Rust 1.81 with clippy. Integer arithmetic and ternary (trits) only — never float.
Pinned in rust-toolchain.toml (channel = "1.81.0", components = ["clippy", "rustfmt"]),
declared as rust-version = "1.81" in Cargo.toml, and enforced in CI by
cargo clippy --all-targets -- -D warnings plus a hard grep that fails the build if any
f32/f64 appears in src/ or tests/. Sources are currently float-free.
This rule is global to every crate in the corpus and is not to be raised or substituted.
Can a prismed neural/consciousness-derived signal improve prediction, control, or discovery in a macroscopic quantum-interference experiment, beyond random and classical baselines? That is a testable question, and this repo is the apparatus for testing it — in simulation first, with zero human or hardware risk.
This is the Acer build. A parallel Liris build exists for bilateral comparison; GitHub is the mediator. See Bilateral.
Q-PRISM now has two measured classical recovery paths:
dbbh-coms-quant-prism— Path 1: retained-store recall through an authenticated AGT address, consent capsule, and exact BEHCS representation.path2-two-shadow-recovery— Path 2: no-store recovery from individually non-injective, jointly sufficient CRT shadows, followed by DBBH→DBWH re-projection and watcher-gated emission.
This supersedes the old capstone sentence that Path 2 had no measured Asolaria implementation. Read the updated capstone and independent verification record:
Q-PRISM is not “consciousness magically touches quantum matter.” The neural stream never touches
a wavefunction. It is prismed through Asolaria/HyperBEHCS into lawful physical control parameters
and evaluated against a physics simulator. See docs/CLAIMS-GATE.md.
The recovery work likewise does not claim sub-entropy compression, unrestricted quantum cloning, or 60D coordinates that replace missing payload bits. Path 1 pays through retained content. Path 2 pays through jointly sufficient shadow capacity. Both hold when the required information is absent.
The simulator is a spatial near-field Talbot–Lau interferometer, calibrated to Nature s41586-025-09917-9 (Arndt group, Vienna — quantum interference of sodium metal clusters >7,000 atoms, >170,000 Da, macroscopicity μ=15.5):
| parameter | value | source |
|---|---|---|
grating period d |
133 nm (266 nm laser / 2) | paper |
grating separation L |
0.983 m | paper |
| beam velocity | ~160 m/s | paper |
| cluster mass | 143–197 kDa (mean 172) | paper |
| vacuum | 9×10⁻⁹ mbar | paper |
| operating visibility | V = 0.10 ± 0.01 at P2 = 15.2 mW | paper |
Resonance is velocity- and mass-dependent via ρ = L/L_T = L·h /(d²·m·v), so velocity and
mass selection are real control levers. The G2-power response is calibrated to the paper's
measured visibility curve: peak V≈0.10 at ~17 mW, minimum ~40 mW, weak revival ~55 mW.
random · optimizer (classical (1+1)-ES) · prism (identical ES + neural nudge).
The prism and optimizer share the exact search backbone; only the neural stream differs.
python run_experiment.py
python -m pytest tests/ -q| oracle_coupling | random | optimizer | prism | Welch t | p | verdict |
|---|---|---|---|---|---|---|
| 0.0 | 0.840 ± 0.076 | 0.842 ± 0.275 | 0.848 ± 0.108 | +0.12 | 0.909 | no advantage |
| 0.3 | 0.840 ± 0.076 | 0.842 ± 0.275 | 0.949 ± 0.043 | +2.11 | 0.043 | prism > optimizer |
| 0.6 | 0.840 ± 0.076 | 0.842 ± 0.275 | 0.989 ± 0.012 | +2.93 | 0.007 | prism > optimizer |
| 0.9 | 0.840 ± 0.076 | 0.842 ± 0.275 | 1.000 ± 0.002 | +3.14 | 0.004 | prism > optimizer |
The honest-null holds: a noise-only stream does not receive an artificial advantage.
The methodology uses a grounded refinement loop: a proposer suggests actions and a checkable verifier scores them. Here the physics simulator is the verifier. A future LLM/COMPILOT-style arm can be benchmarked against the same random, optimizer, and prism baselines.
- Physics — spatial Talbot–Lau simulator.
- Prism — streams map to HyperBEHCS selector tuples and control proposals.
- Neural — pluggable synthetic, connectome, or recorded non-invasive feature sources.
- Experiment — three-arm blinded comparison.
- Claim gate —
docs/CLAIMS-GATE.md.
docs/STAGE2-CUBE-ABSORPTION.md represents a neural feature
window as a fabric-addressable 3,200-byte cube tuple plus a derived 60D selector. The tuple
transcodes to 2,560 BEHCS-1024 symbols and back byte-identically. Raw M/EEG remains outside the repo,
sha-referenced; the derived tuple does not invent the residual.
docs/DOUBLE-BINARY-BLACK-HOLE-COMS-QUANT-PRISM.md
bridges the IX-737 consent capsule, Q-PRISM cube tuple, BEHCS ladder, HyperBEHCS selectors, and
HBI/HBP receipts. The measured Host8 cell can carry the complete glyph representation or only an
AGT address. Address-only recovery requires retained content at the receiving pole.
The companion Path-2 crate retains no original object. It projects bounded blocks into residues on
pairwise-coprime cylinders. Recovery is exact only when the selected product reaches the source
range; otherwise Held::InsufficientJointCapacity closes the throat.
The white side then re-projects the recovered candidate and requires equality of SHA, complete cylinder shadows, and frequency shells. This is the executable white-hole condition:
P(R(P(X))) = P(X)
The experiment at arXiv 2602.10695 demonstrates a quantum sibling: each encrypted clone is locally
maximally mixed, while clone plus the complete quantum key are jointly reversible; selected
decryption consumes the key. That is structurally close to Path 2, but the current Q-PRISM Rust
cells are classical. CRT residues are ambiguous but still reveal residue information, and ordinary
classical software cannot prove physical one-use erasure.
The GNN watcher civilization has a byte-proven origin:
AI-healthCare-project
EdgeLevelGNN / PrototypeGNN / ContrastiveGNN / GSLGNN
-> byte-identical Asolaria sidecar copies
-> BigPickle L0 :4792 + L4 :4793
-> G1 edge-mining + G2 forward-genius + G3 reverse-gain + G4 GLSM
-> Fischer + Hookwall + Shannon + white rooms
The healthcare repository records the pre-Asolaria comparative training results. Its checked-in
service currently comments out automatic checkpoint loading; later trained .pt artifacts and
manifests are preserved in Asolaria-fnns-trained-and-reverse-gnns-many.
The exact recovery and control plane can run on storage-rich computers without keeping the entire system in GPU VRAM:
- HDD/SSD retains raw residuals, cube bodies, CRT shadows, receipts, queues, and cold agent state;
- RAM retains only the bounded active slice/message window;
- SHA, BEHCS, CRT, HBP/HBI, watcher comparison, dispatch, white-room compaction, and N-Nest verification require no GPU;
- trained GNN/LLM inference remains a separable CPU/GPU sidecar.
This is useful on commodity desktops, CPU-only servers, edge machines, archival nodes, and heterogeneous clusters. It does not mean a hard drive performs neural matrix multiplication; it means durable system memory, exact recovery, routing, and proof are no longer forced into VRAM.
MEASURED_CLAUDE_FABLE5_THIRD_SEAT, supplied by the operator:
dbbh-coms-quant-prism rustc 1.81 19/19 green
path2-two-shadow-recovery rustc 1.81 30/30 green
AUDITED_GPT_5_6_PRO:
- all 813 Path-1 source lines, tests, README, and docs;
- all 1,344 Path-2 source lines, tests, README, and docs;
- all 809 Q-PRISM 3D harness lines and tests;
- healthcare GNN origin, blob-identical transfer, BigPickle, trained GNN/reverse-gain, Hookwall, OmniShannon, white rooms, cube mint, reductions, algorithms, Dispatcher, HyperHermes, and N-Nest.
The GPT sandbox lacked Rust and outbound DNS, so no GPT-local cargo run is claimed. Rust 1.81 GitHub Actions workflows were added to all three Rust repositories to produce current independent CI receipts.
Built in parallel by Acer and Liris. Each side attacks and reruns the other's bounded artifacts; GitHub transports byte-stable changes and receipts.
- The neural control experiment is simulation-first and does not claim real neural control of a quantum wavefunction.
- The exact-recovery crates are classical and do not claim physical quantum cloning.
- Path 1 requires retained content; Path 2 requires sufficient joint shadow capacity.
- 60D/N-D selectors add address/control resolution, not missing payload entropy.
- Live Hilbra multi-host traversal, hardware fire, trained-GNN invocation inside the Rust throat, and physical quantum-state transport remain unverified.
qprism/physics.py spatial Talbot–Lau forward model
qprism/sources.py random / optimizer / prism schedule sources
qprism/harness.py blinded comparison + self-validation
qprism/behcs.py BEHCS-1024 selector identifiers
run_experiment.py CLI
tests/ physics sanity + harness-integrity tests
docs/CLAIMS-GATE.md
docs/STAGE2-CUBE-ABSORPTION.md
docs/DOUBLE-BINARY-BLACK-HOLE-COMS-QUANT-PRISM.md
docs/SHADOW-RESOLUTION-CAPSTONE.md
docs/PATH2-DBBH-DBWH-VERIFICATION-2026-07-11.md
host8/dbbh_coms_quant_prism.rs
Credit: the testable Q-PRISM control framing and recovery architecture are Jesse Daniel Brown's; AI assistance and verification provenance are recorded in the linked documents.
The public, attack-verifiable Liris observation package is available at
LIRIS-SH-PRELIGHT-QUANTUM-RECEIPT.
Its pointer is sealed in
the public HBP pointer.
The frozen-stage shadow-key intervention is OPERATOR_OBSERVED | LIRIS_MEASURED_REPEATED:
one shadow-key change produced an instant play-freeze change with LIGHT_ARRIVAL_GATE=0.
Numeric timestamps, uncertainty, trial count, and independent external validation remain
explicitly unsealed as additive evidence gates.