Open Access
2022 Quantitative homogenization in a balanced random environment
Xiaoqin Guo, Jonathon Peterson, Hung V. Tran
Author Affiliations +
Electron. J. Probab. 27: 1-31 (2022). DOI: 10.1214/22-EJP851

Abstract

We consider discrete non-divergence form difference operators in a random environment and the corresponding process – the random walk in a balanced random environment in Zd with a finite range of dependence. We first quantify the ergodicity of the environment from the point of view of the particle. As a consequence, we quantify the quenched central limit theorem of the random walk with an algebraic rate. Furthermore, we prove an algebraic rate of convergence for the homogenization of the Dirichlet problems for both elliptic and parabolic non-divergence form difference operators.

Funding Statement

XG is supported by Simons Foundation’s Collaboration Grant for Mathematicians # 852943. JP was partially supported by NSA grants H98230-15-1-0049 and H98230-16-1-0318. HT is supported in part by NSF grant DMS-1664424.

Acknowledgments

We thank two anonymous referees whose comments improve the presentation of our article. We thank Scott Armstrong and Charlie Smart for letting us know their new version [6] of [5] on arXiv. XG did the main part of his work while at the University of Wisconsin Madison. He thanks Professors Timo Sepäläinen and other colleagues at the UW for their hospitality and the supportive environment they created.

Citation

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Xiaoqin Guo. Jonathon Peterson. Hung V. Tran. "Quantitative homogenization in a balanced random environment." Electron. J. Probab. 27 1 - 31, 2022. https://doi.org/10.1214/22-EJP851

Information

Received: 14 January 2021; Accepted: 8 September 2022; Published: 2022
First available in Project Euclid: 3 October 2022

MathSciNet: MR4491712
zbMATH: 1500.35117
Digital Object Identifier: 10.1214/22-EJP851

Subjects:
Primary: 35J15 , 35J25 , 35K10 , 35K20 , 60G50 , 60K37 , 74Q20 , 76M50

Keywords: Berry-Esseen type estimate , non-divergence form difference operators , quantitative stochastic homogenization , Quenched central limit theorem , random walk in a balanced random environment

Vol.27 • 2022
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