We introduce an algorithm for estimating the trace of a matrix function f(A) using implicit products with a symmetric matrix A. Existing methods for implicit trace estimation of a matrix function tend to treat matrix-vector products with f(A) as a black-box to be computed by a Krylov subspace method. Like other algorithms for implicit trace estimation, our approach is based on a combination of deflation and stochastic trace estimation. However, we take a closer look at how products with f(A) are integrated into these approaches which enables several efficiencies not present in previously studied methods.
翻译:我们采用了一种算法来估计矩阵函数f(A)的痕量,使用含有对称矩阵表A的隐性产品估算矩阵函数f(A)的痕量。 现有的矩阵函数隐含追踪估计方法往往将f(A)的矩阵矢量产品作为黑箱处理,由Krylov子空间方法计算。 与其他隐含追踪估计的算法一样,我们的方法以通缩和随机跟踪估计相结合为基础。然而,我们更仔细地研究F(A)的产品如何融入这些方法,这些方法使得以前研究过的方法中不存在的几种效率。