules and hierarchy controls.

Observed Results
----------------
- Standard passengers seated: 7,649 of 7,671 (99.71%).
- Geographic-cohort passengers seated: 6,961 of 7,671 (90.74%).
- Net passenger difference: -688.
- Successful completions: 46 of 60 executions.
- Geographic mode produced lower completion in 11 of 30 pairs.
- The strongest geographic completion losses included 98.18%, 99.07%,
  57.02%, 79.69%, 47.66%, 60.96%, 64.04% and 60.95% completion cases.
- The longest observed geographic dependency chain contained 28 passengers
  (27 waiting passengers behind the terminal passenger).
- Maximum outside-queue saturation reached 129 waiting passengers; the
  highlighted Experiment 17 case reached 112.
- New residual families included REAR_BOUNDARY_LOCK and
  ENTRY_SATURATION_WITH_INTERNAL_CHAIN.
- Priority competitions and lower-priority deferrals remained zero.

Principal Findings
------------------
1. Broad geographic grouping changed behaviour materially where neutral timing
   windows in Experiment 16 had not.
2. Rear-first thirds concentrated similarly destined passengers and created
   long internal dependency chains before later cohorts could enter.
3. Entry saturation was not merely external delay. In the strongest cases it
   coexisted with a stable internal chain, so the entry tile remained blocked
   while substantial portions of the queue were still outside.
4. The positive scientific result is therefore not that rear-to-front thirds
   are operationally superior. It is that spatial admission composition is a
   causal variable in dependency formation.
5. The same frozen movement engine produced the new behaviour; the independent
   variable was admission geography alone.

Discussion Incorporated Before Experiment 18
---------------------------------------------
Experiment 17 establishes the bridge from asking whether geography matters to
asking how much geographic granularity is appropriate. Broad thirds can be too
coarse: they create large homogeneous waves that may saturate an aisle and form
extended dependency chains. A finer partition may limit the size of each wave
while retaining the spatial separation that Experiment 16 lacked.

Normal entry-headway rules remain applicable inside every cohort. Passengers do
not enter simultaneously. Each released passenger still waits for the ordinary
deterministic headway and an empty entry tile. The cohort mechanism changes
eligibility and spatial composition only.

Experiment 17 Conclusion
------------------------
Experiment 17 is the first admission experiment in this series to produce a
major behavioural change. It supports spatial composition as a dominant
admission-level variable and justifies a controlled granularity study.


======================================================================
EXPERIMENT 18 - FINE-GRAINED DETERMINISTIC GEOGRAPHIC ADMISSION ZONES
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original deterministic movement engine remains unchanged. Experiment 18
modifies only the spatial admission granularity above that engine. Once a
passenger enters, all row-bounded movement, blocker, yield-space, seat-event,
dependency-region, lifecycle and hierarchy rules are identical.

Planned Purpose
---------------
Determine whether dividing the cabin into six smaller deterministic geographic
zones can reduce the extreme admission saturation observed with Experiment 17's
three broad cohorts while preserving useful dependency diversity.

Paired Modes
------------
1. STANDARD DETERMINISTIC DATASET.
2. FINE-GRAINED GEOGRAPHIC ZONE DATASET.

Fine-Grained Zone Contract
--------------------------
- Every cabin is divided longitudinally into six deterministic zones.
- Zones enter from rear to front.
- Seeded relative order is preserved inside each zone.
- Normal deterministic entry-headway rules still apply within every zone.
- Fixed release ticks are calculated before execution.
- A released passenger still requires an empty entry tile.
- No runtime congestion state changes the zone order or release schedule.
- No passenger is held or redirected after entry.

Independent Variable
--------------------
    GEOGRAPHIC ADMISSION GRANULARITY: SIX ZONES INSTEAD OF THREE COHORTS

Primary Evaluation Order
------------------------
1. Correct six-zone mapping and deterministic release.
2. Outside-queue saturation compared with Experiment 17.
3. Completion loss and converted-success cases.
4. Dependency-chain length and residual stall family.
5. Dependency-region creation and confirmation diversity.
6. Genuine priority competitions and deferrals.
7. Cluster selections and starts.
8. Total waiting and tick count.

Experimental Hypothesis
-----------------------
Finer deterministic geographic grouping may reduce the size of each admitted
wave and therefore reduce extreme entry saturation. It may nevertheless retain
more spatial structure than Experiment 16's timing-only windows, allowing useful
dependency differences to remain visible.

Interpretation Safeguards
-------------------------
- Finer zones are not assumed to be better.
- Reduced outside waiting does not by itself prove reduced in-cabin congestion.
- A completion improvement must be checked for displaced dependency costs.
- The six-zone order is a controlled stress dataset, not an airline policy
  recommendation.
- Zero hierarchy competitions must be reported exactly if observed.

======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 17
======================================================================
1. Timing-only windows produced behavioural equivalence in Experiment 16.
2. Broad geographic thirds produced a major behavioural change in Experiment 17.
3. Spatial admission composition is therefore a validated causal variable.
4. Broad cohorts can create rear-boundary locks and entry saturation with long
   internal dependency chains.
5. Normal entry headway remains active inside every cohort and zone.
6. Experiment 18 tests six smaller rear-to-front zones.
7. The movement and dependency architecture remains frozen.
8. The next question is granularity, not whether geography matters.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v18 - EXPERIMENT 18 DESIGN
======================================================================


======================================================================
EXPERIMENT 18 - OFFICIAL FINDINGS
======================================================================

Execution Status
----------------
The full deterministic run completed all 30 paired scenarios (60 executions).
Both modes used identical cabins, occupancy, scenario seeds, passenger manifests,
serving aisles, numerical entry-headway ranges, synchronous movement, seat-event
rules, dependency-region lifecycle and hierarchy controls. Only the pre-run
admission ordering and six-zone release schedule differed.

Observed Results
----------------
- Standard passengers seated: 7,492 of 7,789 (96.19%).
- Fine-zone passengers seated: 6,209 of 7,789 (79.72%).
- Net fine-zone passenger difference: -1,283.
- Successful completions: standard 19 of 30; fine-zone 12 of 30.
- Total successful executions: 31 of 60.
- Fine-zone completion was lower in 16 of 30 pairs.
- Fine-zone mode converted three incomplete standard cases to success, showing
  that the effect was not uniformly negative.
- The largest single paired loss was 153 seated passengers.
- The largest observed increase in the outside queue was 117 passengers.
- The longest observed unresolved dependency chain contained 35 passengers.
- Fine-zone mode created 22 dependency regions, of which 20 reached confirmation.
- Fine-zone hierarchy activity was substantial: 3,710 priority competitions and
  3,446 lower-priority deferrals were recorded.
- Fine-zone cluster intervention remained rare: one selection and two starts.
- Dominant residual families included REAR_BOUNDARY_LOCK and
  ENTRY_SATURATION_WITH_INTERNAL_CHAIN.

Principal Findings
------------------
1. Increasing geographic granularity was not monotonically beneficial.
2. Six uninterrupted rear-to-front zones often concentrated passengers into
   narrow destination bands and generated severe local aisle saturation.
3. The strongest cases combined a blocked entry tile, a long internal dependency
   chain and a large outside queue. External delay and internal congestion were
   therefore parts of the same causal structure rather than separate effects.
4. Experiment 18 did not invalidate Experiment 17. Together they show that
   geography matters, but that excessive spatial localisation can become
   counterproductive.
5. The experiment identified a non-linear operating region: too little spatial
   structure produced little change in Experiment 16, broad structure produced
   major change in Experiment 17, and finer uninterrupted structure produced
   severe saturation in Experiment 18.
6. Unlike the earlier admission experiments, Experiment 18 exercised the frozen
   hierarchy at scale. The large number of genuine competitions and deferrals is
   important architecture-validation evidence even though operational completion
   was frequently worse.
7. The scarcity of cluster starts despite extensive hierarchy activity shows
   that prioritisation can rank competing regions without guaranteeing that a
   currently executable release exists.

Discussion Incorporated Before Experiment 19
---------------------------------------------
The next experiment should not add still more zones. Experiment 18 has already
shown that smaller geographic groups, when released as uninterrupted local waves,
can intensify rather than relieve congestion.

The stronger next question is whether the spatial signal can be retained while
limiting the instantaneous size of each local wave. This requires a controlled
change to release pacing, not a change to the movement engine or an adaptive
runtime policy.

Normal entry-headway rules remain active for every passenger. A micro-batch gate
therefore adds an eligibility boundary above the existing entry rule; it does not
replace numerical headway or allow simultaneous insertion.

Experiment 18 Conclusion
------------------------
Experiment 18 establishes a turning point in the admission programme. Geographic
structure is causal, but finer subdivision alone is not a solution. Excessive
local concentration can create very long dependency chains, substantial outside
queues and repeated hierarchy competitions. The next experiment must preserve
geographic organisation while deterministically bounding each release wave.


======================================================================
EXPERIMENT 19 - PACED GEOGRAPHIC MICRO-BATCH ADMISSION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original deterministic movement backbone remains unchanged. Experiment
19 introduces only a pre-execution admission schedule above that backbone. Once
a passenger enters, the same one-tile synchronous movement, row limit, blocker
yield, seat event, reservation, dependency-region lifecycle and hierarchy rules
continue without modification.

Planned Purpose
---------------
Determine whether fixed deterministic micro-batch pacing can preserve the useful
spatial dependency diversity of geographic admission while reducing the extreme
entry saturation produced by Experiment 18's uninterrupted six-zone waves.

Paired Modes
------------
1. STANDARD DETERMINISTIC DATASET.
2. PACED GEOGRAPHIC MICRO-BATCH DATASET.

Paced Geographic Contract
-------------------------
- The cabin remains divided into six longitudinal destination-row zones.
- Zone order remains rear to front.
- Seeded relative order is preserved inside every zone.
- Each zone is divided before execution into fixed deterministic micro-batches.
- Every micro-batch receives a pre-calculated earliest release tick.
- A fixed pause separates consecutive micro-batches.
- A fixed zone-transition pause separates adjacent geographic zones.
- Normal deterministic numerical entry headway remains active.
- The entry tile must still be empty before insertion.
- The schedule does not inspect runtime congestion, regions or seat events.
- No passenger is held, redirected or reordered after entering the aircraft.

Independent Variable
--------------------
    FIXED MICRO-BATCH PACING WITHIN SIX GEOGRAPHIC ZONES

Primary Evaluation Order
------------------------
1. Correct zone, micro-batch and pre-run release construction.
2. Outside-queue saturation compared with Experiment 18.
3. Completion loss and converted-success cases.
4. Longest dependency-chain length.
5. Entry-saturation and rear-boundary residual families.
6. Confirmed-region concurrency and hierarchy competitions.
7. Lower-priority deferrals, cluster selections and starts.
8. Total waiting and completion ticks.

Experimental Hypothesis
-----------------------
If Experiment 18's main failure mechanism was the uninterrupted size of each
local release wave, fixed micro-batch pauses should reduce entry saturation and
shorten internal dependency chains while retaining more geographic structure
than the timing-only windows of Experiment 16.

A negative result would show that simple time pacing is insufficient once the
queue remains strongly ordered by destination geography. That would justify a
later experiment changing composition between successive geographic releases
rather than merely inserting longer pauses.

Interpretation Safeguards
-------------------------
- Micro-batch pacing is fixed and non-adaptive.
- A lower outside queue alone is not sufficient evidence of improvement.
- Longer elapsed time may be an intentional pacing cost and must be reported.
- Hierarchy activation and operational completion remain separate outcomes.
- The dataset is a controlled research condition, not an airline recommendation.
- Any reduction in dependency chains must be checked for displaced waiting.

======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 18
======================================================================
1. Timing-only windows were behaviourally neutral in Experiment 16.
2. Broad geographic cohorts changed dependency topology in Experiment 17.
3. Six uninterrupted geographic zones frequently intensified saturation in
   Experiment 18.
4. Geographic granularity is therefore non-linear rather than monotonically
   beneficial.
5. Experiment 18 produced genuine hierarchy utilisation at scale.
6. Priority ranking did not guarantee an executable cluster intervention.
7. Normal numerical headway remains active inside all cohorts, zones and batches.
8. Experiment 19 retains six zones but bounds their release into fixed
   deterministic micro-batches.
9. Runtime movement and dependency architecture remain frozen.
10. The next question is whether pacing can separate useful spatial structure
    from destructive local concentration.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v19 - EXPERIMENT 19 DESIGN
======================================================================



======================================================================
EXPERIMENT 19 - OFFICIAL FINDINGS
======================================================================

Execution Status
----------------
The complete deterministic run executed all 30 paired scenarios (60 total
executions). The standard and paced modes retained identical cabin geometry,
occupancy, scenario seed, passenger manifest, serving-aisle assignment, entry
headway range, synchronous movement, seat-event rules, dependency-region
lifecycle and hierarchy controls. Only the precomputed six-zone micro-batch
admission schedule differed.

Observed Results
----------------
- Successful completions across both modes: 29 of 60.
- Incomplete or stalled executions: 31 of 60.
- Paced micro-batches converted at least one incomplete standard case to full
  success; Scenario 3 improved from 196/204 to 204/204.
- Several ordinary cases remained neutral, including Scenario 2 at 204/204 in
  both modes.
- Near-complete regressions also occurred, including Scenario 1 at 304/306
  compared with a 306/306 standard completion.
- Severe local saturation remained possible. Scenario 4 seated 151/259 in the
  paced mode while 77 passengers remained outside and a 30-passenger dependency
  chain occupied the right aisle.
- The most severe recorded paced case ended at 169/324, a paired loss of 155
  passengers with 121 additional passengers outside.
- Rear-boundary locks, linked row-event chains and entry saturation with internal
  chains all remained present.

Principal Findings
------------------
1. Fixed micro-batch pacing partially recovered behaviour lost under Experiment
   18's uninterrupted fine geographic zones.
2. The recovery validates admission-wave size as a causal variable: geography
   alone was not responsible for every deterioration observed in Experiment 18.
3. Pacing was not sufficient as a universal remedy. Some scenarios still formed
   long, spatially concentrated aisle chains with large outside queues.
4. The result is therefore mixed rather than negative: pacing can convert a
   stalled case to success, remain neutral in ordinary cases, or still permit a
   severe saturation event depending on topology and seeded composition.
5. The evidence points to admission-wave shape, not merely batch size. Sharp
   boundaries between successive zones can still create concentrated local
   transitions even when each zone is internally paced.
6. Normal numerical entry headway remained active throughout. The observed
   changes came from eligibility order and pacing, not simultaneous insertion or
   movement-engine modification.

Discussion Incorporated Before Experiment 20
---------------------------------------------
Experiment 20 should retain both six-zone geography and fixed micro-batches but
change the shape of the transition between adjacent zones. Rather than waiting
for one zone's full batch sequence to finish before beginning the next, a small
precomputed overlap should introduce the first micro-batch of the next adjacent
zone before the final micro-batch of the current zone.

This is not runtime adaptation. The complete sequence is created before the
simulation begins, seeded order remains preserved inside every zone, and no
passenger is redirected after entry. The purpose is to smooth abrupt zone
boundaries while preserving deterministic reproducibility.

Experiment 19 Conclusion
------------------------
Experiment 19 confirms that deterministic pacing can recover some completions
and reduce some dependency structures, but fixed pauses alone do not eliminate
entry saturation. The next question is whether a smoother deterministic
inter-zone transition can retain spatial organisation without creating sharp
local release fronts.


======================================================================
EXPERIMENT 20 - OVERLAPPING GEOGRAPHIC MICRO-BATCH ADMISSION
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original deterministic people-movement backbone remains frozen. The new
logic operates only before execution by constructing the eligibility queue and
release ticks. Once admitted, every passenger follows the same one-tile
synchronous movement, row limit, blocker-yield, seat-event, reservation,
dependency-region lifecycle and hierarchy rules used in the preceding
experiments.

Planned Purpose
---------------
Test whether a small fixed overlap between adjacent geographic zones can smooth
the admission profile and reduce the severe entry-saturation cases that remained
under Experiment 19's strictly sequential micro-batch zones.

Paired Modes
------------
1. STANDARD DETERMINISTIC DATASET.
2. OVERLAPPING GEOGRAPHIC MICRO-BATCH DATASET.

Overlapping Admission Contract
------------------------------
- The cabin remains divided into six longitudinal destination-row zones.
- Overall progression remains rear to front.
- Seeded relative order is preserved inside each zone.
- Each zone is divided before execution into deterministic micro-batches.
- The first micro-batch of the next adjacent zone is inserted before the final
  micro-batch of the current zone.
- The overlap sequence and release ticks are fixed before execution.
- Normal deterministic numerical entry headway remains active.
- The entry tile must still be empty before insertion.
- Runtime congestion, dependency regions and seat events do not alter release.
- No passenger is reordered inside a zone, redirected after entry or permitted
  to switch aisle.

Independent Variable
--------------------
    FIXED ADJACENT-ZONE MICRO-BATCH OVERLAP

Primary Evaluation Order
------------------------
1. Correct deterministic overlap construction and replay.
2. Successful completions and conversions relative to the standard mode.
3. Outside-queue accumulation.
4. Longest dependency-chain length and critical-tree depth.
5. Entry-saturation, linked-row-event and rear-boundary residual families.
6. Confirmed-region concurrency and hierarchy competitions.
7. Cluster selections and executable starts.
8. Waiting cost and elapsed ticks.

Experimental Hypothesis
-----------------------
If sharp transitions between sequential geographic zones contributed to the
remaining Experiment 19 saturation cases, a small precomputed overlap should
smooth local admission density, reduce abrupt destination-band fronts and lower
the frequency or severity of entry-saturation chains.

A negative result would show that deterministic overlap merely redistributes the
same spatial concentration, and that future work should change passenger
composition inside micro-batches rather than only their temporal arrangement.

Interpretation Safeguards
-------------------------
- The overlap is fixed and non-adaptive.
- Improved completion must be checked against waiting and elapsed-time cost.
- Lower outside waiting alone does not prove reduced internal congestion.
- Rear-boundary locks are geometric constraints and may remain unaffected.
- The controlled dataset is not an airline boarding recommendation.
- The movement and dependency architecture remains frozen.

======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 19
======================================================================
1. Timing-only windows were neutral in Experiment 16.
2. Broad geographic cohorts changed dependency topology in Experiment 17.
3. Uninterrupted fine zones frequently intensified saturation in Experiment 18.
4. Fixed micro-batch pacing partially recovered completion in Experiment 19.
5. Pacing did not prevent all severe entry-saturation chains.
6. Admission-wave size and transition shape are now separate causal variables.
7. Normal entry headway remains active in every mode.
8. Experiment 20 introduces only a fixed adjacent-zone overlap.
9. Runtime movement and dependency architecture remain frozen.
10. The next question is whether smoother zone boundaries outperform strictly
    sequential geographic micro-batches.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v20 - EXPERIMENT 20 DESIGN
======================================================================



======================================================================
EXPERIMENT 20 - OFFICIAL FINDINGS
======================================================================

Execution Status
----------------
The complete deterministic run executed all 30 paired scenarios (60 total
executions). The standard and overlapping modes retained identical cabin
geometry, occupancy, scenario seed, passenger manifest, serving-aisle
assignment, numerical entry headway, synchronous movement, seat-event rules,
dependency-region lifecycle and hierarchy controls. Only the precomputed
adjacent-zone overlap schedule differed.

Observed Results
----------------
- Standard mode seated 7,927 of 7,996 passengers across the paired set.
- The overlapping mode seated 6,332 of 7,996 passengers, an aggregate loss of
  1,595 seated passengers.
- The overlapping mode was worse in 16 of 30 paired scenarios, improved three,
  and was equal in eleven.
- No incomplete standard case was converted to full success.
- Scenario 14 produced the largest paired loss: 36/259 compared with 259/259,
  with 160 additional passengers remaining outside.
- Scenario 9 seated only 33/216 under overlap, a loss of 183 passengers.
- Entry saturation with an internal chain was the dominant overlap residual
  family, appearing in 12 paired scenarios.
- Some neutral and modestly improved cases remained, including Scenario 22 at
  285/288 compared with 271/288, but these did not offset the dominant decline.

Principal Findings
------------------
1. Fixed adjacent-zone overlap did not smooth the admission profile reliably.
   It frequently allowed neighbouring geographic waves to coexist in the same
   aisle before the earlier wave had dispersed.
2. The resulting wave merger recreated the conditions of a large concentrated
   release: long occupied aisle chains, persistent yield-tile occupation and
   large outside queues.
3. Small deterministic waves are beneficial only while they remain sufficiently
   independent. Premature overlap removes that protection.
4. The result is a clear negative finding for fixed temporal overlap rather than
   for geographic organisation itself.
5. Normal numerical entry headway remained active throughout. The regression
   arose from eligibility-wave interaction, not simultaneous insertion or any
   movement-engine change.
6. Rear-boundary locks remained a separate geometric limitation and were not
   expected to disappear under admission overlap.

Discussion Incorporated Before Experiment 21
---------------------------------------------
The next experiment should stop using a fixed clock to decide when the next
geographic zone begins. Instead, it should apply a declared deterministic
completion milestone. The next adjacent zone becomes eligible only after a
fixed proportion of the current zone has entered the aircraft.

This is state-triggered but not optimisation-driven. The threshold is fixed
before execution, does not inspect congestion scores, dependency regions or seat
events, and does not choose among alternative policies at runtime. Its purpose
is to preserve wave independence while avoiding arbitrary timing assumptions.

Experiment 20 Conclusion
------------------------
Experiment 20 demonstrates that premature deterministic overlap is strongly
counterproductive. Admission-wave independence is more important than merely
smoothing a visual timing boundary. The next question is whether a fixed
completion-triggered release rule can preserve that independence while allowing
controlled progression between geographic zones.


======================================================================
EXPERIMENT 21 - COMPLETION-TRIGGERED GEOGRAPHIC ADVANCEMENT
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original deterministic people-movement backbone remains frozen. The new
logic governs only which preassigned passenger may become eligible at the
aircraft entrance. Once admitted, every passenger follows the same one-tile
synchronous movement, row limit, blocker-yield, seat-event, middle-bank
reservation, dependency-region lifecycle and hierarchy rules used throughout
the programme.

Planned Purpose
---------------
Test whether geographic admission waves can remain sufficiently independent
when progression to the next zone is controlled by a fixed completion milestone
rather than by fixed release ticks or premature overlap.

Paired Modes
------------
1. STANDARD DETERMINISTIC DATASET.
2. COMPLETION-TRIGGERED GEOGRAPHIC DATASET.

Completion-Triggered Admission Contract
---------------------------------------
- The cabin remains divided into six longitudinal destination-row zones.
- Overall progression remains rear to front.
- Seeded relative order is preserved inside every zone.
- Each aisle tracks its own zone progression independently.
- The next frontward non-empty zone is unlocked only after at least 80 percent
  of the currently active zone for that aisle has entered the aircraft.
- Once more than one zone is unlocked, passenger selection follows a fixed
  deterministic alternation across unlocked non-empty zones.
- The 80 percent threshold and alternation rule are declared before execution.
- Normal deterministic numerical entry headway remains active.
- The entry tile must still be empty before insertion.
- Congestion scores, dependency regions, seat events and hierarchy decisions do
  not alter the threshold or select a different policy.
- No passenger changes seat, serving aisle or destination after entry.

Independent Variable
--------------------
    FIXED ZONE-COMPLETION MILESTONE FOR FRONTWARD ADVANCEMENT

Primary Evaluation Order
------------------------
1. Correct deterministic threshold and replay behaviour.
2. Successful completions and converted-success cases.
3. Aggregate seated passengers and outside-queue accumulation.
4. Longest dependency-chain length and critical-tree depth.
5. Entry-saturation and linked-row-event residual families.
6. Rear-boundary residuals, which remain geometrically distinct.
7. Confirmed-region concurrency, hierarchy competitions and deferrals.
8. Waiting cost and elapsed ticks.

Experimental Hypothesis
-----------------------
If Experiment 20 failed because the next wave was released before the current
wave had dispersed sufficiently, an 80 percent completion milestone should
preserve more wave independence, reduce simultaneous geographic concentration
and recover completion relative to fixed overlap.

A negative result would show that a simple completion proportion is still too
coarse and that later work should examine deterministic composition inside each
release wave rather than only the timing or trigger of zone advancement.

Interpretation Safeguards
-------------------------
- The milestone is fixed and non-optimising.
- Runtime state is used only to evaluate the declared completion proportion.
- No congestion-sensitive or predictive admission decision is introduced.
- Improved completion must be checked against additional waiting time.
- A lower outside queue alone does not establish reduced internal dependency.
- The controlled dataset is not an airline boarding recommendation.
- The movement and dependency architecture remains frozen.

======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 20
======================================================================
1. Timing-only windows were neutral in Experiment 16.
2. Broad geographic cohorts changed dependency topology in Experiment 17.
3. Uninterrupted fine zones frequently intensified saturation in Experiment 18.
4. Fixed micro-batch pacing partially recovered completion in Experiment 19.
5. Premature adjacent-zone overlap caused a strong aggregate regression in
   Experiment 20.
6. Small admission waves help only while they remain sufficiently independent.
7. Normal entry headway remains active in every mode.
8. Experiment 21 replaces fixed overlap timing with an 80 percent completion
   milestone.
9. The trigger is deterministic and non-optimising; movement architecture stays
   frozen.
10. The next question is whether completion-triggered advancement preserves wave
    independence more reliably than fixed temporal overlap.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v21 - EXPERIMENT 21 DESIGN
======================================================================


======================================================================
EXPERIMENT 21 - OFFICIAL FINDINGS
======================================================================

Execution Status
----------------
The complete deterministic run executed all 30 paired scenarios (60 total
executions). Standard and completion-triggered modes retained identical cabin
geometry, occupancy, scenario seed, passenger manifest, serving-aisle
assignment, numerical entry headway, synchronous movement, seat-event rules,
dependency-region lifecycle and hierarchy controls. Only the declared
completion-triggered geographic admission policy differed.

Observed Results
----------------
- Standard mode seated 7,927 of 7,996 passengers.
- Completion-triggered mode seated 5,638 of 7,996 passengers, an aggregate loss
  of 2,289 seated passengers.
- Completion-triggered mode was worse in 17 of 30 pairs, improved four and was
  equal in nine.
- Four incomplete standard cases were converted to success, showing that the
  mechanism was not uniformly defective.
- Scenario 26 produced the largest loss: 31/353 compared with 353/353, with 251
  additional passengers outside and a 35-passenger dependency chain.
- The largest improvement was Scenario 22 at +17 seated passengers.
- Entry saturation with an internal chain was the completion-triggered residual
  family in 15 scenarios; 13 scenarios completed fully.
- Scenario 29 converted a 257/259 rear-boundary lock into 259/259 success.

Principal Findings
------------------
1. An 80 percent entry-completion threshold did not reliably preserve wave
   independence.
2. The threshold measured how much of a zone had entered, but not whether those
   passengers had dispersed spatially inside the aisle.
3. Consequently, a newly unlocked frontward zone could still merge with a dense
   unresolved rearward wave and create long entry-saturation chains.
4. The severe failures again showed dominant NEXT_AISLE_TILE_OCCUPIED evidence,
   large outside queues and linked row-event dependencies.
5. Neutral and converted-success cases confirm that completion-triggering is
   scenario dependent rather than universally invalid.
6. Normal numerical entry headway remained active. The negative result arose
   from admission-wave composition and internal spatial interaction, not from a
   movement-engine change.

Discussion Incorporated Before Experiment 22
---------------------------------------------
Experiments 18-21 have now tested increasingly refined timing, pacing, overlap
and completion-trigger rules. The repeated residual family indicates that the
next controlled variable should be passenger composition inside the active
wave, rather than another variation of when a zone becomes eligible.

Experiment 22 therefore returns to the broad rear/middle/front cohorts associated
with the constructive result in Experiment 17. Within each active cohort, it
interleaves eligible passengers from opposite serving aisles in a fixed
left/right sequence where possible. This changes spatial composition while
retaining deterministic cohort progression and ordinary entry headway.

Experiment 21 Conclusion
------------------------
Completion percentage is an incomplete proxy for wave dispersal. A zone may be
80 percent admitted while its passengers still occupy a long, tightly coupled
aisle chain. The next experiment therefore isolates opposite-aisle composition
inside broad cohorts rather than refining the release clock again.


======================================================================
EXPERIMENT 22 - COARSE-COHORT OPPOSITE-AISLE INTERLEAVING
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original deterministic people-movement backbone remains frozen. The new
logic affects only the order in which preassigned passengers become eligible at
the entrance. Once admitted, passengers use the same one-tile synchronous
movement, row limit, blocker-yield, seat-event, middle-bank reservation,
dependency-region lifecycle and hierarchy rules.

Planned Purpose
---------------
Test whether broad geographic cohort benefits can be retained while reducing
single-aisle concentration through deterministic opposite-aisle interleaving.

Paired Modes
------------
1. STANDARD DETERMINISTIC DATASET.
2. COARSE-COHORT OPPOSITE-AISLE INTERLEAVED DATASET.

Admission Contract
------------------
- The cabin is divided into three broad destination-row cohorts: rear, middle
  and front.
- Cohorts progress strictly rear to middle to front.
- A cohort advances only when both serving-aisle queues for that cohort are
  empty.
- Seeded relative order is preserved within each aisle/cohort queue.
- Where both aisles have eligible passengers, successful admissions alternate
  left then right in a fixed deterministic sequence.
- If the preferred aisle is temporarily unable to admit because of its entry
  cooldown or occupied entry tile, the other eligible aisle may proceed.
- The next successful admission preference is always the opposite of the side
  most recently admitted.
- Normal deterministic numerical entry headway remains active independently for
  each aisle.
- Entry tiles must remain empty before insertion.
- No congestion score, dependency region, seat event or hierarchy decision
  changes the cohort or aisle preference.
- No passenger changes seat, serving aisle or destination.

Independent Variable
--------------------
    OPPOSITE-AISLE COMPOSITION INSIDE BROAD GEOGRAPHIC COHORTS

Primary Evaluation Order
------------------------
1. Deterministic replay and correct rear/middle/front progression.
2. Aggregate seated passengers and converted-success cases.
3. Left/right admission balance within active cohorts.
4. Outside-queue accumulation and entry saturation.
5. Longest dependency-chain length and critical-tree depth.
6. Linked row-event and rear-boundary residual families.
7. Confirmed-region concurrency, hierarchy competitions and deferrals.
8. Waiting cost and elapsed ticks.

Experimental Hypothesis
-----------------------
If the repeated failures in Experiments 18-21 were amplified by one-sided
admission-wave composition, deterministic opposite-aisle interleaving inside
broad cohorts should reduce sustained concentration in a single aisle while
preserving the geographic structure that proved useful in Experiment 17.

A negative result would show that aisle alternation alone cannot control local
row-event dependencies and that the broad-cohort benefit depends on more than
left/right composition.

Interpretation Safeguards
-------------------------
- Interleaving is fixed and deterministic, not congestion adaptive.
- Numerical headway remains active and may delay either side independently.
- A balanced admission count does not by itself prove reduced internal
  dependency.
- Rear-boundary locks remain a separate geometric limitation.
- The controlled dataset is not an airline boarding recommendation.
- The movement and dependency architecture remains frozen.

======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 21
======================================================================
1. Timing-only windows were neutral in Experiment 16.
2. Broad geographic cohorts changed dependency topology in Experiment 17.
3. Fine zones frequently intensified saturation in Experiment 18.
4. Micro-batch pacing partially recovered completion in Experiment 19.
5. Adjacent-zone overlap caused strong regression in Experiment 20.
6. An 80 percent completion trigger also regressed strongly in Experiment 21.
7. Completion percentage does not measure spatial dispersal inside the aisle.
8. Entry saturation with internal chains remained the recurring failure family.
9. Experiment 22 returns to broad cohorts and changes wave composition through
   deterministic opposite-aisle interleaving.
10. Normal entry headway and the frozen movement architecture remain active.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v22 - EXPERIMENT 22 DESIGN
======================================================================


======================================================================
EXPERIMENT 22 - OFFICIAL FINDINGS
======================================================================

Execution Status
----------------
The complete deterministic run executed all 30 paired scenarios (60 total
executions). Standard and opposite-aisle-interleaved modes retained identical
cabin geometry, occupancy, scenario seed, passenger manifest, serving-aisle
assignment, numerical entry headway, synchronous movement, seat-event rules,
dependency-region lifecycle and hierarchy controls. Only the declared admission
composition inside the broad rear/middle/front cohorts differed.

Observed Results
----------------
- Standard mode seated 7,927 of 7,996 passengers.
- Coarse-cohort opposite-aisle interleaving seated 7,101 of 7,996 passengers,
  an aggregate loss of 826 seated passengers.
- Interleaving improved two pairs, was worse in 12 and was equal in 16.
- One incomplete standard case was converted to success.
- Scenario 1 improved from 221/235 to 232/235 and reduced the outside queue by
  eight passengers.
- In Scenario 1 the residual family changed from entry saturation with an
  internal chain to a rear-boundary lock, showing that interleaving can improve
  admission-wave behaviour in an individual case without resolving the final
  geometric boundary condition.
- Several already successful scenarios remained fully successful, confirming
  that the mechanism was not intrinsically invalid.

Principal Findings
------------------
1. Opposite-aisle alternation did not improve the architecture overall.
2. Aisle balance alone was not a sufficient proxy for reduced internal
   dependency.
3. Alternation weakened the local geographic cohesion that had been constructive
   in Experiment 17 and distributed seat-event activity across both aisles
   without reliably reducing row-event coupling.
4. The aggregate regression shows that broad geographic structure matters more
   than mechanically equalising left/right admissions.
5. The isolated improvements remain useful evidence: admission-wave composition
   can change the residual family even when it does not produce full completion.
6. Normal numerical entry headway remained active throughout; the result arose
   from deterministic queue composition rather than a movement-engine change.

Discussion Incorporated Before Experiment 23
---------------------------------------------
Experiments 17-22 have now tested geographic scale, timing windows, fine zones,
micro-batch pacing, overlap, completion-triggered advancement and opposite-aisle
interleaving. The evidence indicates that further variations of admission timing
or aisle alternation are unlikely to be the strongest next step.

Experiment 23 therefore retains the successful coarse rear/middle/front
geographic structure and changes only passenger composition inside each cohort.
Passengers are ordered by fixed blocker-complexity class, with simpler seat
topologies released before more complex topologies while seeded order is
preserved within each class.

Experiment 22 Conclusion
------------------------
Deterministic opposite-aisle alternation is not a general substitute for
geographic cohesion. The next controlled question is whether preserving the
cohort while ordering its internal seat topology can reduce blocker interaction
without reopening the movement architecture.


======================================================================
EXPERIMENT 23 - COARSE-COHORT BLOCKER-COMPLEXITY ORDERING
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original deterministic people-movement backbone remains frozen. The new
logic changes only the pre-execution order in which already assigned passengers
become eligible at the entrance. Once admitted, every passenger follows the same
one-tile synchronous movement, row limit, blocker-yield, seat-event,
middle-bank reservation, dependency-region lifecycle and hierarchy rules.

Planned Purpose
---------------
Test whether broad geographic cohort benefits can be retained while reducing
early blocker interaction by admitting lower-complexity seat topologies before
higher-complexity topologies inside each cohort.

Paired Modes
------------
1. STANDARD DETERMINISTIC DATASET.
2. COARSE-COHORT BLOCKER-COMPLEXITY-ORDERED DATASET.

Admission Contract
------------------
- The cabin is divided into three broad destination-row cohorts: rear, middle
  and front.
- Cohorts progress strictly rear to middle to front.
- Each aisle retains its own queue and ordinary numerical entry headway.
- Passenger complexity is calculated before execution from seat depth relative
  to the assigned serving aisle.
- Complexity class 0 contains aisle-adjacent or zero-crossing seats.
- Complexity class 1 contains seats one position deeper.
- Complexity class 2 contains deeper, multiple-blocker-prone topologies.
- Inside each aisle/cohort queue, classes progress from 0 to 1 to 2.
- Seeded relative order is preserved within every complexity class.
- Entry tiles must remain empty before insertion.
- No runtime congestion score, dependency region, seat event or hierarchy
  decision changes the declared class ordering.
- No passenger changes seat, serving aisle or destination.

Independent Variable
--------------------
    BLOCKER-COMPLEXITY COMPOSITION INSIDE BROAD GEOGRAPHIC COHORTS

Primary Evaluation Order
------------------------
1. Deterministic replay and correct cohort/class ordering.
2. Aggregate seated passengers and converted-success cases.
3. Outside-queue accumulation and entry saturation.
4. Seat-event requests, failed starts and blocker interaction.
5. Longest dependency-chain length and critical-tree depth.
6. Linked row-event and rear-boundary residual families.
7. Confirmed-region concurrency, hierarchy competitions and deferrals.
8. Waiting cost and elapsed ticks.

Experimental Hypothesis
-----------------------
If broad geographic cohesion is beneficial but mixed blocker complexity causes
premature seat-event coupling, admitting simpler seat topologies before deeper
ones should allow early passengers to clear the aisle and create more usable
yield space before complex blocker transactions begin.

A negative result would show that simple-first composition merely postpones or
concentrates the difficult seat events and that blocker complexity must not be
interpreted as an independently optimisable admission variable.

Interpretation Safeguards
-------------------------
- Complexity is fixed from seat topology before movement begins.
- The classes do not predict actual blockers present at runtime.
- Seeded order is preserved within each class.
- Numerical headway remains active independently for both aisles.
- A lower early blocker count does not by itself establish improved completion.
- Rear-boundary locks remain a separate geometric limitation.
- The controlled dataset is not an airline boarding recommendation.
- The movement and dependency architecture remains frozen.

======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 22
======================================================================
1. Broad geographic cohorts remain the strongest constructive admission result.
2. Fine geographic subdivision and several timing refinements regressed.
3. Micro-batch pacing produced partial recovery but did not eliminate severe
   saturation.
4. Opposite-aisle interleaving improved isolated cases but lost 826 passengers
   in aggregate.
5. Aisle balance is not equivalent to preserved geographic cohesion.
6. Experiment 23 retains broad cohorts and tests fixed blocker-complexity
   composition inside each cohort.
7. Simple, intermediate and complex classes are determined before execution.
8. Normal entry headway and the frozen movement architecture remain active.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v23 - EXPERIMENT 23 DESIGN
======================================================================


======================================================================
EXPERIMENT 23 - OFFICIAL FINDINGS
======================================================================

Execution Status
----------------
The complete deterministic run executed all 30 paired scenarios (60 total
executions). Standard and blocker-complexity-ordered modes retained identical
cabin geometry, occupancy, scenario seed, passenger manifest, serving-aisle
assignment, numerical entry headway, synchronous movement, seat-event rules,
dependency-region lifecycle and hierarchy controls. Only the fixed pre-execution
ordering of seat-topology classes inside the broad cohorts differed.

Observed Results
----------------
- Standard mode seated 7,927 of 7,996 passengers.
- Coarse-cohort blocker-complexity ordering seated 6,466 of 7,996 passengers,
  an aggregate loss of 1,461 seated passengers.
- Complexity ordering improved three pairs, was worse in 19 and was equal in
  eight.
- No incomplete standard case was converted to success.
- Scenario 1 improved from 221/235 to 232/235 and reduced the outside queue by
  eight passengers.
- Scenario 1 changed from entry saturation with an internal chain to a
  rear-boundary lock, showing that topology ordering can improve an individual
  admission wave without generalising across the dataset.
- Scenario 2 regressed from 216/216 to 213/216 and ended in a linked row-event
  chain.
- Scenario 3 regressed from 306/306 to 130/306, with 141 passengers still
  outside, 28 moving in the aisle and seven waiting at rows.

Principal Findings
------------------
1. Fixed simple-to-complex ordering was a clear aggregate regression.
2. Seat-topology complexity is not an independently optimisable admission
   variable in this architecture.
3. Grouping all simple passengers before intermediate and complex passengers
   weakened the natural seeded spatial relationships inside each broad cohort.
4. Difficult seat events were postponed and then concentrated rather than
   eliminated.
5. The strongest failures returned to entry saturation, long aisle queues and
   linked row-event chains.
6. The isolated Scenario 1 improvement remains valid evidence that composition
   can alter the residual family, but it does not support general adoption.
7. Normal numerical headway remained active and the movement engine remained
   frozen throughout.

Discussion Incorporated Before Experiment 24
---------------------------------------------
Experiments 17-23 have now tested equal broad cohorts, finer zones, fixed timing,
micro-batches, overlapping waves, completion-triggered advancement, opposite-
aisle interleaving and blocker-complexity ordering. The repeated regressions show
that preserving broad geographic cohesion and seeded internal order is more
important than imposing additional ordering classes.

Experiment 24 therefore restores seeded order inside each aisle/cohort and
changes only the positions of the two broad longitudinal boundaries. Instead of
equal thirds, deterministic geometry-weighted boundaries allocate approximately
25 percent of rows to the front cohort, 35 percent to the middle cohort and 40
percent to the rear cohort. This tests boundary placement without changing the
movement architecture or introducing runtime adaptation.

Experiment 23 Conclusion
------------------------
Simple-first blocker ordering does not generalise. It can postpone and
concentrate complex seat events while breaking useful spatial relationships.
The next controlled variable is cohort boundary geometry, with passenger order
otherwise restored.


======================================================================
EXPERIMENT 24 - GEOMETRY-WEIGHTED COARSE-COHORT BOUNDARIES
======================================================================

Connection to Amit Amlani's Original People-Movement Algorithm
--------------------------------------------------------------
Amit's original deterministic people-movement backbone remains frozen. The new
logic changes only the pre-execution row boundaries used to place passengers
into rear, middle and front admission cohorts. Once admitted, every passenger
uses the same one-tile synchronous movement, row limit, blocker-yield,
seat-event, middle-bank reservation, dependency-region lifecycle and hierarchy
rules.

Planned Purpose
---------------
Test whether the constructive broad-cohort behaviour can be retained or improved
by moving the cohort boundaries away from equal thirds while preserving seeded
passenger order inside each cohort.

Paired Modes
------------
1. STANDARD DETERMINISTIC DATASET.
2. GEOMETRY-WEIGHTED COARSE-COHORT DATASET.

Admission Contract
------------------
- The cabin retains three broad destination-row cohorts.
- Cohorts progress strictly rear to middle to front.
- The front cohort contains approximately 25 percent of cabin rows.
- The middle cohort extends to approximately 60 percent of cabin rows, giving
  it approximately 35 percent of rows.
- The rear cohort contains the remaining approximately 40 percent of rows.
- Exact integer boundaries are calculated deterministically from each cabin's
  row count before execution.
- Each aisle retains its own seeded queue inside every cohort.
- Seeded relative order is preserved; no complexity sort or aisle alternation
  is applied.
- Ordinary numerical entry headway remains active independently for each aisle.
- Entry tiles must be empty before insertion.
- No runtime congestion, completion, dependency or hierarchy signal changes a
  boundary or passenger's eligibility.
- No passenger changes seat, serving aisle or destination.

Independent Variable
--------------------
    PRECOMPUTED LONGITUDINAL COHORT-BOUNDARY GEOMETRY

Primary Evaluation Order
------------------------
1. Deterministic replay and correct geometry-weighted cohort membership.
2. Aggregate seated passengers and converted-success cases.
3. Comparison with the equal-third broad-cohort result.
4. Outside-queue accumulation and entry saturation.
5. Longest dependency-chain length and critical-tree depth.
6. Rear-boundary, linked row-event and internal-chain residual families.
7. Confirmed-region concurrency, hierarchy competitions and deferrals.
8. Waiting cost and elapsed ticks.

Experimental Hypothesis
-----------------------
If equal thirds place too much pressure on a narrow rear operating region,
allocating a larger share of cabin rows to the rear cohort may preserve local
geographic cohesion while reducing abrupt density changes at the rear/middle
boundary.

A negative result would show that broad-cohort benefit is not improved merely by
moving static boundaries and that the equal-third division is already an
adequate coarse representation.

Interpretation Safeguards
-------------------------
- Boundaries are derived only from cabin row count before execution.
- The 25/35/40 proportions are a controlled research partition, not an airline
  recommendation.
- Seeded passenger order is restored and preserved inside each cohort.
- Numerical headway remains active independently for both aisles.
- Rear-boundary locks remain a separate physical limitation.
- No runtime adaptation or congestion optimisation is introduced.
- The movement and dependency architecture remains frozen.

======================================================================
RUNNING CONCLUSIONS AFTER EXPERIMENT 23
======================================================================
1. Broad geographic cohorts remain the strongest constructive admission result.
2. Fine subdivision and multiple timing refinements produced major regressions.
3. Micro-batch pacing gave partial recovery but did not generalise fully.
4. Opposite-aisle interleaving and blocker-complexity ordering both weakened
   aggregate performance.
5. Experiment 23 lost 1,461 seated passengers relative to standard mode.
6. Seat complexity cannot be treated as an independent admission priority.
7. Experiment 24 restores seeded internal order and changes only static cohort
   boundary geometry.
8. Normal entry headway and the frozen movement architecture remain active.

======================================================================
END OF DETERMINISTIC STRESS DATASET RESEARCH LOG v24 - EXPERIMENT 24 DESIGN
======================================================================
