Adaptive Multilevel Monte Carlo Method for Elliptic Eigenvalue Problem with Random Coefficients

Tao Gong

School of Mathematical Sciences, Guizhou Normal University, Guiyang Guizhou 550025, China.

Changlun Ye

School of Mathematical Sciences, Guizhou Normal University, Guiyang Guizhou 550025, China.

Hai Bi *

School of Mathematical Sciences, Guizhou Normal University, Guiyang Guizhou 550025, China.

*Author to whom correspondence should be addressed.


Abstract

This paper establishes for the first time an adaptive multilevel Monte Carlo algorithm for the elliptic eigenvalue problem with random coefficients. This algorithm integrates the traditional multilevel Monte Carlo method with the adaptive finite element method, distributing samples across multiple levels. We provide the complexity analysis of the algorithm and demonstrate through a series of numerical experiments that the proposed algorithm can improve computational accuracy and reduce computational costs.

Keywords: Multilevel Monte Carlo, adaptive mesh refinement, stochastic eigenvalue problem, complexity analysis


How to Cite

Gong, Tao, Changlun Ye, and Hai Bi. 2025. “Adaptive Multilevel Monte Carlo Method for Elliptic Eigenvalue Problem With Random Coefficients”. Journal of Advances in Mathematics and Computer Science 40 (10):1-23. https://doi.org/10.9734/jamcs/2025/v40i102055.

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