Quantum algorithms for solving a drift-diffusion equation: A complexity analysis

Fuente: arXiv
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Main Authors: Devereux, Ellen, Datta, Animesh
Format: Preprint
Published: 2025
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author Devereux, Ellen
Datta, Animesh
author_facet Devereux, Ellen
Datta, Animesh
contents We present four quantum algorithms for solving a multidimensional drift-diffusion equation. They rely on a quantum linear system solver, a quantum Hamiltonian simulation, a quantum random walk, and the quantum Fourier transform. We compare the complexities of these methods to their classical counterparts, finding that diagonalization via the quantum Fourier transform offers a quantum computational advantage for solving linear partial differential equations at a fixed final time. We employ a multidimensional amplitude estimation process to extract the full probability distribution from the quantum computer.
format Preprint
id arxiv_https___arxiv_org_abs_2505_21221
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Quantum algorithms for solving a drift-diffusion equation: A complexity analysis
Devereux, Ellen
Datta, Animesh
Quantum Physics
We present four quantum algorithms for solving a multidimensional drift-diffusion equation. They rely on a quantum linear system solver, a quantum Hamiltonian simulation, a quantum random walk, and the quantum Fourier transform. We compare the complexities of these methods to their classical counterparts, finding that diagonalization via the quantum Fourier transform offers a quantum computational advantage for solving linear partial differential equations at a fixed final time. We employ a multidimensional amplitude estimation process to extract the full probability distribution from the quantum computer.
title Quantum algorithms for solving a drift-diffusion equation: A complexity analysis
topic Quantum Physics
url https://arxiv.org/abs/2505.21221