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Autori principali: Chae, Junghoon, Steed, Chad A., Humble, Travis S.
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2409.06159
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author Chae, Junghoon
Steed, Chad A.
Humble, Travis S.
author_facet Chae, Junghoon
Steed, Chad A.
Humble, Travis S.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2409_06159
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Visual Analytics of Performance of Quantum Computing Systems and Circuit Optimization
Chae, Junghoon
Steed, Chad A.
Humble, Travis S.
Quantum Physics
Human-Computer Interaction
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.
title Visual Analytics of Performance of Quantum Computing Systems and Circuit Optimization
topic Quantum Physics
Human-Computer Interaction
url https://arxiv.org/abs/2409.06159