[2603.26359] Automated near-term quantum algorithm discovery for molecular ground states

[2603.26359] Automated near-term quantum algorithm discovery for molecular ground states

arXiv - AI 3 min read

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Abstract page for arXiv paper 2603.26359: Automated near-term quantum algorithm discovery for molecular ground states

Quantum Physics arXiv:2603.26359 (quant-ph) [Submitted on 27 Mar 2026] Title:Automated near-term quantum algorithm discovery for molecular ground states Authors:Fabian Finger, Frederic Rapp, Pranav Kalidindi, Kerry He, Kante Yin, Alexander Koziell-Pipe, David Zsolt Manrique, Gabriel Greene-Diniz, Stephen Clark, Hamza Fawzi, Bernardino Romera Paredes, Alhussein Fawzi, Konstantinos Meichanetzidis View a PDF of the paper titled Automated near-term quantum algorithm discovery for molecular ground states, by Fabian Finger and 12 other authors View PDF HTML (experimental) Abstract:Designing quantum algorithms is a complex and counterintuitive task, making it an ideal candidate for AI-driven algorithm discovery. To this end, we employ the Hive, an AI platform for program synthesis, which utilises large language models to drive a highly distributed evolutionary process for discovering new algorithms. We focus on the ground state problem in quantum chemistry, and discover efficient quantum heuristic algorithms that solve it for molecules LiH, H2O, and F2 while exhibiting significant reductions in quantum resources relative to state-of-the-art near-term quantum algorithms. Further, we perform an interpretability study on the discovered algorithms and identify the key functions responsible for the efficiency gains. Finally, we benchmark the Hive-discovered circuits on the Quantinuum System Model H2 quantum computer and identify minimum system requirements for chemical precision. We e...

Originally published on March 30, 2026. Curated by AI News.

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