Numerical estimation of the eigenvalue problem with stochastic density function based on quasi-Monte Carlo method

The expectation value of the least eigenvalue of the Helmholtz equation with stochastic density function is investigated. The density function is assumed to admit series expansion, where the stochastic variables and the physical variables are separated. By truncating the density function to a finite dimension, the finite element (FE) method is applied to solve the eigenvalue problem. The finite-dimensional integral is approximated by quasi-Monte Carlo (QMC) method. The uniform bounds of the FE errors of the least eigenvalue and the least eigenfunction are proved. Detailed study of the bounds of the derivatives of the least eigenvalue and the least eigenfunction with respect to the stochastic variables are provided. The total truncation-FE-QMC error is derived. The numerical example is conducted to verify the estimation of the total truncation-FE-QMC error.

Publication Details

Journal
International Journal of Computational Methods
Published
2026-03-24
DOI
https://doi.org/10.1142/s021987622650026x
Primary Topic
Mathematical Approximation and Integration
Type
article
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article

Numerical estimation of the eigenvalue problem with stochastic density function based on quasi-Monte Carlo method

International Journal of Computational Methods
Mathematical Approximation and Integration
article

Numerical estimation of the eigenvalue problem with stochastic density function based on quasi-Monte Carlo method

article en

Abstract

The expectation value of the least eigenvalue of the Helmholtz equation with stochastic density function is investigated. The density function is assumed to admit series expansion, where the stochastic variables and the physical variables are separated. By truncating the density function to a finite dimension, the finite element (FE) method is applied to solve the eigenvalue problem. The finite-dimensional integral is approximated by quasi-Monte Carlo (QMC) method. The uniform bounds of the FE errors of the least eigenvalue and the least eigenfunction are proved. Detailed study of the bounds of the derivatives of the least eigenvalue and the least eigenfunction with respect to the stochastic variables are provided. The total truncation-FE-QMC error is derived. The numerical example is conducted to verify the estimation of the total truncation-FE-QMC error.

International Journal of Computational Methods
Openalex Percentile: Top 8%
Mathematical Approximation and Integration
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Numerical estimation of the eigenvalue problem with stochastic density function based on quasi-Monte Carlo method · International Journal of Computational Methods (2026) | TGRS Research Map | TGRS