A Fully Discrete Variational Approximation of Mather Measures and Sets
Abstract
We introduce a fully--discrete variational approximation of Mather measures and sets for Tonelli Lagrangians on the flat torus, together with a numerical procedure for approximating the entire Mather set. The scheme is based on a fully--discrete Lax--Oleinik operator with integer winding labels. We prove an O(τ+h/τ) error estimate for the critical value, convergence of critical solutions, and a finite-dimensional characterization of fully--discrete Mather measures. Accumulation points of the reconstructed minimizing measures are continuous Mather measures, while the supports satisfy complementary upper and lower convergence results involving the Mañé and Mather sets. To avoid the selection of only some minimizing components by exact discrete minimizers, we introduce a mass-threshold approximation based on almost-minimizing holonomic measures. This yields a finite-dimensional constrained optimization procedure designed to recover the whole Mather set.
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BibTeX
@misc{camilli2026fully,
title = {{A Fully Discrete Variational Approximation of Mather Measures and Sets}},
author = {Fabio Camilli and Cristian Mendico},
howpublished = {HAL},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.15281},
eprint = {2609.15281},
archivePrefix = {arXiv},
url = {https://hal.science/hal-05750883v1},
}
RIS
TY - UNPB
TI - A Fully Discrete Variational Approximation of Mather Measures and Sets
AU - Fabio Camilli
AU - Cristian Mendico
PY - 2026
DA - 2026/09/14
PB - HAL
DO - 10.48550/arxiv.2609.15281
UR - https://hal.science/hal-05750883v1
AB - We introduce a fully--discrete variational approximation of Mather measures and sets for Tonelli Lagrangians on the flat torus, together with a numerical procedure for approximating the entire Mather set. The scheme is based on a fully--discrete Lax--Oleinik operator with integer winding labels. We prove an O(τ+h/τ) error estimate for the critical value, convergence of critical solutions, and a finite-dimensional characterization of fully--discrete Mather measures. Accumulation points of the reconstructed minimizing measures are continuous Mather measures, while the supports satisfy complementary upper and lower convergence results involving the Mañé and Mather sets. To avoid the selection of only some minimizing components by exact discrete minimizers, we introduce a mass-threshold approximation based on almost-minimizing holonomic measures. This yields a finite-dimensional constrained optimization procedure designed to recover the whole Mather set.
ER -