Efficient quantum thermal simulation

Quantum computers promise to tackle quantum simulation problems that are classically intractable 1 . Although a lot of quantum algorithms 2 , 3 – 4 have been developed for simulating quantum dynamics, a general-purpose method for simulating low-temperature quantum phenomena remains unknown. In class...

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Veröffentlicht in:Nature (London) Jg. 646; H. 8085; S. 561 - 566
Hauptverfasser: Chen, Chi-Fang, Kastoryano, Michael, Brandão, Fernando G. S. L., Gilyén, András
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 16.10.2025
Nature Publishing Group
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ISSN:0028-0836, 1476-4687, 1476-4687
Online-Zugang:Volltext
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Zusammenfassung:Quantum computers promise to tackle quantum simulation problems that are classically intractable 1 . Although a lot of quantum algorithms 2 , 3 – 4 have been developed for simulating quantum dynamics, a general-purpose method for simulating low-temperature quantum phenomena remains unknown. In classical settings, the analogous task of sampling from thermal distributions has been largely addressed by Markov Chain Monte Carlo (MCMC) methods 5 , 6 . Here we propose an efficient quantum algorithm for thermal simulation that—akin to MCMC methods—exhibits detailed balance, respects locality and serves as a toy model for thermalization in open quantum systems. The enduring impact of MCMC methods suggests that our new construction may play an equally important part in quantum computing and applications in the physical sciences and beyond. An efficient quantum thermal simulation algorithm that exhibits detailed balance, respects locality, and serves as a self-contained model for thermalization in open quantum systems.
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ISSN:0028-0836
1476-4687
1476-4687
DOI:10.1038/s41586-025-09583-x