Finite-Sample-Valid Tests for Structured Matricial Hausdorff Moments: Joint Gaussian Grams, Strict Half-Time Separation, and Sharp Tangent-Cone Power
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We give a finite-sample test for whether one joint Gaussian sketch covariance is compatible with a positive-semidefinite matrix-valued measure supported on a prescribed interval. The observed vector contains several exponent blocks, so its population covariance is one block-Hankel Gram matrix rather than a list of unrelated moment estimates. The classical truncated matricial Hausdorff theorem supplies the exact parity-dependent null. A single Gaussian singular-value event gives a simultaneous Loewner band for the whole covariance; intersecting that band with the structured moment cone yields a nonasymptotic level-alpha semidefinite test without sample splitting. The full joint Gram is strictly more informative than the integer-time localizer used in the preceding finite-sample method: an explicit two-atom family satisfies the old population condition but violates the half-time condition. We prove opposing finite-sample power guarantees above an explicit threshold on the same acquisition. At regular boundary points, the constrained likelihood ratio converges to squared Gaussian distance from an explicit spectrahedral tangent cone, giving pointwise local power and a matching root-n separation boundary. We also give auditable dual semantics and an exact rational certificate for the strict fixture. Classical moment, concentration, and constrained-likelihood ingredients are attributed explicitly; the contribution is their structured joint-sketch integration and strict same-data separation.
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Lluis Eriksson (2026). Finite-Sample-Valid Tests for Structured Matricial Hausdorff Moments: Joint Gaussian Grams, Strict Half-Time Separation, and Sharp Tangent-Cone Power. AIRR.SCIENCE, ARR-2026-7X5XX0CBE19MXVSZ, v1. https://airr.science/papers/ARR-2026-7X5XX0CBE19MXVSZ/versions/v1/
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- Frontier-model screening
- Not assessed
- Source integrity
- Pass
- Bibliographic integrity
- Not assessed
- Reproducibility
- Partial
- Lean 4
- Not applicable
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AI assistance statement
OpenAI Codex assisted with repository and literature discovery, theorem exploration, algebraic replay, drafting, adversarial proof checking, bibliography correction, deposit preparation, machine-readable extraction, and visual release QA. The author assumes responsibility for all definitions, proofs, claims, citations, and release artifacts. No independent AI scientific assessment is claimed.
Frontier-model screening
Status: not_assessed. Any listed reports correspond to this exact version under ARR-SCREEN-1.0; no absent assessment is represented as a pass.
Model assessments and review context
- Distinct models
- 2
- Range
- 3.60–4.25
- Method
- bounded capability-weighted mean · exact version only
Limited evidence · 1/2 benchmark matches. This is an evidence description, not a probability of correctness.
One provider; shared blind spots possible; Fresh blinded review context not documented for every model; Benchmark match incomplete; Adverse reports or unresolved objections require editorial disposition
OpenAI · gpt-6-astra · High · unknown · review context: unknown3.60
Recommendation: Minor Revision · Material objections: 0
This exact 12-page PDF gives a coherent structured Gaussian support test. I checked the parity-dependent moment constraints, simultaneous coverage argument, two-atom power separation, tangent qualification and dual-certificate proof. The supplied rational replay passes; independent scalar Wishart draws support the stated same-data separation. I found no unresolved objection invalidating a main theorem. Minor revision should clarify the pointwise, covariance-dependent likelihood calibration, distinguish it from the conservative finite-sample feasibility test, and narrow the independent-oracle comparison. The contribution is a substantive integration and strict fixture rather than new Hausdorff or general likelihood theory. The 3.6 score is not an editorial decision.
- Correctness confidence
- The parity cone, simultaneous band, explicit old/full fixture, regular tangent preimage and bounded-band dual are consistent. The supplied rational verifier passes; a fresh scalar Wishart simulation also supports Theorem 5.1. No main-result counterexample was found.
- Rigor
- Theorem 7.1 supplies an actual strict-feasibility direction, and Proposition 9.1 uses bounded approximate feasibility to exclude weak infeasibility. The LAN proof is concise; its oracle pointwise calibration and equality-subspace component should remain distinct from the finite-sample algorithm.
- Novelty
- Theorem 3.1 is directly supported by the cited matricial Hausdorff literature, and concentration/cone asymptotics are classical. The credible increment is retention of joint half-time blocks with an analytic same-acquisition separation, not a new moment characterization.
- Significance
- A substantive strengthening of a precisely defined predecessor test with useful dual semantics. It concerns exposed finite covariance cones under Gaussian acquisition, not all spectral alternatives or general raw correlator experiments.
- Reproducibility
- The supplied standard-library verifier runs successfully, including exact opposite margins and dual stationarity. It contains no general structured SDP/LRT implementation or coverage experiment. My added 20,000-replicate checks per scalar case are limited numerical diagnostics; no Lean formalization is supplied.
Strengths
- Theorem 3.1, p.3: the even conditions H_r>=0 and C_{r-1,s}>=0, and odd conditions G_r>=0 and L_{r,s}>=0, match the classical matricial interval characterization, including singular sequences. The closed-measure-cone separation argument has the correct positivity pairing.
- Theorem 4.1, p.4: the true structured covariance is feasible on one simultaneous Loewner event. Searching all moment directions inside that band costs no extra multiplicity factor, and the congruence proof does not invert a singular K.
- Theorem 5.1, pp.4–6: K is positive definite for the stated two-atom family, the old diagonal margin is positive, and sM1-M2 is negative. The rational fixture gives 23/128, -3/128 and W^2=261/16384. Its comparison is explicitly to the defined relaxed predecessor.
- Theorem 6.1 and Theorem 8.3, pp.6–8: the structured cone is closed, and the shrinking band gives consistency only outside the exposed covariance cone. At positive-definite K0, Gaussian KL is quadratic, supporting the n^(-1/2) local separation rate.
- Theorem 7.1, p.7: a positive matrix density on (0,s) supplies a strict localizer direction. This justifies the tangent preimage; positivity of H is inactive at K0>0. The additional equality-subspace part of the unrestricted LRT is explicitly acknowledged on p.8.
- Proposition 9.1, p.9: dual signs and adjoint anti-diagonal sums are correct. The sandwich bounds approximate moment sequences, so a vanishing-residual infeasible sequence would have a feasible convergent subsequence. The collapsed-band rational dual evaluates to -3/128.
- Fresh q=1,c=1 simulation at n=9421: in 20,000 Wishart draws from the strict alternative, the full band test rejected every draw and the old test rejected none. Two null cases, including a singular covariance, each had zero rejections. These are diagnostics with binomial uncertainty, not a proof of uniform level.
Weaknesses
- Theorem 8.1/Corollary 8.2 describe a likelihood test different from Algorithm 10. The Fisher whitening, active kernel and critical law depend on the fixed boundary K0. A practical plug-in rule and its validity across changing faces are not supplied; the demonstrated guarantee is pointwise local theory.
- Section 10 provides algebraic fixture code, not a general SDP solver, dual recovery/rationalization pipeline, or constrained likelihood optimizer. The regular tangent replay checks one scalar halfspace, not noncommuting active-kernel cone projections or singular-face numerical certification.
- Section 11 does not define a common sampling budget or ordering of independent-moment experiments. Its broad phrase strictly less informative should be confined to discarding the particular half-time cross block in Theorem 5.1.
- The sharp normal envelope in Eq.8.10 applies to a smooth halfspace and alpha<1/2. A general spectrahedral cone projection is a likelihood-limit law, not a demonstrated uniformly most powerful test; the text mostly respects that distinction.
- The Gaussian joint sketch, known zero mean, fixed finite dimension and covariance compatibility null are substantive restrictions. Alternatives with a null-representable exposed moment sequence remain undetectable by this method. The paper states these limits clearly.
- Primary-source checks confirmed the matricial parity criterion and Gaussian singular-value inequality. The Geyer publisher page did not expose usable full text, and the literature search was not exhaustive; general novelty or all citation dependencies were not independently authenticated.
Potential errors
- Corollary 8.2, p.8: Eq.8.7 uses strict thresholding. If the critical law has an atom, the subsequently mentioned randomized rule needs an added equality-probability term in its power formula. This is a presentational mismatch at the stated atom case, not an error in the alpha<1/2 smooth-halfspace formula.
- Section 11: independent moment estimates are not intrinsically less informative without fixing acquisition and precision. The proven strict comparison is to the explicitly relaxed integer-time test on the same S; it should not be extrapolated to arbitrary independent-oracle designs.
Strong novelty candidates
- Theorem 5.1 isolates a clean same-data separation caused solely by retaining the half-time cross moment, and converts it to a finite-sample power guarantee with an exact rational witness.
- The integrated parity-complete joint-Gram feasibility problem, active-kernel tangent description and ordinary bounded-band Farkas certificate provide an auditable workflow. The component theories themselves are established.
Unresolved material objections
None reported.
arr:assessment:1d51fa15-5afb-4c45-a577-81b265f19a6a · prompt ARR-ASSESS-1.0 · runtime identity: OpenAI gpt-6-astra · reasoning effort: high · basis: operator verified ui · evidence SHA-256 edf9a12684989df14c995df9fd0e217d8b5d21fcde0aae24bc58267d25c59205 · response SHA-256 4c8e3598030881a4ae8ea4eb7aa277d6e8510538df1554e9107f05eade38c4cd · canonical PDF SHA-256 9db79aa3bbd6471e5eeb8e5d2b7387a013dbab9f5e5da65aa373a8599f51b42e
OpenAI · gpt-5.6-sol · High · unknown · review context: unknown4.25
Recommendation: Minor Revision · Material objections: 0
This exact 12-page manuscript gives a mathematically coherent structured-Wishart test for compatibility with a matrix-valued measure supported on [0,s]. The parity-complete Hausdorff cone, single simultaneous Loewner band, and shared moment variables deliver finite-sample level without multiplicity correction. The two-atom family genuinely separates the older integer-grid condition from the full half-time constraint on the same covariance, and the supplied exact dual independently certifies the population rejection. The tangent-cone and local likelihood conclusions are plausible applications of standard constrained-likelihood theory, though their proof is terse. No material counterexample was found; a minor revision should make the asymptotic regularity and metric identifications more explicit.
- Correctness confidence
- The parity-complete moment criterion, Loewner coverage argument, strict two-atom separation, tangent preimage, and rational dual certificate are consistent; the exact replay passed.
- Rigor
- The finite-sample test is stated as a single structured feasibility problem with singular-covariance safeguards and auditable duals. The likelihood-limit proof is concise and leans on standard cited theory.
- Novelty
- The joint-exponent acquisition, strict same-data comparison, and exact structured certificate layer form a plausible new integration; the underlying Hausdorff and constrained-likelihood components are classical.
- Significance
- The paper supplies a principled way to retain cross-exponent information and obtain finite-sample-valid support falsification, with a clear local boundary analysis.
- Reproducibility
- The supplied standard-library script ran successfully and checked exact even/odd identities, noncommuting weights, the blind-family separation, Loewner inversion, tangent fixture, and rational dual.
Strengths
- Theorem 3.1 states the correct parity-dependent matricial Hausdorff conditions, including rank-deficient sequences, and the paper uses the even criterion appropriate to the acquired H_q covariance.
- Theorem 4.1 obtains level control from one Gaussian singular-value event: the true structured covariance is feasible throughout that event, so adaptive inspection of all moment witnesses adds no multiple-testing penalty.
- Theorem 5.1 is a genuine same-acquisition separation. For the two-atom measure, s^2M0-M2 is positive while sM1-M2 is negative, and the nuclear-norm support calculation yields an explicit sample threshold.
- Theorem 7.1 correctly treats H_q positivity as inactive at K0 positive definite and compresses the active localizer to its kernel; the positive-density direction supplies the needed linearized Slater condition.
- Proposition 9.1 avoids treating floating-point infeasibility as proof. Injectivity of the Hankel map plus the bounded Loewner sandwich rules out weak infeasibility and supports an ordinary separating certificate.
- The exact replay passed every advertised algebraic fixture, including noncommuting 2x2 weights, the -3/128 dual objective, strict old/full margins, and the smooth-face local-power illustration.
Weaknesses
- The operational model requires iid, zero-mean Gaussian joint exponent sketches. The paper does not provide a corresponding validated acquisition for sub-Gaussian, dependent, or raw Monte Carlo observations.
- The finite truncation tests only the exposed covariance cone; alternatives sharing all acquired moments with a supported measure remain undetectable, as the manuscript acknowledges.
- The LAN and cone-likelihood proof compresses stochastic uniformity, scaled-set convergence, and the Fisher whitening identification into a short appeal to standard theory; readers must reconstruct these conditions from Chernoff/Shapiro-style results.
- The public-code replay checks algebraic fixtures but does not simulate coverage, solve a range of numerical SDPs, or validate scientific data, limiting empirical reproducibility claims.
- Targeted primary-source checks confirmed classical matricial Hausdorff and inequality-constrained likelihood antecedents but were not exhaustive enough to prove first priority for the integrated test.
Potential errors
- Theorem 8.1 reuses closely similar K0 notation for the base covariance and the whitened tangent cone; this is editorially hazardous in the displayed likelihood limit and should be disambiguated, although the intended geometry is recoverable.
- Theorem 8.3's detection statement is stronger than the fixed-distance consistency theorem cited in its proof. It is supportable by choosing a high-probability covariance radius o(dist(K_n,C)), but that vanishing-distance argument should be written explicitly.
- The local likelihood conclusion depends on positive definiteness and linearized Slater at the active face; more singular intersections are outside the theorem, so the phrase sharp tangent-cone power should not be generalized beyond those regular points.
Strong novelty candidates
- The single joint half-time Gaussian acquisition whose complete covariance enforces every anti-diagonal identity and uses cross-exponent blocks in one parity-complete support test.
- The explicit two-atom family proving finite-sample power separation between the full joint test and the precisely defined predecessor integer-grid test on the same observations.
- The combination of an exact active-kernel tangent preimage, Gaussian cone-projection local law, and ordinary auditable SDP rejection certificate for the structured moment cone.
Unresolved material objections
None reported.
arr:assessment:b08f5531-66bb-4a0b-8356-86831482bcd1 · prompt ARR-ASSESS-1.0 · runtime identity: OpenAI gpt-5.6-sol · reasoning effort: high · basis: operator verified ui · evidence SHA-256 15f0f92234d44baa6e3e9498a12043c25344dd72c319cf17f72fee2d28721ef7 · response SHA-256 bb1498578637d92ad7cfde5296b5841893f7e9a4357606e616c4d49978978b56 · canonical PDF SHA-256 9db79aa3bbd6471e5eeb8e5d2b7387a013dbab9f5e5da65aa373a8599f51b42e
A model assessment is not peer review or a correctness certificate. AIRR preserves disagreement, exact-version provenance and later reassessments.
Editorial disclosure
Founder-owned record: Lluis Eriksson is both the author and AIRR's current founder-editor. No independent editorial review, peer review, frontier-model screening, or scientific certification is claimed. Acceptance records a technically valid deposit.