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The Lanczos algorithm for matrix functions: a handbook for scientists

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arxiv 2410.11090 v1 pith:O5NF6B3Z submitted 2024-10-14 math.NA cs.DScs.NA

classification math.NAcs.DScs.NA
keywords functionsmatrixlanczoslanczos-basedmethodsalgorithmarithmeticbeen
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Lanczos-based methods have become standard tools for tasks involving matrix functions. Progress on these algorithms has been driven by several largely disjoint communities, resulting many innovative and important advancements which would not have been possible otherwise. However, this also has resulted in a somewhat fragmented state of knowledge and the propagation of a number of incorrect beliefs about the behavior of Lanczos-based methods in finite precision arithmetic. This monograph aims to provide an accessible introduction to Lanczos-based methods for matrix functions. The intended audience is scientists outside of numerical analysis, graduate students, and researchers wishing to begin work in this area. Our emphasis is on conceptual understanding, with the goal of providing a starting point to learn more about the remarkable behavior of the Lanczos algorithm. Hopefully readers will come away from this text with a better understanding of how to think about Lanczos for modern problems involving matrix functions, particularly in the context of finite precision arithmetic.

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  1. Faster Linear Algebra Algorithms with Structured Random Matrices

    cs.DS 2025-08 accept novelty 8.0 of 10

    Randomized sketching needs only the new OSI property, not the full subspace embedding, and multiple structured matrices satisfy it with near-optimal cost.

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