# CCT Marquee Simulation Program

These simulations are standalone model-level demonstrations of CCT design
possibilities. They do not need to become hardware benches and do not replace
the discriminator-oriented bench lanes in `cct-ltua/analysis`.

The four possibility classes are:

1. Structured control expands a nonlinear reachable-state graph.
2. Structured driving changes a material-transition process frontier.
3. Structured excitation expands the qualified functions of a fixed wave
   architecture.
4. Structured material processing writes retained geometry.

The first lane ended with the closed multistable Phase-1C result: a raw
phase/feedback-dependent signal survived, but it missed the access and nuisance
gates and failed the half-step numerical audit. It is not a marquee result and
will not be retuned or reinterpreted.

The material-transition lane is also closed without a marquee result. Its new
spatial NiTi TDGL pilot was kept separate from the earlier bulk-strain NiTi
experiment. Structured feedback and the optimized per-command composite each
qualified 8/9 retained variant states. Structured feedback improved accuracy
on two twin mixtures, but required more generalized work and left more interface;
it earned zero process wins and a matched-coverage qProgT ratio of 0.878. Time
shuffling reduced exact successes from 61 to 39 and wrong-target feedback to
zero, so temporal organization was a real mechanism inside the model, but it
did not beat optimized proportional loading on access, process quality, energy
efficiency, or nuisance robustness. All 90 half-step comparisons passed. The
reserved 32 confirmation seeds remain untouched.

The `fixed_wave_function_phase0_pilot` remains a separate, frozen development
result. In its eight seeds, coherent space-time inversion reached all 10 complex
output functions while the per-command oracle composite of four optimized
baselines reached eight. Its advance screens passed. Nothing in the later
confirmation overwrites, pools, or retrospectively reclassifies that assessment.

The separate `fixed_wave_function_phase1_confirmatory` run is now complete on
32 previously untouched seeds. Structured control qualified 9/10 nominal
functions versus 8/10 for the composite baseline. That +1 difference missed the
predeclared +2 access gate, even though the access sign was positive in 6/7
plant cases. The missing qualification was `switch_2_to_3`, which succeeded on
26/32 seeds and therefore missed both the 27-success requirement and the frozen
Wilson-lower-bound threshold.

The confirmation did pass a different, independent result. Across the eight
functions reachable by both controller families, structured control reduced
mean coherent cross-talk from 0.1338 to 0.0487 (63.6%) at the same mean incident
energy and without a command-level success regression. The sign persisted in
7/7 frozen plant cases. Phase scrambling and wrong-model inversion each reduced
314/320 structured successes to zero; time shuffling did the same as an
independent diagnostic. All 200 half-step numerical comparisons retained their
labels, with zero passivity-closure failures. Matched-coverage qProgT remained
exactly 1.0, so no efficiency badge was earned.

The promoted model-level possibility is therefore narrower than the pilot
suggested: structured space-time excitation can improve the process frontier
for functions already shared with optimized controls, and that improvement
depends on phase and architecture information. This confirmation does not
support the stronger predeclared reachable-set expansion or programmability-per-
joule claims.

The retained-geometry lane has completed its separate Phase-0 pilot. In a
dimensionless kinematic-hardening Cosserat rod with explicit unloaded 3D
geometry, state-conditioned parallel allocation reached 6/8 command classes,
the same as the per-command oracle composite of end, moving-zone, static, and
cyclic open-loop baselines. It therefore did not expand the nominal reachable
set. It did pass an isolated process screen on the two helix commands: relative
to optimized end loading, mean source energy was 60.2% lower and active steps
were 46.1% lower without a frozen quality regression. That two-command process
sign persisted in 5/7 plant cases. Its matched-six-command qProgT ratio was
1.729, and all 80 numerical-refinement comparisons passed.

Those positive screens are not advanced because their preregistered mechanism
test failed. Feedback-parallel and time-shuffled schedules both produced 57/64
exact nominal outcomes; a calibration-derived feedback-blind replay produced
63/64, while spatial zone permutation fell to 14/64. The experiment therefore
supports spatial actuator assignment inside the model, but not a benefit from
online state feedback or temporal order. The blind-replay performance is a
lead for a new learned open-loop distributed-schedule experiment, not a result
retrospectively reassigned to this pilot. Its 32 confirmation seeds remain
untouched.

That lead was then tested separately as
`retained_geometry_open_loop_program_phase1`, with the exact frozen blind
schedule promoted before any new seed was opened. On 16 fresh nominal rods the
learned program produced 115/128 exact outcomes, but only five command classes
met the stricter 14/16 reachability requirement. The newly calibrated
conventional composite also reached five. Both S-bends scored 12/16 and the
spatial wave 11/16, so there was no access expansion. The candidate earned zero
nominal process wins, and its matched-five-command qProgT ratio of 1.2399 missed
the independent 1.25 gate.

The Phase-1 experiment did validate a narrower mechanism. Spatial zone
permutation and uniform-dose replacement each reduced 115/128 exact outcomes
to zero; reconstructing the same per-zone dose with different coactivation
reduced it to 4/128, while shuffling intact schedule blocks retained 111/128.
Thus zone identity and block coactivation/dose structure mattered strongly,
whereas the global ordering of intact blocks mattered little. A direct
open-loop optimizer exactly matched the candidate at 5/8 reachable commands
and 115/128 outcomes. The supported model-level statement is therefore that a
spatially programmed distributed load can reliably write several retained
geometries, but this run does not show access, process, or programmability-per-
energy advantage over strong standard controls, nor a unique benefit from the
feedback-derived compiler. No confirmation was opened.

The coordination-order challenge and its FHN external-transfer follow-up remain
positive but non-distinctive results. The order descriptor correctly classified
all five synthetic coordination cases, and the frozen temporal `2->1` program
then beat its reverse and marginal-matched destructuring on the external FHN
ring. In both experiments a strong established workflow reached the same
answer. These runs therefore support the portability and usefulness of the CCT
description, not unique ownership of the mechanism.

The original `cross_domain_temporal_prediction_phase0` is preserved as a
separate selector-v0 result. Its CCT-labeled workflow was allowed to choose only
the temporal pair with the largest commutator contrast or a non-temporal
fallback, while the comparator could choose any of 11 policies. The resulting
native advantage is valid for that restricted selector but is not a fair
estimate of CCT's broader potential. A retrospective audit found that a temporal
program beat the best equal-energy non-temporal program in 21/24 completed
cases, with a wholly positive paired interval in 19/24. The restricted selector
added 0.01731 mean regret relative to equal full-menu access; 0.01551 of that
penalty remained after merely removing its promotion gates, locating the main
problem in temporal-pair access rather than confidence testing.

The separate `cross_domain_opportunity_map_phase0r` pilot repaired that
asymmetry prospectively. It froze 12 previously unevaluated interior
interpolation cases, six FHN and six LLG, and gave both selectors access to the
same complete 11-policy equal-drive menu. Temporal coordination improved the
held-out task frontier in 12/12 cases. Mean best-temporal minus
best-non-temporal score was +0.03819, with a case-bootstrap 95% interval of
+0.02311 to +0.05886; the sign was positive separately in both systems.

The calibration-only task-aligned causal contrast predicted the fresh held-out
opportunity gain with Pearson correlation 0.988 and Spearman correlation 0.909,
and its unrestricted full-menu mean selector chose the held-out best program in
12/12 cases. The one-standard-error full-menu comparator chose the best in
11/12, so the pilot provides no broad claim of distinctive CCT superiority from
that one disagreement. Its strongest supported possibility is instead that one
continuous, system-independent intervention contrast prospectively identified
the magnitude of useful temporal coordination across two unrelated standard
model families. The advancement screen passed, but this remains a small
interior-case pilot rather than a broad parameter-domain confirmation.

The subsequent `cross_domain_opportunity_discrimination_phase1` confirmation
closed that specific gap. Before calibration it froze broad 36-case banks for
each system, the complete equal-drive policy menu, the four calibration seeds,
the high/boundary/low selection algorithm, and all possible holdout seeds.
Calibration then selected four cases per stratum and system, and those 24 cases
were frozen before any of their 32-seed holdouts were opened. The primary
held-out quantity compared the exact temporal and non-temporal programs chosen
during calibration, rather than retrospectively choosing the best holdout
programs.

The confirmation produced 11 positive, six uncertain/null, and seven negative
cases. The signed calibration contrast classified all 18 decisive cases
correctly and obtained qualified-positive AUC 1.0. Its association with held-out
gain was Pearson 0.9975 (case-bootstrap 95% interval 0.9885-0.9994) and Spearman
0.9974 (0.9763-1.0000), with mean absolute prediction error 0.00625. All eight
predicted-high cases were positive; the eight boundary cases split into three
positive, four null/uncertain, and one negative; the eight predicted-low cases
contained six negative and two null/uncertain. The numerical audit had zero
prospective-pair or workflow sign changes.

Both unrestricted full-menu selectors achieved zero held-out regret in all 24
cases and made identical decisions. The confirmation therefore supports the
cross-domain predictive-discrimination possibility, but not distinctive CCT
superiority. It also does not yet show that the contrast avoids full policy
calibration: both workflows observed all 11 policies on four calibration seeds.
The earned result is that one common intervention contrast, computed under a
small and equal calibration budget, prospectively separated where temporal
coordination helped, did not matter, or hurt across two standard model families.

The next `cct_limited_probe_discovery_phase0` pilot tested whether the CCT
representation could find useful programs sooner rather than merely describe a
complete sweep. It expanded the equal-drive menu from 11 to 32 schedules and
compared adaptive Gaussian-process searches over probe budgets 2 through 10 on
12 fresh FHN and LLG cases. Both workflows received the same two initial
probes, four common calibration seeds per queried policy, unrestricted access
to every schedule, and the same upper-confidence acquisition procedure. The
CCT model class combined raw schedules with timing, switching, coactivation,
directed lag-order, and triple-coordination features; it contained the raw-only
comparator as a zero-blend fallback. Development tuning nevertheless selected
a fully structural kernel before any fresh outcome was evaluated.

Across the complete regret-versus-probe curve, CCT reduced mean regret-area by
0.01656 relative to raw-schedule active search, with a paired case-bootstrap
95% interval of -0.03429 to -0.00175. At three probes CCT had found the held-out
best policy in 5/12 cases versus 3/12; at four probes the split was 7/12 versus
3/12; and at ten probes it was 9/12 versus 7/12. CCT's mean regret was lower at
every post-anchor budget. The clearest gain was in LLG; FHN was approximately
equivalent over the whole curve. Of 93 divergent adaptive probes, the CCT probe
had the higher held-out value 44 times, the raw-GP probe 33 times, and 16 tied.
The numerical audit passed with zero workflow sign changes.

This pilot is the first direct evidence in the program that the CCT structural
representation can reduce policy-search burden rather than only organize or
predict a full calibration map. Its comparison is to a tuned raw-schedule
Gaussian-process search, not every possible domain-native active learner, and
the cross-domain mean advantage is driven mainly by the LLG cases. A larger
confirmation with an additional unseen model family is therefore the
appropriate test of general reduced-search advantage.

Earlier EHO campaigns remain a separate positive source lineage. The selected
program begins from newly frozen tasks and uses an explicit passivity ledger,
intervention-channel information, seeded disorder, held-out evaluation, and
separate access, process, and qProgT outcomes.
