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synthetic-data
mathematical-proofs
system-identification
inverse-problems
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| # Claim ledger | |
| This ledger separates mathematical derivation, numerical checking, historical originality, and physical validation. None substitutes for another. | |
| | ID | Exact claim | Location | Evidence | Boundary | | |
| |---|---|---|---|---| | |
| | C1 | A finite mixed-clock cost frame identifies an observable linear model and its preparation metric up to similarity. | Theorem 5; Lemma 4; Propositions 2-3 | Full proof; 30 synthetic reconstructions; rational finite-shift certificate | Dimension bound; exact quadratic full preparation; ideal real thresholds and clocks | | |
| | C2 | All singleton limits can coincide while joint constraints differ; unbounded frequencies create arbitrarily close aliases. | Proposition 7; Theorem 8 | Explicit rotations; branch and near-alias datasets | Different information interfaces, not equally informed algorithms | | |
| | C3 | Kernel, rank, transition, local generator, and prediction errors admit explicit bounds. | Proposition 9; Corollary 10 | Full proof; 120 noise cases | Rank gap, calibrated support errors, principal-log branch and local radius | | |
| | C4 | Principal-cost exponents equal twice the observability depths. | Theorem 11 | Full factorization proof; two chain designs | Fixed observable model and metric; distinct scaled times; asymptotic limit | | |
| | C5a | Detecting the last state of an n-chain requires squared-support precision of power epsilon^(2(n-1)). | Theorem 12 | Matching exponent upper/lower arguments | Fixed chain pair, normalized directions, model-dependent constants | | |
| | C5b | Under independent Gaussian support noise, the two-hypothesis query count has power epsilon^(-4(n-1)). | Theorem 13 | KL lower bound and exact Gaussian test; 96,000 trials | Known chain pair; fixed variance and support-oracle assumptions | | |
| | B1 | Full joint feasible subspace already determines dynamics. | Proposition 6 | Full proof | Cost values are not essential to exact generator recovery in this class | | |
| | E1 | Cost reconstruction matches a direct exact-kernel baseline. | Experiment section; exact_reconstruction.csv | Numerical tie to rounding accuracy | No acquisition-efficiency or performance advantage | | |
| | N1 | First theorem of its kind in history | No supporting evidence | **Unestablished** | Do not claim | | |
| | P1 | New physical law or new physical phenomena | No physical validation | **Unestablished** | The model is stipulated | | |
| | G1 | Arbitrary physical-model reconstruction | Open program | **Not proved** | No universal theorem | | |
| Theorem numbers include the initial definition and propositions. “Full proof” means a written derivation, not proof-assistant verification or external review. | |
| ## Proof review performed | |
| Checked these potential failure points explicitly: | |
| 1. A mixed-clock rank plateau implies inverse-clock invariance by finite-dimensional injectivity. | |
| 2. Two irrationally related exponentials determine the continuous group by density, including repeated eigenvalues. | |
| 3. The limiting reconstruction is not advertised as a stable finite-precision algorithm. | |
| 4. Cost data identify a metric and similarity class, not hidden factors or named microscopic variables. | |
| 5. A near-identity clock map alone does not identify the logarithm branch. | |
| 6. The short-time leading matrix is full rank by polynomial interpolation and injectivity on each filtration increment. | |
| 7. Principal task eigenvectors can change with time scale. | |
| 8. The deterministic midpoint oracle works for every normalized query, including adaptive queries. | |
| 9. The Gaussian lower bound handles adaptive histories through the chain rule. | |
| 10. All rank-gap and model-dependent-constant assumptions remain explicit. | |
| This is internal review. External mathematical review remains needed before treating the claims as independently validated. | |
| ## Version 2 extension | |
| | ID | Claim | Location | Evidence and boundary | | |
| |---|---|---|---| | |
| | C6 | All-budget joint linear probes can fail to determine even observable state dimension | Proposition 14 | Exact circle/disk construction; standard convexification fact | | |
| | C7 | Quadratic mismatch graphs determine a compact nonlinear flow and cost up to conjugacy | Theorem 15 | Written proof; assumes embedding, full preparation and infinite exact data | | |
| | C8a | Finite-grid Hausdorff bound and sharp square-root noise exponent | Theorem 16 | Matching exponent bounds; six grid cases; disk/annulus indistinguishability | | |
| | C8b | Graph geometry controls map error on an aligned domain | Proposition 17 | Written elementary Lipschitz argument | | |
| | C8c | Anchored signed losses recover the next state and bound drift error | Proposition 18 | Written proof; 76,800 losses; exact anchors and shared timing assumption | | |
| | C9 | The oscillator has an explicit delay embedding and no finite linear realization with linear readout | Proposition 19 | Strict derivative and Vandermonde arguments; separate ODE integration check | | |
| | B2 | An information-equivalent conditional-response observer ties the quadratic readout | Nonlinear discussion | Losses algebraically encode the response; no information advantage | | |
| Internal review checked: compact zero sets; single-valued graph through embedding; complete-flow inverses; dense signed times; cost recovery from nested sublevels; both directed grid distances; all-center midpoint lower bound; common-domain requirement; correct factor four in loss differences; shared timing; monotone delay coordinate; and the explicit linear-readout restriction. | |
| The six new statements have written proofs. No general theorem has proof-assistant verification or external peer review. Their historical originality remains unestablished. | |