Verification record · AUDIT-DS-NONCENTERED-GLOBAL-BASIN-TRANSFER
Publication-grade audit of the DS18 exact off-(L) basin and empirical transfer
Verification recordpublication: internalno direct precedent found
Statement
Independent adversarial audit of DS-NONCENTERED-GLOBAL-BASIN-TRANSFER. Verdict: verified with hardened assumptions. The population optimum, its uniqueness a.s. up to labels and null sets, quantitative strict isolation in decision distance, the almost-sure transfer of every sequence of exact finite global optimizers on one selection-independent probability-one event, finite ordinary one-point exchange stability, and the fixed margins (1/4, 1/4, 1/2) all survive. Five hardenings: (H1) the proof no longer imports the (L)-conditioned DS15 Lemma 3 and Proposition 5, which DS18 cited outside their registered hypothesis set, and proves the scalar uniqueness, rigidity and consistency steps for this law directly; (H2) the in-bin DS9 feasibility convention is named, and a zero binned nuisance block is shown to force sum_i S_lambda_i = 0 and hence to be null under the law, so regularity is a.s. vacuous while remaining load-bearing off that null set; (H3) uniqueness is a.s. up to labels and null sets, with the half-open reference labeling stated; (H4) the probability-one event is exhibited explicitly and the transfer is given a computable finite-N form P_N(z != q*) <= 3 Delta_N / eta + boundary band mass with Delta_N = v_hat_3 - Phi_hat(z*); (H5) DS14's (M3) is lambda_min(I_hat) >= kappa, not det/tr, which the margin triple needs. Two prior-art repairs: six direct antecedents already in the project bibliography were unlinked, and the uniqueness citation was mis-scoped to a strict-log-concavity result that Uniform[-1,1] fails.
Assumptions
source frozen at b1855c1 with the audit handoff at 7864348
the independent instrument does not import, extend or translate py/ds_noncentered_global_basin.py and does not import the scorequant library
exact claims recomputed in pure-stdlib fractions.Fraction; continuous-law quantities confirmed by a separate directed-rounding Decimal interval route and a seeded Monte-Carlo route
the audit does not re-audit inherited
DS-SCHUR,FI-QUANT-IDENTITYorFI-RANK-CEILING, and does not re-prove the audited DS14/DS15/DS17 nodes; it only checks that DS18's use of them matches their registered hypothesesno src/, public API, example or documentation-API change is authorized by this audit
independent publication-grade verification and hardening of the first exact off-(L) population-to-empirical transfer theorem
Where it stops
Bounded by
- CE-DS-NONCENTERED-SINGULAR-DESTINATION-001
An exact global optimum over regular (nonsingular-nuisance) finite labelings is one-point exchange-stable under ANY feasibility convention, so DS18.2's finite stability step needs no convention. FALSE off the null set: on this support-minimal N=4 table from the named off-(L) law, both exact global regular optima reach the single nuisance-singular labeling by one admissible relocation whose DS11 pseudo-inverse value exceeds the regular optimum by exactly 1/96. The in-bin (DS9) convention -- singular destinations are infeasible -- is therefore load-bearing and must be named. This does not refute DS18, whose law makes such tables null.
Closest prior work
- Kieffer (1983)Uniqueness of locally optimal quantizer for log-concave density and convex error weighting function
- Mease, Nair (2006)Unique optimal partitions of distributions and connections to hazard rates and stochastic ordering
- Pollard (1981)Strong Consistency of K-Means Clustering
- Rakhlin, Caponnetto (2006)Stability of K-Means Clustering
- Telgarsky, Vattani (2010)Hartigan's Method: k-means Clustering without Voronoi
- de Castro, Dorigo (2019)INFERNO: Inference-Aware Neural Optimisation
Nearest prior work
- Fisher (1958)On Grouping for Maximum Homogeneity
- Silvey (1978)Optimal design measures with singular information matrices
- Sabin, Gray (1986)Global convergence and empirical consistency of the generalized Lloyd algorithm
- Serinko, Babu (1992)Weak limit theorems for univariate k-mean clustering under a nonregular condition
- Graf, Luschgy (2000)Foundations of Quantization for Probability Distributions
- Venkitasubramaniam, Tong, Swami (2006)Score-Function Quantization for Distributed Estimation
- Liu, Pages (2020)Convergence rate of optimal quantization and application to the clustering performance of the empirical measure
Why each source is not this result: the search records
Nearest sources, checked 31 August 2026
Relationships
Evidence references
Reviewed inputs and supporting evidence; these are not proof prerequisites.
- Exact off-class global basin transfers to empirical exchange-stable optimaDS-NONCENTERED-GLOBAL-BASIN-TRANSFER
- Variational form of the profiled objectiveDS-PROFILED-VARIATIONAL
- Margins dichotomy at global finite Ds optima (conditionally centered laws, scalar nuisance)OPEN-DS-MARGINS-AT-OPTIMA
- Inhabitation reduces to a scalar root equation per lawDS-STABLE-BASINS-FIXED-POINT-GATE
- Conditional finite-to-population Ds bridgeOPEN-DS-FINITE-POP-BRIDGE