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SoK: Benchmarking the Performance of a Quantum Computer
Junchao Wang1,2, Guoping Guo2, Zheng Shan1
1State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou 450002, China.
Entropy (Basel, Switzerland)
|July 8, 2023
Summary
Quantum computing performance evaluation requires robust benchmarking beyond qubit count. This review categorizes methods and proposes new standards for accurate quantum computer assessment.
Area of Science:
- Quantum Computing
- Computer Science
- Information Technology
Background:
- Quantum computers offer potential advantages over classical computers for specific problems.
- Current performance evaluation often relies solely on qubit count, which is misleading.
- Effective quantum benchmarking is crucial for development and investment decisions.
Purpose of the Study:
- To review existing quantum computer performance benchmarking protocols, models, and metrics.
- To classify current benchmarking techniques into distinct categories.
- To discuss future trends and propose new benchmarking standards like QTOP100.
Main Methods:
- Literature review of quantum benchmarking protocols.
- Classification of benchmarking techniques into physical, aggregative, and application-level categories.
- Analysis of current metrics and their limitations.
Main Results:
- Identified three primary categories of quantum benchmarking: physical, aggregative, and application-level.
- Highlighted the inadequacy of qubit count as a sole performance metric.
- Discussed the need for comprehensive benchmarking for accurate quantum computer evaluation.
Conclusions:
- Quantum computer performance evaluation necessitates sophisticated benchmarking beyond simple qubit counts.
- A structured approach to benchmarking, encompassing physical, aggregative, and application-level aspects, is essential.
- The proposed QTOP100 aims to establish a future standard for quantum computer benchmarking.
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