@inproceedings{bdd8c4efd44142be98fdbb0788af698a,
title = "Visual Analytics of Performance of Quantum Computing Systems and Circuit Optimization",
abstract = "Driven by potential exponential speedups in business, security, and scientific scenarios, interest in quantum computing is surging. This interest feeds the development of quantum computing hardware, but several challenges arise in optimizing application performance for hardware metrics (e.g., qubit coherence and gate fidelity). In this work, we describe a visual analytics approach for analyzing the performance properties of quantum devices and quantum circuit optimization. Our approach allows users to explore spatial and temporal patterns in quantum device performance data and it computes similarities and variances in key performance metrics. Detailed analysis of the error properties characterizing individual qubits is also supported. We also describe a method for visualizing the optimization of quantum circuits. The resulting visualization tool allows researchers to design more efficient quantum algorithms and applications by increasing the interpretability of quantum computations.",
keywords = "circuit optimization, data visualization, quantum computing, visual analytics",
author = "Junghoon Chae and Steed, {Chad A.} and Humble, {Travis S.}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2024 ; Conference date: 01-07-2024 Through 03-07-2024",
year = "2024",
doi = "10.1109/ISVLSI61997.2024.00116",
language = "English",
series = "Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI",
publisher = "IEEE Computer Society",
pages = "613--618",
editor = "Himanshu Thapliyal and Jurgen Becker",
booktitle = "2024 IEEE Computer Society Annual Symposium on VLSI",
}