Benchmarking quantum computers with any quantum algorithm
Fuente:
arXiv
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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866916886774546432 |
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| author | Seritan, Stefan K. Dhumuntarao, Aditya Wilber-Gauthier, Aidan Q. Rudinger, Kenneth M. Russo, Antonio E. Blume-Kohout, Robin Baczewski, Andrew D. Proctor, Timothy |
| author_facet | Seritan, Stefan K. Dhumuntarao, Aditya Wilber-Gauthier, Aidan Q. Rudinger, Kenneth M. Russo, Antonio E. Blume-Kohout, Robin Baczewski, Andrew D. Proctor, Timothy |
| contents | Application-based benchmarks are increasingly used to quantify and compare quantum computers' performance. However, because contemporary quantum computers cannot run utility-scale computations, these benchmarks currently test this hardware's performance on ``small'' problem instances that are not necessarily representative of utility-scale problems. Furthermore, these benchmarks often employ methods that are unscalable, limiting their ability to track progress towards utility-scale applications. In this work, we present a method for creating scalable and efficient benchmarks from any quantum algorithm or application. Our subcircuit volumetric benchmarking (SVB) method runs subcircuits of varied shape that are ``snipped out'' from some target circuit, which could implement a utility-scale algorithm. SVB is scalable and it enables estimating a capability coefficient that concisely summarizes progress towards implementing the target circuit. We demonstrate SVB with experiments on IBM Q systems using a Hamiltonian block-encoding subroutine from quantum chemistry algorithms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_05754 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Benchmarking quantum computers with any quantum algorithm Seritan, Stefan K. Dhumuntarao, Aditya Wilber-Gauthier, Aidan Q. Rudinger, Kenneth M. Russo, Antonio E. Blume-Kohout, Robin Baczewski, Andrew D. Proctor, Timothy Quantum Physics Application-based benchmarks are increasingly used to quantify and compare quantum computers' performance. However, because contemporary quantum computers cannot run utility-scale computations, these benchmarks currently test this hardware's performance on ``small'' problem instances that are not necessarily representative of utility-scale problems. Furthermore, these benchmarks often employ methods that are unscalable, limiting their ability to track progress towards utility-scale applications. In this work, we present a method for creating scalable and efficient benchmarks from any quantum algorithm or application. Our subcircuit volumetric benchmarking (SVB) method runs subcircuits of varied shape that are ``snipped out'' from some target circuit, which could implement a utility-scale algorithm. SVB is scalable and it enables estimating a capability coefficient that concisely summarizes progress towards implementing the target circuit. We demonstrate SVB with experiments on IBM Q systems using a Hamiltonian block-encoding subroutine from quantum chemistry algorithms. |
| title | Benchmarking quantum computers with any quantum algorithm |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2508.05754 |