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Quantum vs. classical algorithms for solving the heat equation

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arxiv 2004.06516 v2 pith:BASP3T6F submitted 2020-04-14 quant-ph

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keywords classicalquantumalgorithmsheatsolvingapproachequationequations
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abstract

Quantum computers are predicted to outperform classical ones for solving partial differential equations, perhaps exponentially. Here we consider a prototypical PDE - the heat equation in a rectangular region - and compare in detail the complexities of ten classical and quantum algorithms for solving it, in the sense of approximately computing the amount of heat in a given region. We find that, for spatial dimension $d \ge 2$, there is an at most quadratic quantum speedup using an approach based on applying amplitude estimation to an accelerated classical random walk. However, an alternative approach based on a quantum algorithm for linear equations is never faster than the best classical algorithms.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Schr\"odingerization based quantum algorithms for the fractional Poisson equation

    math.NA 2025-05 conditional novelty 5.0 of 10

    A quantum algorithm combining the Caffarelli-Silvestre extension with Schrödingerization solves fractional Poisson equations with mesh dependence independent of dimension.

  2. A Quantum Path to Partial Differential Equations

    quant-ph 2026-07 accept novelty 3.5 of 10

    Lecture notes that organize quantum PDE algorithms around block encodings of finite-difference and finite-element operators, tracking discretization, preparation, normalization, postselection, and measurement costs.

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