Advantages of two quantum programming platforms in quantum computing and quantum chemistry

IF 7.1 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Pei-Hua Wang, Wei-Yeh Wu, Che-Yu Lee, Jia-Cheng Hong, Yufeng Jane Tseng
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引用次数: 0

Abstract

Quantum computing is at the forefront of technological advancement and has the potential to revolutionize various fields, including quantum chemistry. Choosing an appropriate quantum programming language becomes critical as quantum education and research increase. In this paper, we comprehensively compare two leading quantum programming languages, Qiskit and PennyLane, focusing on their suitability for teaching and research. We delve into their basic and advanced usage, examine their learning curves, and evaluate their capabilities in quantum computing experiments. We also demonstrate using a quantum programming language to build a half adder and a machine learning model. Our study reveals that each language has distinct advantages. While PennyLane excels in research applications due to its flexibility to adjust parameters in detail and access multiple sources of real quantum devices, Qiskit stands out in education because of its web-based graphical user interface and smaller code size. The codes and the dataset used in the studies are available at https://github.com/wangpeihua1231/quantum-programming-platform.

两种量子编程平台在量子计算和量子化学中的优势
量子计算处于技术进步的前沿,有可能彻底改变包括量子化学在内的各个领域。随着量子教育和研究的增加,选择一种合适的量子编程语言变得至关重要。在本文中,我们全面比较了两种领先的量子编程语言Qiskit和PennyLane,重点关注它们对教学和研究的适用性。我们深入研究它们的基本和高级使用,检查它们的学习曲线,并评估它们在量子计算实验中的能力。我们还演示了使用量子编程语言构建半加法器和机器学习模型。我们的研究表明,每种语言都有其独特的优势。PennyLane在研究应用方面表现出色,因为它可以灵活地调整细节参数,并访问多个真正的量子设备来源,而Qiskit在教育领域脱颖而出,因为它的基于网络的图形用户界面和更小的代码大小。研究中使用的代码和数据集可在https://github.com/wangpeihua1231/quantum-programming-platform上获得。
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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来源期刊
Journal of Cheminformatics
Journal of Cheminformatics CHEMISTRY, MULTIDISCIPLINARY-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
14.10
自引率
7.00%
发文量
82
审稿时长
3 months
期刊介绍: Journal of Cheminformatics is an open access journal publishing original peer-reviewed research in all aspects of cheminformatics and molecular modelling. Coverage includes, but is not limited to: chemical information systems, software and databases, and molecular modelling, chemical structure representations and their use in structure, substructure, and similarity searching of chemical substance and chemical reaction databases, computer and molecular graphics, computer-aided molecular design, expert systems, QSAR, and data mining techniques.
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