Quadratically Regularized Optimal Transport: Localization Bounds and Affine Case Analysis

• URL: http://arxiv.org/abs/2605.24644v2
• Date: Tue, 26 May 2026 07:42:35 GMT
• Title: Quadratically Regularized Optimal Transport: Localization Bounds and Affine Case Analysis
• Abstract summary: We show that the support of the QOT cannot concentrate around the Monge graph faster than order $varepsilonfrac1d+2$ in the directed Hausdorff distance.<n>We derive a sharp pointwise tube bound of order $varepsilonfrac1d+2$ by reducing the problem to self-transport and applying recent self-transport sparsity results.
• Score: 4.280045284812897
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quadratic regularization has emerged as a potential alternative to the popular entropic regularization in computational optimal transport, offering the theoretical advantage of producing sparse couplings through its hinge density structure. Despite recent progress in one-dimensional settings and general upper bounds, fundamental questions about the localization rate of QOT optimizers around the Monge coupling have remained open. In this work, we establish a general lower bound showing that the support of the QOT optimizer cannot concentrate around the Monge graph faster than order $\varepsilon^{\frac{1}{d+2}}$ in the directed Hausdorff distance, matching the conjectured optimal exponent under standard regularity assumptions in \citet{wiesel2025sparsity}. We also show that the QOT value gap controls the mean-squared deviation $\mathbb E_{π_\varepsilon}\|y-T(x)\|^2$ by the scale of $\varepsilon^{\frac{2}{d+2}}$. As a corollary, in the affine Brenier regime, which includes Gaussian-to-Gaussian transport, we derive a sharp pointwise tube bound of order $\varepsilon^{\frac{1}{d+2}}$ by reducing the problem to self-transport and applying recent self-transport sparsity results. Finally, we validate our theoretical bound with a synthetic experiment in high-dimensional settings.

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