基于监督学习和相关性的量子电路合成

IF 2.2 3区物理与天体物理 Q1 PHYSICS, MATHEMATICAL Quantum Information Processing Pub Date : 2024-05-24 DOI:10.1007/s11128-024-04426-6

Carolina Allende, André Fonseca de Olivera, Efrain Buksman

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引用次数: 0

摘要

这项工作介绍了如何使用变分量子电路对量子算子进行单元分解。通过使用经典优化技术并利用相关性和纠缠，变分量子电路能够转换各种量子算法，包括托福利门和随机单元。此外，还介绍了一个案例研究，在该案例中，这种分解方法被用于分解分类任务中出现的单元矩阵。

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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Synthesis of quantum circuits based on supervised learning and correlations

This work introduces the use of a variational quantum circuit in order to perform unitary decomposition of a quantum operator. By use of classical optimization techniques and exploiting correlations and entanglement, the variational quantum circuit is able to translate a wide range of quantum algorithms, including the Toffoli gate and random unitary. A case study is also presented, where this decomposition is used to decompose a unitary matrix arise from a classification task.

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来源期刊

Quantum Information Processing 物理-物理：数学物理

CiteScore

4.10

自引率

20.00%

发文量

337

审稿时长

4.5 months

期刊介绍： Quantum Information Processing is a high-impact, international journal publishing cutting-edge experimental and theoretical research in all areas of Quantum Information Science. Topics of interest include quantum cryptography and communications, entanglement and discord, quantum algorithms, quantum error correction and fault tolerance, quantum computer science, quantum imaging and sensing, and experimental platforms for quantum information. Quantum Information Processing supports and inspires research by providing a comprehensive peer review process, and broadcasting high quality results in a range of formats. These include original papers, letters, broadly focused perspectives, comprehensive review articles, book reviews, and special topical issues. The journal is particularly interested in papers detailing and demonstrating quantum information protocols for cryptography, communications, computation, and sensing.