Work

Entropy density benchmarking of near-term quantum circuits

Year: 2026

Type: article

Abstract: Understanding the limitations imposed by noise on current and next-generation quantum devices is a crucial step toward demonstrating practical quantum advantage. In this work, we investigate the accumulation of entropy density as a benchmark to monitor the performance of quantum processing units (QPUs). We provide a proof-of-principle demonstration of our methodology which entails developing simple heuristic models of how entropy accumulates, testing them against real QPU data, and finally using these models to determine a circuit volume threshold above which quantum advantage is unattainable. Monitoring entropy density not only offers an alternative approach that complements existing circuit-level benchmarking techniques, but, more importantly, it bridges the gap between circuit-level and application-level benchmarking protocols. In particular, our heuristic model of entropy accumulation allows us to outperform existing techniques that bound the circuit-size threshold for quantum advantage.

Source: Physical Review A

DOI: 10.1103/swvt-3pkh

Authors: Marine Demarty, James Mills, Kenza Hammam, Raúl García-Patrón

Institutions: University of Edinburgh, Quandela (France), Phasecraft Ltd. (United Kingdom)

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,675

Funder: Engineering and Physical Sciences Research Council