Curvature, relative entropy, and global Sinkhorn convergence

Unrefereed research candidate. In one sentence: one Poincaré inequality on the source measure makes every full iteration of the exact continuous Sinkhorn algorithm shrink the entropic dual gap by the fixed factor CPL2/(CPL2+λ2), from the first step and for any target, so about (CPL2/λ2) log(1/ε) iterations suffice; the exponent 2 cannot be improved in general. Sinkhorn's algorithm (matrix scaling, iterative proportional fitting) is the standard solver for entropy-regularised optimal transport; smaller regularisation λ approximates unregularised transport better but slows the algorithm. Here CP is the source Poincaré constant and L bounds the source gradients of the cost. Theorem 1 transfers a uniform curvature bound on the semidual objective into a global relative-entropy inequality; Theorem 2 gives the Poincaré rate; Theorem 3 and Corollary 4 extend it to unbounded costs with compactly supported targets, including quadratic or bilinear cost with Gaussian or exponential-tailed sources and point-cloud targets (L becomes the target's Chebyshev radius R), for every λ. Corollary 5 turns the curvature estimate of Chizat, Delalande and Vaškevičius (CDV) into a global factor C/(C+λ), about 1/λ iterations, in their bounded-density and log-concave settings. Theorem 6 shows that no exponent below 2 is possible for a fixed source; Proposition 7 attains order λ2 uniformly over a bounded Poincaré class, Proposition 8 shows no single fixed absolutely continuous source attains it, and Corollary 9 shows the λ2 exponent of the Talagrand-inequality rates is also sharp. A practical stopping certificate bounds the gap by (1 + B/λ2) times the observed dual increase. Remark 5.2 states a conjecture on the eventual factor. Relation to prior work: Chiarini, Conforti, Greco and Tamanini (CCGT) already obtained the same rational rate under the stronger Talagrand inequality and Hessian bounds; the gains here are the weaker inequality, first-derivative hypotheses, validity for every λ and bounded initial potential, unbounded costs with compact targets, and the sharpness results. The mirror-descent route from a reverse-entropy inequality to a linear rate is that of Aubin-Frankowski, Korba and Léger; the curvature estimate in Corollary 5 is CDV's. S. Di Marino announced λ2 rates under Poincaré inequalities on both marginals; those proofs could not be inspected, so priority for the exponent is uncertain. The archive contains the manuscript (PDF and Markdown source), the proof outline, three floating-point check programmes with their outputs, a figure, earlier manuscript versions and diffs, the bibliography, the dated literature audit, a rating-free internal review summary, CI and SHA-256 sums. Assurance: written proofs; the scripts are floating-point checks of selected formulas, not proofs or interval certificates; internal AI-assisted review only (not peer review, independent reproduction or formal verification). Limits: exact algorithm on population (continuous) measures only, not empirical sources; unbounded targets with quadratic cost are not covered; constants are not sharp. Creator: Anonymous. Text and figures CC0-1.0; code MIT.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-03
DOI
https://doi.org/10.5281/zenodo.23929616
Primary Topic
Geometric Analysis and Curvature Flows
Type
preprint
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preprint

Curvature, relative entropy, and global Sinkhorn convergence

Zenodo (CERN European Organization for Nuclear Research)
Geometric Analysis and Curvature Flows
preprint

Curvature, relative entropy, and global Sinkhorn convergence

preprint en

Abstract

Unrefereed research candidate. In one sentence: one Poincaré inequality on the source measure makes every full iteration of the exact continuous Sinkhorn algorithm shrink the entropic dual gap by the fixed factor CPL2/(CPL2+λ2), from the first step and for any target, so about (CPL2/λ2) log(1/ε) iterations suffice; the exponent 2 cannot be improved in general. Sinkhorn's algorithm (matrix scaling, iterative proportional fitting) is the standard solver for entropy-regularised optimal transport; smaller regularisation λ approximates unregularised transport better but slows the algorithm. Here CP is the source Poincaré constant and L bounds the source gradients of the cost. Theorem 1 transfers a uniform curvature bound on the semidual objective into a global relative-entropy inequality; Theorem 2 gives the Poincaré rate; Theorem 3 and Corollary 4 extend it to unbounded costs with compactly supported targets, including quadratic or bilinear cost with Gaussian or exponential-tailed sources and point-cloud targets (L becomes the target's Chebyshev radius R), for every λ. Corollary 5 turns the curvature estimate of Chizat, Delalande and Vaškevičius (CDV) into a global factor C/(C+λ), about 1/λ iterations, in their bounded-density and log-concave settings. Theorem 6 shows that no exponent below 2 is possible for a fixed source; Proposition 7 attains order λ2 uniformly over a bounded Poincaré class, Proposition 8 shows no single fixed absolutely continuous source attains it, and Corollary 9 shows the λ2 exponent of the Talagrand-inequality rates is also sharp. A practical stopping certificate bounds the gap by (1 + B/λ2) times the observed dual increase. Remark 5.2 states a conjecture on the eventual factor. Relation to prior work: Chiarini, Conforti, Greco and Tamanini (CCGT) already obtained the same rational rate under the stronger Talagrand inequality and Hessian bounds; the gains here are the weaker inequality, first-derivative hypotheses, validity for every λ and bounded initial potential, unbounded costs with compact targets, and the sharpness results. The mirror-descent route from a reverse-entropy inequality to a linear rate is that of Aubin-Frankowski, Korba and Léger; the curvature estimate in Corollary 5 is CDV's. S. Di Marino announced λ2 rates under Poincaré inequalities on both marginals; those proofs could not be inspected, so priority for the exponent is uncertain. The archive contains the manuscript (PDF and Markdown source), the proof outline, three floating-point check programmes with their outputs, a figure, earlier manuscript versions and diffs, the bibliography, the dated literature audit, a rating-free internal review summary, CI and SHA-256 sums. Assurance: written proofs; the scripts are floating-point checks of selected formulas, not proofs or interval certificates; internal AI-assisted review only (not peer review, independent reproduction or formal verification). Limits: exact algorithm on population (continuous) measures only, not empirical sources; unbounded targets with quadratic cost are not covered; constants are not sharp. Creator: Anonymous. Text and figures CC0-1.0; code MIT.

Zenodo (CERN European Organization for Nuclear Research)
Geometric Analysis and Curvature Flows
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