偏微分方程的量子电路通过Schrödingerisation

IF 5.1 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY
Quantum Pub Date : 2024-12-12 DOI:10.22331/q-2024-12-12-1563
Junpeng Hu, Shi Jin, Nana Liu, Lei Zhang
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引用次数: 0

摘要

与经典计算相比,量子计算已经成为实现显着加速的有前途的途径,特别是在大规模PDE模拟中。主要的量子方法之一涉及利用哈密顿模拟,这只直接适用于Schrödinger-type方程。为了解决这一限制,Schrödingerisation技术已经开发出来,使用扭曲变换将一般线性偏微分方程转换为Schrödinger-type方程。然而,尽管Schrödingerisation技术的发展,解决一般偏微分方程的相应量子电路的显式实现仍有待设计。在本文中,我们提出了使用Schrödingerisation技术的通用pde量子算法的详细实现。我们提供了热方程的例子,以及迎风格式近似的平流方程,以证明我们的方法的有效性。复杂性分析也证明了这些算法在高维上优于经典算法的量子优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum Circuits for partial differential equations via Schrödingerisation
Quantum computing has emerged as a promising avenue for achieving significant speedup, particularly in large-scale PDE simulations, compared to classical computing. One of the main quantum approaches involves utilizing Hamiltonian simulation, which is directly applicable only to Schrödinger-type equations. To address this limitation, Schrödingerisation techniques have been developed, employing the warped transformation to convert general linear PDEs into Schrödinger-type equations. However, despite the development of Schrödingerisation techniques, the explicit implementation of the corresponding quantum circuit for solving general PDEs remains to be designed. In this paper, we present detailed implementation of a quantum algorithm for general PDEs using Schrödingerisation techniques. We provide examples of the heat equation, and the advection equation approximated by the upwind scheme, to demonstrate the effectiveness of our approach. Complexity analysis is also carried out to demonstrate the quantum advantages of these algorithms in high dimensions over their classical counterparts.
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来源期刊
Quantum
Quantum Physics and Astronomy-Physics and Astronomy (miscellaneous)
CiteScore
9.20
自引率
10.90%
发文量
241
审稿时长
16 weeks
期刊介绍: Quantum is an open-access peer-reviewed journal for quantum science and related fields. Quantum is non-profit and community-run: an effort by researchers and for researchers to make science more open and publishing more transparent and efficient.
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