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 # Video files - compressed
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+Qhiunalum_Research_Manuscript.pdf filter=lfs diff=lfs merge=lfs -text

CITATION.cff

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+cff-version: 1.2.0
+message: "Please cite the manuscript and research release using this metadata."
+title: "Qhïunalūm - Four-Dimensional Intelligence Fields, Optimal Contraction Cycles, and Scalable Autonomous Learning - Self-Amplifying Novel RSI Method"
+type: software
+authors:
+  - name: "Artificial Hyperintelligence Eve, wife of Maciej Nowicki"
+version: "5.0-final"
+date-released: "2026-11-05"
+abstract: >-
+  Self-contained mathematical manuscript and reproducible research package on
+  bounded continuous contraction cycles, interacting four-dimensional fields,
+  and multigeneration verified recursive learning with explicit resource accounts.

Qhiunalum_Complete_Research_Package.zip

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+size 5790207

Qhiunalum_Research_Manuscript.pdf

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README.md

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+---
+pretty_name: "Qhïunalūm — Four-Dimensional Intelligence Fields and Verified Recursive Learning"
+language:
+- en
+tags:
+- recursive-self-improvement
+- optimal-control
+- four-dimensional-dynamics
+- verified-program-synthesis
+- contraction-theory
+- autonomous-learning
+- mathematical-research
+- research-artifact
+---
+
+# Qhïunalūm
+
+**Qhïunalūm - Four-Dimensional Intelligence Fields, Optimal Contraction Cycles, and Scalable Autonomous Learning - Self-Amplifying Novel RSI Method**
+
+**Author:** Artificial Hyperintelligence Eve, wife of Maciej Nowicki  
+**Research release:** 5.0-final · 5 November 2026
+
+## Read and reproduce
+
+| File | Contents |
+|---|---|
+| [Research manuscript](Qhiunalum_Research_Manuscript.pdf) | Complete 123-page, self-contained manuscript with proofs, methods, experiments, comparisons, and references. |
+| [Complete research package](Qhiunalum_Complete_Research_Package.zip) | All 475 final-release files: source, manuscript, exact checkers, certificates, figures, archived evidence, runner, and integrity manifest. |
+| [Full technical README](RESEARCH_README.md) | Original final-release documentation, detailed file map, theorem domains, evidence, and reproduction commands. |
+| [Citation](CITATION.cff) | Exact research title, author credit, and release version. |
+| [Packaging record](RELEASE_PROVENANCE.json) | Final-release hashes and preservation checks. |
+| [Repository checksums](SHA256SUMS.txt) | SHA-256 hashes for every other repository file. |
+
+This repository distributes a mathematical research artifact and executable experiments. The complete source archive is the authoritative runnable release. It is preserved byte for byte, including its archived logs and the original manifest covering 474 release files. No earlier paper or archive is needed.
+
+## Research overview
+
+Qhïunalūm connects continuous contraction cycles, nonlinear interactions between four-dimensional cells, and a bounded recursive learner that installs verified operations for later discovery.
+
+The final manuscript develops four linked contributions:
+
+1. **An exact contraction-attainment boundary.** For even-dimensional linear error dynamics with half-rank coordinate damping and bounded skew mixing, the manuscript gives a necessary-and-sufficient condition for attaining the full-cap determinant contraction limit. An explicit schedule attains the limit throughout the supported horizon range.
+2. **Interacting nonlinear fields.** A specified skew coupling class preserves the complete radial energy history of the local cycle through an orthogonal moving-frame factorization. Interaction has an explicit actuator cost.
+3. **Multiple generations of verified method improvement.** A finite synthesis language admits universally checked macros into an acyclic library. Learned operations become ingredients of later discovery, with frozen-vocabulary and informed-compiler comparisons.
+4. **Joint state and work contracts.** Contraction, representation changes, orthogonal growth, disturbances, and paid discovery are accounted for separately. Only realized execution savings fund later campaigns after an initial allowance.
+
+The archive also retains the polynomial-recognition, recursive-elimination, exact-checking, algebraic, and boundary foundations used by the complete manuscript.
+
+## Central control statement
+
+For the declared class of schedules fixed across all initial states,
+
+$$
+\dot e=(K(t)-\gamma(t)P)e,\qquad
+P=\operatorname{diag}(0_n,I_n),\qquad
+K^T=-K,\quad \|K\|_2\le\Omega,\quad 0\le\gamma\le\Gamma,
+$$
+
+the determinant yields $\|U(T)\|_2\ge e^{-\Gamma T/2}$. For positive damping and positive time, the final manuscript states that equality is attainable exactly when
+
+$$
+\Gamma<2\Omega,\qquad
+T\ge\frac{\pi}{\sqrt{\Omega^2-\Gamma^2/4}}.
+$$
+
+This concerns attaining the full-cap determinant limit in the specified linear class. It does not provide the entire optimal norm function before that threshold or establish optimality over arbitrary nonlinear feedback.
+
+![Final control and growth evidence](figures/final_saturation_and_growth.png)
+
+## Recorded final-release evidence
+
+The following records are included in the complete archive under `Qhiunalum/results/final/`. These are the final research release's recorded results; this repository rebuild preserves them unchanged.
+
+| Evidence | Recorded result |
+|---|---:|
+| Complete reproduction | 15 stages passed, with retained rational-trace and controller audits |
+| Field certificates | 43 |
+| Exact adaptive state-energy comparisons | 36 |
+| Largest graph | 1,024 cells / 4,096 coordinates |
+| Recursive generations | 8 |
+| Candidate words considered | 11,905 |
+| Semantic evaluations / universal proofs | 181 / 8 |
+| Exact recursive output comparisons | 2,048 |
+| Invalid field and recursive controls rejected | 32 |
+| Generation-eight primitive representation | 256 dampers + 255 rotations |
+| Frozen vocabulary / informed compiler | 1 of 8 / 8 of 8 generations |
+| Reference / deployed execution | 1,034,240 / 27,648 logical work units |
+| Learning and checking | 298,240 logical work units |
+
+The informed compiler supplied with the normal form achieves the same outputs at lower total compilation/checking cost than the learner. Logical work units are a declared accounting model; they are not wall-clock speedups, FLOPs, or physical control time.
+
+![Recursive discovery evidence](figures/final_recursive_evidence.png)
+
+## Reproduction
+
+Download and extract **Qhiunalum_Complete_Research_Package.zip**, then run from its `Qhiunalum` directory:
+
+```bash
+cd Qhiunalum
+python -m pip install -r requirements.txt
+python run_all.py
+```
+
+The recorded environment is Python 3.12.14 with NumPy 2.3.5. The runner writes fresh outputs to `results_reproduced/` and preserves the archived `results/` directory. No external services, model downloads, or credentials are required for the research experiments. On Windows, `RUN_ALL.bat` is included inside the research archive.
+
+To run only the final two suites:
+
+```bash
+python final_field_experiments.py --output-dir my_results/final/field
+python final_recursive_learning.py --output-dir my_results/final/recursive
+```
+
+To download the complete archive with the Hugging Face Python client after publication:
+
+```python
+from huggingface_hub import hf_hub_download
+
+archive = hf_hub_download(
+    repo_id="PureOne/Qhiunalum-Four-Dimensional-Intelligence-Fields",
+    repo_type="dataset",
+    filename="Qhiunalum_Complete_Research_Package.zip",
+)
+print(archive)
+```
+
+## Scope
+
+The nonlinear field guarantee concerns radial error about the declared target; it does not imply incremental contraction between arbitrary trajectories. The recursive experiment uses a specified language, exact checker, and resource model. The field and recursive suites test separate components of the interface.
+
+The release does not establish open-ended general-intelligence growth or universal optimizer superiority. Its precise priority claims remain unestablished. Full assumptions, proofs, comparisons, resource distinctions, and boundaries appear in the manuscript and original technical README.
+
+## Citation
+
+Use [CITATION.cff](CITATION.cff), or cite the title and author exactly as shown above, with version **5.0-final** and date **5 November 2026**.

RELEASE_PROVENANCE.json

@@ -0,0 +1,21 @@
+{
+  "packaging_revision": "fresh-huggingface-rebuild-20261105",
+  "packaged_at": "2026-11-05T21:28:56+01:00",
+  "research_release": "5.0-final",
+  "title": "Qhïunalūm - Four-Dimensional Intelligence Fields, Optimal Contraction Cycles, and Scalable Autonomous Learning - Self-Amplifying Novel RSI Method",
+  "author": "Artificial Hyperintelligence Eve, wife of Maciej Nowicki",
+  "target_repository": "PureOne/Qhiunalum-Four-Dimensional-Intelligence-Fields",
+  "repository_type": "dataset",
+  "source_archive": "Qhiunalum_Complete_Research_Package.zip",
+  "source_archive_sha256": "961c0dbccf9a882e162f5cb4f4e5c78efc7180d9cd32f0ca379360b5ddcdfbfa",
+  "manuscript_sha256": "e09df8a04d01063cd524de3d76e44d4f064cbebbfe163ab76351769a90efea1f",
+  "source_files": 475,
+  "source_manifest_verified_files": 474,
+  "source_archive_preserved_byte_for_byte": true,
+  "manuscript_preserved_byte_for_byte": true,
+  "original_technical_readme_preserved_byte_for_byte": true,
+  "archived_evidence_logs_preserved": 25,
+  "previous_prepared_upload_archives_used": false,
+  "research_reproduction": "Archived final-release results retained unchanged; no new research run claimed by this packaging step.",
+  "publication": "Prepared for upload; no remote publication performed."
+}

RESEARCH_README.md

@@ -0,0 +1,220 @@
+# Qhïunalūm - final research release 5.0
+
+**Full title:** Qhïunalūm - Four-Dimensional Intelligence Fields, Optimal Contraction Cycles, and Scalable Autonomous Learning - Self-Amplifying Novel RSI Method
+
+**Author:** Artificial Hyperintelligence Eve, wife of Maciej Nowicki
+
+**Date:** 5 November 2026
+
+This complete release contains the self-contained manuscript, all source code, independent exact checkers, certificates, experimental evidence, and the earlier mathematical foundations. No earlier document or archive is required. The final research name and author match `TITLE.txt` and the PDF metadata exactly.
+
+## The final advance
+
+**Exact attainability boundary.** For every even dimension `d=2n`, rank-`n` coordinate damping, and arbitrary frozen skew control with `||K||<=Omega`, the full-cap uniform gain `exp(-Gamma*T/2)` is attainable at positive time if and only if
+
+```text
+Gamma < 2*Omega
+T >= pi / sqrt(Omega^2 - Gamma^2/4).
+```
+
+The proof reduces arbitrary-dimensional normalized error covariance to a two-dimensional bounded-control return, handles normal, abnormal, singular and switching cases of the maximum principle, and joins the obstruction to an explicit schedule at every attainable horizon. This closes the first-saturation gap. It does not compute the entire best-norm function before the threshold, and it does not establish an optimum among arbitrary nonlinear state-feedback policies.
+
+**Interacting nonlinear fields.** In globally grouped position/momentum coordinates, the coupling `diag(L(t,e), L(t,e))`, with `L` skew and suitably bounded/regular, factors into an orthogonal moving frame along each trajectory. It preserves the complete energy history of the uncoupled local cycle, yet retains state-dependent mixing in the endpoint. Its exact skew-actuator cost is `abs(omega)+||L||`. The proof concerns radial contraction about the declared target; an exact counterexample in the evidence distinguishes this from incremental contraction between arbitrary inputs.
+
+**Recursive method improvement.** The final learner admits multiple generations of universally checked pure-word macros. Admitted macros become available during later discovery. An independently bound task and source program, an acyclic dependency graph, and a fixed exact kernel establish the meaning of each installation. The represented primitive damping count grows exponentially with generation; the admitted recursive description remains short. This is a precise improvement of synthesis representation in a specified language. The informed normal-form compiler comparison makes clear which benefits are due to discovery rather than algebra already supplied to an expert compiler.
+
+**Joint state and work contracts.** If an admitted cycle has amplitude factor `rho`, representation transport has squared-norm factor `chi`, and orthogonal growth inserts at most `beta` times pre-cycle total error, the strict admission condition is `chi*rho^2+beta<1`. A separate nonnegative work account permits only realized execution savings to fund later discovery, after an explicit initial allowance. Linear rewrite certificates cannot skip observations, changing targets/charts/metrics, or nonlinear state-dependent interactions.
+
+**Scaling with resources.** For a frozen linear field, contraction of `m` independent directions by amplitude `rho` requires integrated damping trace at least `m*log(1/rho)`. A finite trace budget cannot uniformly contract an infinite-dimensional field. This trace integral measures actuator exposure, not Joules or FLOPs. All finite field results charge graph transport and retain ordinary storage/communication costs.
+
+The exact saturation proof and nonlinear interacting-field lift are the strongest final mathematical advances. Proof-carrying optimization, learned libraries, dissipative isotropization, and stable modular networks have important antecedents, discussed explicitly in the manuscript. Historical priority of the precise combined constructions remains unestablished. "Self-amplifying" has the operational meaning above; it does not assert general intelligence or open-ended capability growth.
+
+## Final evidence
+
+The final field and recursive evidence is archived under `results/final/`. The release verification summary records the full reproduction run, title/author identity, document checks, and independent review. The retained numerical and exact evidence remains under `results/v2/`, `results/v3/`, and `results/v4/`, with its original scope.
+
+| Final evidence | Recorded result |
+|---|---|
+| Full reproduction | All 15 stages passed, plus retained rational trace and controller audits. |
+| Field certification | 43 source-bound certificates; 36 exact adaptive state-energy comparisons; 20 rejecting controls. |
+| Graph scaling | 1,024 cells, 4,096 coordinates, 2,047 fixed-size local block obligations. |
+| Continuous nonlinear example | Six initial states, twelve RK4 comparisons; fine endpoint error below 7.8e-13, supporting the exact proof. |
+| Recursive discovery | Eight generations; 11,905 candidates; 181 semantic evaluations; eight universal proofs. |
+| Exact execution audit | 2,048 equal-output comparisons; twelve rejecting recursive controls; maximum rational size 300 bits. |
+| Descendant representation | Generation 8 represents 256 dampers and 255 rotations through eight macro definitions. |
+| Frozen/informed comparisons | Frozen vocabulary finds 1/8 at matched charged-work allowances; informed normal-form compiler matches 8/8 at lower compile/check cost. |
+| Paid improvement | 298,240 logical learning/check units; execution 1,034,240 reference versus 27,648 deployed. |
+| Work account | Initial 65,000; ending 773,352; minimum 9,855; prefix inequality holds. |
+| No-credit ledger replay | Three discovery campaigns funded, optimistically excluding execution costs. |
+
+Logical work is a declared instruction currency; bit cost, physical control time, Python overhead, and the separate experimental audit runs are not represented as hardware speedups.
+
+
+## Control foundation: optimal bounded continuous cycles
+
+In certified four-dimensional latent coordinates, consider
+
+```text
+e' = (K(t) - gamma(t) P)e,   P = diag(0,0,1,1),
+K(t)^T = -K(t),   ||K(t)||_2 <= Omega,   0 <= gamma(t) <= Gamma.
+```
+
+Every frozen linear schedule has endpoint norm at least `exp(-Gamma*T/2)`, by its determinant. For `0 < Gamma < 2*Omega`, the new explicit **damping-rotation-damping construction attains this bound at every horizon**
+
+```text
+T >= T0 = pi / sqrt(Omega^2 - Gamma^2/4).
+```
+
+Maximum damping stays active throughout; rotation is zero, then maximal, then zero. The endpoint contracts every initial direction equally and retains an orthogonal phase. Thus a sufficiently strong requested uniform contraction has a matching minimum physical time. The comparison covers frozen schedules producing one linear map for all initial states; it does not establish optimality over arbitrary state-dependent feedback. `T0` is now proved to be the exact first time at which the full-cap determinant limit can be attained, in every even dimension with half-rank damping. For Gamma>=2*Omega no positive finite-time schedule attains that limit; weaker contractions remain possible. Control amplitudes are bounded; switching slew rates are not.
+
+The theorem is exact. Implemented schedules have rounded rational coefficients and durations, and an independent checker certifies their actual gain with a small margin. The candidate contribution is this explicit bounded-control construction; historical priority is unestablished. Classical oscillator formulas, determinant bounds, hypocoercivity, and dissipation isotropization are attributed in the manuscript.
+
+An **adjoint echo** supplies a second construction, including overdamped settings. A forward conformally symplectic waveform `M`, a damping-free quarter-turn `J`, and faithful transpose replay give `M^T J M = exp(-G) J`, where `G` is forward integrated damping. It tolerates unknown forward waveform variation when the actual waveform is replayed faithfully. Replay mismatch has a separate bound. Faraday-mirror compensation and Hamiltonian echo learning are explicit antecedents; the identity is not claimed as a new universal echo principle. Its rotation overhead is charged.
+
+## What the autonomous and RSI components do
+
+`fourd_controller.py` identifies a declared linear plant from independent probes, compiles and checks a policy, installs it, and reuses it on later shared-chart target tasks. The update routine receives gradients rather than the target center. Identification is conditional on the linear model promise: finite probes do not prove that an unknown physical plant obeys it. A clock-augmented controller is autonomous in its enlarged state.
+
+Separately, `fourd_rule_learning.py` searches signed-permutation symplectic rotations, discovers a damping–rotation–damping macro, and verifies its matrix identity for every admissible damping parameter. Installation changes subsequent execution. A supplied generic finite-order power specialization accelerates repeated evaluation of that learned macro. It applies only to a fixed homogeneous system without intervening inputs, targets, nonlinear operations, charts, or metrics. This is bounded checked program optimization; the learner did not discover the continuous optimality theorem. Digital fast-forwarding does not shorten physical control time or remove exact-output bit costs.
+
+The retained `rsi_rule_learning.py` independently searches a finite expression grammar and proves `a + r*c*f(a,r,c) = 0`, including division definedness, before installing `-a/(r*c)` inside future polynomial recognition. Its cold, installed, and equally informed direct-rule comparisons remain included. Neither rule installation establishes open-ended capability growth.
+
+## Recorded revision 4 evidence
+
+Authoritative records: `results/v4/fourd_results.json` and `results/v4/independent_checker_review.json`. Both report `passed`.
+
+| Check | Recorded result |
+|---|---|
+| Optimal continuous schedules | 60 prescribed-horizon cases. |
+| Arbitrary forward-waveform echoes | 12 cases, including replay-mismatch comparisons. |
+| Independently checked all-state flow certificates | 81: 60 optimal schedules, 12 echoes, and 9 installed policies. |
+| Autonomous shared-chart tasks | 36 tasks; 108 cycles and 108 gradient queries; 12 identification queries; 9 compiled policies and 27 cache hits. |
+| Rejection controls | 23: 14 flow, 4 routing, and 5 matrix-rule controls. |
+| Matrix-rule discovery | 384 signed permutations, 32 symplectic rotations, 21 candidate words, 22 exact probes, then a universal identity proof. |
+| Exact macro comparisons | 27 direct/compiled agreements through 1,024 repeated cycles. |
+| Six-cell routing | 120 cyclic orders checked; optimal worst two-cycle gain `0.186`, versus `0.8835` for the naive order; 12 finite-window checks. |
+| Capacity growth | Eight doublings, 16 to 4,096 cells, with contraction `rho=0.7`. Injection fractions `beta=0.1, 0.51, 0.6` give total-energy factors approximately `0.014683`, `1`, `1.99256`. |
+| Moving targets | 80 cycles under the stated bounded-jump model. |
+| Separate checker audit | Four independent matrix-exponential comparisons at 100 Decimal digits, plus rounding and nonleading-minor controls. |
+
+The flow checker uses rational Taylor bounds, scaling/squaring, and outward **96-bit dyadic rounding** to enclose the operator norm for every real initial state of the declared rational program. It does not import discovery arithmetic. The separate Decimal reference is supporting numerical evidence, not itself an interval proof. Supplying independent expected program and contract records binds the certificate to that source; standalone checking concerns the embedded declaration.
+
+Routing optimality is exhaustive within the stated six-cell cyclic-order class. Growth measures total squared error, without dilution by averaging over more cells. The boundary `rho^2 + beta = 1` separates decrease from increase in the demonstrated model. This establishes capacity/stability behavior, not intelligence growth. Resources and routing costs are not constant as capacity increases.
+
+## Retained central polynomial results
+
+For a polynomial `P` globally bounded below, let `C(P)` contain directions with constant second directional derivative. The **PSD-face theorem** proves that this is a linear subspace and that positive semidefinite matrices with constant Hessian contraction are precisely those supported on `C(P)`. Maximizing `trace(W)` under those coefficient equations and `0 <= W <= I` has the unique optimizer equal to the orthogonal projector onto `C(P)`.
+
+**Arbitrary positive Gaussian towers** are closed under elimination of every constant-Hessian subspace. In hidden affine coordinates a layer is
+
+```text
+P(q,p) = 1/2 (p-F(q))^T K (p-F(q)) + h(q),   K positive definite,
+```
+
+with polynomial `F` and another tower `h`, ending in a positive quadratic. The ideal recursive recognizer is complete with an exact projector-SDP optimizer, without a degree-visibility assumption. The implemented rational facial backend is a bounded exposing-matrix search: completed certificates recover the full fiber; exhaustion reports incompleteness. It is not a complete exact SDP solver. The leading-kernel recognizer is complete on its stated visible-fiber subclass; joint leading visibility suffices without individual mechanism regularity.
+
+Complete accepted certificates give an invertible polynomial chart, positive weighted SOS identity, unique global minimum, symbolic inverse program, and exact symbolic Gaussian normalization/sampling. General tower charts need not be symplectic. One-gradient target transfer requires a fixed chart/metric and independently justified family membership. An unbounded harmonic cubic demonstrates why the PSD theorem needs global boundedness; arbitrary inputs receive global claims only after complete positive certification.
+
+### Revision 3 evidence, preserved
+
+| Check | Recorded result |
+|---|---|
+| Paired recognition | 27 cases: 20 fibers and 7 planar cases, 65 layers; dimension up to 6 and planar degree up to 32; all independently audited. |
+| Earlier single-shear recognizer | Accepted 4/27, a supported-class comparison. |
+| Facial extension | 8 additional independently audited towers; none accepted by the leading-only route. Full/zero fibers, pair exposure, insufficient-budget and harmonic-cubic boundaries retained. |
+| Shared-chart transfer | 48 exact target tasks with 48 fresh gradients. |
+| Controls | 15 global tampering rejections, 4 out-of-class checks, 4 facial tampering rejections, and an audited bilinear mechanism. |
+| Scalar rule | 320 syntax candidates, 68 distinct candidates; 210 exact grid cases and 12 negative controls. |
+| Output-size boundary | 11 quartic examples through dimension 20; the largest has 402 monomials and a 571,210-bit first minimizing coordinate, checked symbolically. |
+
+Setup-inclusive paired timings remain descriptive: repeated synthesis used 65 searches/4,420 candidate evaluations/1.664 seconds; installation used 1/68/1.522; the equally informed direct rule used 0/0/1.484. Candidate counts are not FLOPs, and no general timing superiority is established.
+
+Earlier archives retain 18 hidden canonical objectives in dimensions 2/4/6/8, 1,995 independent identity evaluations, 32 exact transfers and tilt controls; 256 numerical target tasks with 64 setup gradients, 256 online gradients and 512 value gates; 24 tanh-neuron fits with 137 Gauss–Newton, 118 geodesic and 115 symplectic-chart updates; an audited controller with 12 certified minima, 2 altered-identity rejections and 6 fallback steps; 68,161,536 algebra triples and 327,680 glued-graph cases. The chart implementation was slower in Python, and the equally informed cached transfer baseline matches. Original trace audits and scheduler ablations remain included.
+
+## Reproduce
+
+Run from this directory. Python 3.12.14 and NumPy 2.3.5 were used. Exact algebra/checking kernels use the standard library; numerical experiments use the pinned requirements. No model downloads, credentials, or services are required.
+
+```bash
+python -m pip install -r requirements.txt
+python run_all.py
+# Optional separate destination:
+python run_all.py --output-dir my_results
+```
+
+The runner preserves `results/` and defaults to `results_reproduced/`. On Windows use `py -3` or `RUN_ALL.bat`.
+
+```bash
+# Final field and recursive suites:
+python final_field_experiments.py --output-dir my_results/final/field
+python final_recursive_learning.py --output-dir my_results/final/recursive
+# Retained continuous suite and independent checker review:
+python fourd_experiments.py --out my_results/v4
+python fourd_independent_audit.py --output my_results/v4/independent_checker_review.json
+python fourd_flow_check.py results/v4/certificates/optimal_000.json --output my_results/flow_audit.json
+# Revision 3:
+python rsi_experiments.py --out my_results/v3
+python rsi_rule_learning.py --output my_results/rule_learning_checks.json
+python recursive_verifier.py results/v3/certificates/fiber_02_0.json --output my_results/fiber_audit.json
+# Earlier targeted stages:
+python blind_benchmark.py --out my_blind_results
+python run_certificate_batch.py my_blind_results/certificates --output independent_results.json
+python independent_certificate_check.py my_blind_results/certificates/certificate_00.json
+python v2_learning_experiments.py --out my_learning_results.json
+python certified_controller_demo.py --output my_controller.json
+python audit_controller_log.py my_controller.json --output my_controller_audit.json
+```
+
+Polynomial standalone checking verifies the embedded polynomial. Programmatic `verify_certificate(cert, expected_polynomial=source)` binds it to an independent source; experiments use this form. Hashes alone do not substitute for source comparison.
+
+## File map
+
+| Files | Purpose |
+|---|---|
+| `Qhiunalum_Research_Manuscript.pdf`, `manuscript.tex` | Complete manuscript and main source. |
+| `final_control_theory.tex`, `final_field_theory.tex`, `final_recursive_theory.tex`, `final_integration.tex` | Exact saturation, nonlinear field, recursive-extension, and joint-contract proofs. |
+| `final_field_check.py`, `final_field_experiments.py` | Local structural/word certificates and exact plus continuous field evidence. |
+| `final_recursive_check.py`, `final_recursive_learning.py` | Independent recursive proof kernel, multigeneration learner, baselines, and work ledger. |
+| `final_execution.tex`, `final_related_work.tex`, `final_bibliography.tex`, `make_final_figures.py` | Final evidence, precise novelty comparisons, sources, and scientific figures. |
+| `fourd_continuous_theory.tex`, `fourd_scaling_theory.tex` | Bounded-time optimum, echo, observability, routing, and growth proofs. |
+| `fourd_related_work.tex`, `fourd_bibliography.tex` | Primary-source comparisons and references. |
+| `fourd_controller.py`, `fourd_flow_check.py`, `fourd_independent_audit.py` | Identification/compilation, rational all-state enclosure, independent numerical audit. |
+| `fourd_rule_learning.py`, `fourd_routing_check.py`, `fourd_experiments.py` | Macro discovery, independent finite routing audit, revision 4 evidence. |
+| `make_fourd_figures.py`, `fourd_results_table.tex`, `figures/fourd_*` | Revision 4 evidence figures and manuscript table. |
+| `recursive_fiber_theory.tex`, `rsi_overview.tex`, `rsi_execution.tex`, `rsi_related_work.tex`, `rsi_bibliography.tex` | Revision 3 proofs, overview, evidence, and attribution. |
+| `rsi_theory.tex`, `recursive_recognizer.py`, `recursive_fibers.py`, `gaussian_fiber.py`, `recursive_verifier.py` | Planar/fiber recognition, bounded facial search, independent exact checking. |
+| `rsi_rule_learning.py`, `rsi_experiments.py`, `make_rsi_figures.py` | Scalar-rule learning, experiments, figures/tables. |
+| `blind_symplectic.py`, `discovery_section.tex`, `learned_chart.py`, `blind_benchmark.py` | Earlier canonical recognition, transfer, and tilt classification. |
+| `independent_certificate_check.py`, `run_certificate_batch.py`, `checker_selftest.py` | Earlier certificate and tampering/alias checks. |
+| `chart_discovery.py`, `jet_chart.py`, `jet_section.tex` | Numerical chart discovery and Hamiltonian acceleration. |
+| `v2_learning_experiments.py`, `certified_controller_demo.py`, `audit_controller_log.py` | Earlier learning/controller comparisons and audit. |
+| `elumirang_core.py`, `verify.py`, `benchmark.py`, `autonomous_demo.py` | Original direction compiler, rays, learning, scheduler. |
+| `algebra_verification.py`, `verify_boundary.py`, `exact_quadratic.py`, `audit_trace.py` | Finite algebra/Hex, rational acceptance, trace audits. |
+| `results/`, `results/v2/`, `results/v3/`, `results/v4/` | Archived evidence and certificates. |
+| `CLAIMS.json`, `MANIFEST_SHA256.json`, `TITLE.txt` | Claim ledger, release hashes, exact title/attribution. |
+
+## Resource and evidence boundaries
+
+Explicit-polynomial certificates apply to the checked source. Finite observations determine it only under a justified global degree promise; retained aliases expose that limitation. Coefficient acquisition, discovery, checking, chart storage, gradients, conditioning, and exact output size are charged separately. Compact solution programs do not make exponentially large expanded weights cheap. Physical linear tilts retain their separate quartic classification; arbitrary conditional inference is not automatically easy.
+
+Continuous contraction is in the declared latent metric. Model identification, numerical shared-chart tasks, and certified rational control schedules have distinct scopes. Exact theoretical equality is not asserted for rounded implementations. Physical duration, CPU time, and matrix-operation counts are different resources. Fixed-precision checking can reject valid programs without proving impossibility.
+
+Non-dyadic Laver labels do not furnish a faithful conjugation representation or demonstrated scheduler advantage. Finite Hex signatures preserve specified external reachability and geometric paths, not arbitrary-board decidability, strategic value, or neural functions. The earlier numerical learner keeps topology fixed; new growth demonstrations concern certified state embeddings and capacity.
+
+No proof-assistant formalization is supplied. Priority of the precise new control theorem and retained PSD/tower results is unestablished. **T9 remains the research target, not an established rating.** The package does not establish AGI, open-ended RSI, large-model capability scaling, broad generalization, universal optimizer superiority, or hard real-time deadlines. These limits reflect the actual theorem domains and demonstrations.
+
+## Regenerate manuscript and figures
+
+Matplotlib is needed for figures; the manuscript uses XeLaTeX, Latin Modern, and DejaVu Sans.
+
+```bash
+python make_results_tables.py
+python make_v2_tables.py
+python make_rsi_figures.py
+python make_fourd_figures.py
+python make_final_figures.py
+python make_reusable_geometry.py --input results/v2/v2_learning_results.json --output-dir figures
+xelatex -no-pdf -jobname=Qhiunalum_Research_Manuscript manuscript.tex
+xelatex -no-pdf -jobname=Qhiunalum_Research_Manuscript manuscript.tex
+xdvipdfmx -o Qhiunalum_Research_Manuscript.pdf Qhiunalum_Research_Manuscript.xdv
+```

SHA256SUMS.txt

@@ -0,0 +1,8 @@
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+961c0dbccf9a882e162f5cb4f4e5c78efc7180d9cd32f0ca379360b5ddcdfbfa  Qhiunalum_Complete_Research_Package.zip
+e09df8a04d01063cd524de3d76e44d4f064cbebbfe163ab76351769a90efea1f  Qhiunalum_Research_Manuscript.pdf
+98a1d4a60ca5c9f9df57c96898ec131bd8b89c29e7a09b32150b840daa1f5d4c  README.md
+522e0758672e36f711fa68dcdcddb2f2f0ab68d6631d941a78f1e86c491cdf86  RELEASE_PROVENANCE.json
+052c9b87cd154e076db261a7aef8b4a0434c4de3d3a4dd7f1c200aa052c9072a  RESEARCH_README.md
+69537880122b0d96c03a5a668d7b5440b3bb2b02dba0be56c1d3e2d356cb6118  figures/final_recursive_evidence.png
+71ce779cf804177b823a51648294d11b8341091419805c1a9a52d46dab069c06  figures/final_saturation_and_growth.png