paper

ForgettingOT: Certified Speculative Batching from Sinkhorn's Projective Forgetting

arXiv:2607.24741

Abstract

Positive two-marginal entropic optimal transport is solved by a nonlinear, positive, order-preserving, homogeneous Sinkhorn map. After quotienting the dual scaling gauge, we show that the active eigenmode of the fixed-point Jacobian , generically , controls the strict correction tail. The projective-residual ratio converges to this mode, and the additional certified cycles required for tolerance scale as . ForgettingOT turns this nonlinear Perron--Frobenius fact into a certified executor for streams of related Sinkhorn problems. A computable projective variation in the marginals and kernel bounds the carry residual, while a verified contraction gives candidate repair depth. A window theorem converts these depths and the audit grid into bounds on packed work, collective rounds, overshoot, and fallback. Empirical tail estimates allocate work but never authorize release; current-instance certificates or measured marginal residuals do so, with ordinary Sinkhorn as fallback. On 15 FP64 A100/OTT-JAX cells, the observed quotient slow-mode ratio agrees with to . On controlled four-A100 streams, the complete executor is -- faster than sequential soft -transform warm starts, with 30/30 paired wins and no violations of the marginal tolerance. Eight-A100 support-4096 streams give -- wall-time speedup and -- fewer vector-collective rounds. The outer executor composes with target-preserving Sinkhorn accelerators; a changed map or approximate target needs a contraction or error bridge before inheriting the repair-depth bound.

18 pages, 5 figures, 9 tables. Major revision: adds a variation-dependent nonlinear Perron-Frobenius work and communication analysis, expanded 8-A100 single-node experiments, and compatibility analysis with modern Sinkhorn accelerators

ForgettingOT: Certified Speculative Batching from Sinkhorn's Projective Forgetting · wovepaper