Visual Analytics of Performance of Quantum Computing Systems and Circuit Optimization

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publication2024 IEEE Computer Society Annual Symposium on VLSI
Subtitle of host publicationEmerging VLSI Technologies and Architectures, ISVLSI 2024
EditorsHimanshu Thapliyal, Jurgen Becker
PublisherIEEE Computer Society
Pages613-618
Number of pages6
ISBN (Electronic)9798350354119
DOIs
StatePublished - 2024
Event2024 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2024 - Knoxville, United States
Duration: Jul 1 2024Jul 3 2024

Publication series

NameProceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI
ISSN (Print)2159-3469
ISSN (Electronic)2159-3477

Conference

Conference2024 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2024
Country/TerritoryUnited States
CityKnoxville
Period07/1/2407/3/24

Funding

This research used computing resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. The manuscript is authored by UTBattelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. http://energy.gov/downloads/doe-public-access-plan. This research was supported by the US Department of Energy, Advanced Scientific Computing Research (ASCR), Accelerated Research in Quantum Computing (ARQC) program.

Keywords

  • circuit optimization
  • data visualization
  • quantum computing
  • visual analytics

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