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Quantum vs. classical algorithms for solving the heat equation
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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.
Forward citations
Cited by 2 Pith papers
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Schr\"odingerization based quantum algorithms for the fractional Poisson equation
A quantum algorithm combining the Caffarelli-Silvestre extension with Schrödingerization solves fractional Poisson equations with mesh dependence independent of dimension.
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A Quantum Path to Partial Differential Equations
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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