QuSquare: Scalable Quality-Oriented Benchmark Suite for Pre-Fault-Tolerant Quantum Devices

Abstract:As quantum technologies continue to advance, the proliferation of hardware architectures with diverse capabilities and limitations has underscored the importance of benchmarking as a tool to compare performance across platforms. Achieving fair, scalable and consistent evaluations is a key open problem in quantum computing, particularly in the pre-fault-tolerant era. To address this challenge, we introduce QuSquare, a quality-oriented benchmark suite designed to provide a scalable, fair, reproducible, and well-defined framework for assessing the performance of quantum devices across hardware architectures. QuSquare consists of four benchmark tests that evaluate quantum hardware performance at both the system and application levels: Partial Clifford Randomized, Multipartite Entanglement, Transverse Field Ising Model (TFIM) Hamiltonian Simulation, and Data Re-Uploading Quantum Neural Network (QNN). Together, these benchmarks offer an integral, hardware-agnostic, and impartial methodology to quantify the quality and capabilities of current quantum computers, supporting fair cross-platform comparisons and fostering the development of future performance standards.

arXiv:2512.19665 [quant-ph]

(or arXiv:2512.19665v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2512.19665 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.1088/2058-9565/ae917c Focus to learn more DOI(s) linking to related resources

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