Wang Pei-Hua, Wu Wei-Yeh, Lee Che-Yu, Hong Jia-Cheng, Tseng Yufeng Jane
Undergraduate Program in Intelligent Computing and Big Data, Chung Yuan Christian University, No. 200, Zhongbei Road, Taoyuan, 320314, Taiwan.
Quantum Information Center, Chung Yuan Christian University, No. 200, Zhongbei Road, Taoyuan, 320314, Taiwan.
J Cheminform. 2025 May 19;17(1):77. doi: 10.1186/s13321-025-01026-z.
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 .
量子计算处于技术进步的前沿,有潜力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,重点关注它们在教学和研究方面的适用性。我们深入探讨它们的基本和高级用法,研究它们的学习曲线,并评估它们在量子计算实验中的能力。我们还演示了使用一种量子编程语言构建一个半加器和一个机器学习模型。我们的研究表明,每种语言都有独特的优势。虽然PennyLane由于其在详细调整参数和访问多个真实量子设备源方面的灵活性而在研究应用中表现出色,但Qiskit因其基于网络的图形用户界面和较小的代码规模而在教育方面脱颖而出。研究中使用的代码和数据集可在https://github.com/wangpeihua1231/quantum-programming-platform获取。