Visual Analytics of Performance of Quantum Computing Systems and Circuit Optimization

TL;DR

This paper presents a visual analytics tool for analyzing quantum device performance and circuit optimization, aiding researchers in designing more efficient quantum algorithms by exploring performance patterns and error properties.

Contribution

It introduces a novel visual analytics approach for quantum performance data and circuit optimization visualization, enhancing interpretability and design of quantum algorithms.

Findings

Enabled detailed analysis of qubit error properties

Facilitated exploration of spatial and temporal performance patterns

Improved understanding of quantum circuit optimization processes

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.