利用黑盒查询插值参数化量子电路

IF 3 2区数学 Q1 MATHEMATICS, APPLIED

SIAM Journal on Scientific Computing Pub Date : 2024-09-13 DOI:10.1137/23m1609543

Lars Simon, Holger Eble, Hagen-Henrik Kowalski, Manuel Radons

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引用次数: 0

摘要

SIAM 科学计算期刊》，第 46 卷第 5 期，第 B600-B620 页，2024 年 10 月。摘要这篇文章的重点是通过（三角）多项式插值，为参数化量子电路开发经典代型。我们开发了两种构建此类代理的算法，并证明了性能保证。这些构造基于电路评估，而电路评估是黑盒的，即没有利用电路的具体结构。与利用特定电路特性的白盒评估相比，我们承认黑盒方法的局限性，但我们展示了黑盒方法可能证明是有益的应用场景。示例应用包括但不限于变分量子求解器的近似和贫瘠高原问题的缓解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Interpolating Parametrized Quantum Circuits Using Blackbox Queries

SIAM Journal on Scientific Computing, Volume 46, Issue 5, Page B600-B620, October 2024.
Abstract. This article focuses on developing classical surrogates for parametrized quantum circuits using interpolation via (trigonometric) polynomials. We develop two algorithms for the construction of such surrogates and prove performance guarantees. The constructions are based on circuit evaluations which are blackbox in the sense that no structural specifics of the circuits are exploited. While acknowledging the limitations of the blackbox approach compared to whitebox evaluations, which exploit specific circuit properties, we demonstrate scenarios in which the blackbox approach might prove beneficial. Sample applications include but are not restricted to the approximation of variational quantum eigensolvers and the alleviaton of the barren plateau problem.

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来源期刊

SIAM Journal on Scientific Computing 数学-应用数学

CiteScore

5.50

自引率

3.20%

发文量

209

审稿时长

1 months

期刊介绍： The purpose of SIAM Journal on Scientific Computing (SISC) is to advance computational methods for solving scientific and engineering problems. SISC papers are classified into three categories: 1. Methods and Algorithms for Scientific Computing: Papers in this category may include theoretical analysis, provided that the relevance to applications in science and engineering is demonstrated. They should contain meaningful computational results and theoretical results or strong heuristics supporting the performance of new algorithms. 2. Computational Methods in Science and Engineering: Papers in this section will typically describe novel methodologies for solving a specific problem in computational science or engineering. They should contain enough information about the application to orient other computational scientists but should omit details of interest mainly to the applications specialist. 3. Software and High-Performance Computing: Papers in this category should concern the novel design and development of computational methods and high-quality software, parallel algorithms, high-performance computing issues, new architectures, data analysis, or visualization. The primary focus should be on computational methods that have potentially large impact for an important class of scientific or engineering problems.