On Symmetric Lanczos Quadrature for Stochastic Trace Estimation

Fuente: arXiv
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Main Authors: Li, Wenhao, Zhu, Shengxin
Format: Preprint
Published: 2025
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author Li, Wenhao
Zhu, Shengxin
author_facet Li, Wenhao
Zhu, Shengxin
contents A common approach to approximating quadratic forms of matrix functions is to use a quadrature rule derived from the Lanczos process, known as a Lanczos quadrature. Although symmetric quadrature rules are computationally favorable, it has remained unclear whether a symmetric Lanczos quadrature is practically feasible. In this work, we resolve this ambiguity by establishing necessary and sufficient conditions for the existence of symmetric Lanczos quadratures. We show that the sufficient condition can be met for a class of Jordan-Wielandt matrices by carefully constructing initial vectors with specific distributions for the Lanczos algorithm. Applying such a symmetric Lanczos quadrature to compute the Estrada index of bipartite or directed graphs ensures that the resulting stochastic trace estimators are unbiased. Furthermore, we observe that the variance of the quadratic form estimator based on the symmetric Lanczos quadrature is lower than that of the standard estimator.
format Preprint
id arxiv_https___arxiv_org_abs_2504_18913
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On Symmetric Lanczos Quadrature for Stochastic Trace Estimation
Li, Wenhao
Zhu, Shengxin
Numerical Analysis
65D32, 65F15
A common approach to approximating quadratic forms of matrix functions is to use a quadrature rule derived from the Lanczos process, known as a Lanczos quadrature. Although symmetric quadrature rules are computationally favorable, it has remained unclear whether a symmetric Lanczos quadrature is practically feasible. In this work, we resolve this ambiguity by establishing necessary and sufficient conditions for the existence of symmetric Lanczos quadratures. We show that the sufficient condition can be met for a class of Jordan-Wielandt matrices by carefully constructing initial vectors with specific distributions for the Lanczos algorithm. Applying such a symmetric Lanczos quadrature to compute the Estrada index of bipartite or directed graphs ensures that the resulting stochastic trace estimators are unbiased. Furthermore, we observe that the variance of the quadratic form estimator based on the symmetric Lanczos quadrature is lower than that of the standard estimator.
title On Symmetric Lanczos Quadrature for Stochastic Trace Estimation
topic Numerical Analysis
65D32, 65F15
url https://arxiv.org/abs/2504.18913