English

Field Codes for Distributed Coupling Samplers and Certified Empirical Transport

Computational Complexity 2026-07-29 v1 Information Theory Machine Learning Optimization and Control

Abstract

In this paper, we formulate three communication tasks for empirical optimal transport: distributed coupling sampling, cost-evaluable coupling output, and scalar value-certified sampling. Our main result is a field-code compiler: any communicated transport field approximating an optimal empirical Monge map to error η\eta can be completed by sparse target-cell residuals into an exact-marginal value-certified sampler with scalar certificate W1(μ,ν)UW1(μ,ν)+2ΔW_1(\mu,\nu)\leq U\leq W_1(\mu,\nu)+2\Delta, where Δ\Delta is the public target-partition diameter. The certificate accuracy is controlled by Δ\Delta alone. The field error η\eta controls residual communication under a cell-margin condition; without a margin, η\eta alone does not bound residuals. We instantiate the compiler via adaptive local-affine and tensor-product spline codes with d(m+1)dbd(m+1)^db field bits in the spline case, plus residual lists charged separately. For lower bounds, exact Gap-Hamming embeddings prove certified output is hard, including a smooth cell-packing diffeomorphism family requiring Ω(ε2d/(d+4))\Omega(\varepsilon^{-2d/(d+4)}) communication for any cost-evaluable, cost-certified, or value-certified protocol. The same gadgets admit zero-communication samplers, formally separating the sampler and certificate-bearing output models. These results identify the transport field as the right communicated object whenever a field code is available, primarily as a residual-sparsity tool.

Cite

@article{arxiv.2607.27078,
  title  = {Field Codes for Distributed Coupling Samplers and Certified Empirical Transport},
  author = {Hung Mai and Hai Nguyen and Luong Doan and Ngoc Vu and Khanh Nguyen and Nhung Duong and Tuan Do},
  journal= {arXiv preprint arXiv:2607.27078},
  year   = {2026}
}