Benchmarking quantum co-processors in an application-centric, hardware-agnostic and scalable way
ORAL
Abstract
Existing protocols for benchmarking current quantum coprocessors fail to meet the usual standards for assessing the performance of high-performance-computing platforms. After a synthetic review of these protocols—whether at the gate, circuit, or application level—we introduce a new benchmark, dubbed Atos Q-score, which is application-centric, hardware-agnostic, and scalable to quantum advantage processor sizes and beyond. The Q-score measures the maximum number of qubits that can be used effectively to solve the MaxCut combinatorial optimization problem with the quantum approximate optimization algorithm. We give a robust definition of the notion of effective performance by introducing an improved approximation ratio based on the scaling of random and optimal algorithms. We illustrate the behavior of Q-score using perfect and noisy simulations of quantum processors.
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Publication: doi: 10.1109/TQE.2021.3090207
Presenters
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Thomas Ayral
Atos Quantum Lab
Authors
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Thomas Ayral
Atos Quantum Lab
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Simon Martiel
Atos Quantum Lab
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Cyril Allouche
Atos Quantum Lab