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利用 PennyLane 库高效实现 Shor 算法的量子基元。

Efficient realization of quantum primitives for Shor's algorithm using PennyLane library.

机构信息

Russian Quantum Center, Skolkovo, Moscow, Russia.

National University of Science and Technology "MISIS", Moscow, Russia.

出版信息

PLoS One. 2022 Jul 14;17(7):e0271462. doi: 10.1371/journal.pone.0271462. eCollection 2022.

Abstract

Efficient realization of quantum algorithms is among main challenges on the way towards practical quantum computing. Various libraries and frameworks for quantum software engineering have been developed. Here we present a software package containing implementations of various quantum gates and well-known quantum algorithms using PennyLane library. Additoinally, we used a simplified technique for decomposition of algorithms into a set of gates which are native for trapped-ion quantum processor and realized this technique using PennyLane library. The decomposition is used to analyze resources required for an execution of Shor's algorithm on the level of native operations of trapped-ion quantum computer. Our original contribution is the derivation of coefficients needed for implementation of the decomposition. Templates within the package include all required elements from the quantum part of Shor's algorithm, specifically, efficient modular exponentiation and quantum Fourier transform that can be realized for an arbitrary number of qubits specified by a user. All the qubit operations are decomposed into elementary gates realized in PennyLane library. Templates from the developed package can be used as qubit-operations when defining a QNode.

摘要

高效实现量子算法是迈向实用量子计算道路上的主要挑战之一。已经开发出了各种量子软件工程库和框架。在这里,我们展示了一个软件包,其中包含使用 PennyLane 库实现的各种量子门和著名的量子算法。此外,我们还使用了一种简化的算法分解技术,将算法分解为一组对于囚禁离子量子处理器来说是本地的门,并使用 PennyLane 库实现了该技术。该分解用于在囚禁离子量子计算机的本地操作级别上分析 Shor 算法的执行所需的资源。我们的原创贡献是推导出实现分解所需的系数。该软件包中的模板包括 Shor 算法量子部分所需的所有元素,特别是高效的模幂运算和量子傅里叶变换,这些都可以为用户指定的任意数量的量子位实现。所有的量子位操作都被分解为在 PennyLane 库中实现的基本门。从开发的软件包中派生的模板可以在定义 QNode 时用作量子位操作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ee0/9282478/630740c7f014/pone.0271462.g001.jpg

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