Q-BEAST: A Practical Course on Experimental Evaluation and Characterization of Quantum Computing Systems
Abstract
Quantum computing (QC) promises to be a transformative technology with impact on various application domains, such as optimization, cryptography, and material science. However, the technology has a sharp learning curve, and practical evaluation and characterization of quantum systems remains complex and challenging, particularly for students and newcomers from computer science to the field of quantum computing. To address this educational gap, we introduce Q-BEAST, a practical course designed to provide structured training in the experimental analysis of quantum computing systems. Q-BEAST offers a curriculum that combines foundational concepts in quantum computing with practical methodologies and use cases for benchmarking and performance evaluation on actual quantum systems. Through theoretical instruction and hands-on experimentation, students gain experience in assessing the advantages and limitations of real quantum technologies. With that, Q-BEAST supports the education of a future generation of quantum computing users and developers. Furthermore, it also explicitly promotes a deeper integration of High Performance Computing (HPC) and QC in research and education.
Cite
@article{arxiv.2508.14084,
title = {Q-BEAST: A Practical Course on Experimental Evaluation and Characterization of Quantum Computing Systems},
author = {Minh Chung and Yaknan Gambo and Burak Mete and Xiao-Ting Michelle To and Florian Krötz and Korbinian Staudacher and Martin Letras and Xiaolong Deng and Mounika Vavilala and Amir Raoofy and Jorge Echavarria and Luigi Iapichino and Laura Schulz and Josef Weidendorfer and Martin Schulz},
journal= {arXiv preprint arXiv:2508.14084},
year = {2025}
}
Comments
This paper is submitted and accepted in the Fourth Annual Quantum Science and Engineering Education Conference (QSEEC25), which is collocated with the IEEE International Conference on Quantum Computing & Engineering (QCE25), part of IEEE Quantum Week 2025