Phase transitions in random circuit sampling.

Autor: Morvan A; Google Research, Mountain View, CA, USA., Villalonga B; Google Research, Mountain View, CA, USA., Mi X; Google Research, Mountain View, CA, USA., Mandrà S; Google Research, Mountain View, CA, USA.; Quantum Artificial Intelligence Laboratory, NASA Ames Research Center, Moffett Field, CA, USA.; KBR, Houston, TX, USA., Bengtsson A; Google Research, Mountain View, CA, USA., Klimov PV; Google Research, Mountain View, CA, USA., Chen Z; Google Research, Mountain View, CA, USA., Hong S; Google Research, Mountain View, CA, USA., Erickson C; Google Research, Mountain View, CA, USA., Drozdov IK; Google Research, Mountain View, CA, USA.; Department of Physics, University of Connecticut, Storrs, CT, USA., Chau J; Google Research, Mountain View, CA, USA., Laun G; Google Research, Mountain View, CA, USA., Movassagh R; Google Research, Mountain View, CA, USA., Asfaw A; Google Research, Mountain View, CA, USA., Brandão LTAN; Strativia, Foreign Guest Researcher (Contractor) at National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA., Peralta R; National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA., Abanin D; Google Research, Mountain View, CA, USA., Acharya R; Google Research, Mountain View, CA, USA., Allen R; Google Research, Mountain View, CA, USA., Andersen TI; Google Research, Mountain View, CA, USA., Anderson K; Google Research, Mountain View, CA, USA., Ansmann M; Google Research, Mountain View, CA, USA., Arute F; Google Research, Mountain View, CA, USA., Arya K; Google Research, Mountain View, CA, USA., Atalaya J; Google Research, Mountain View, CA, USA., Bardin JC; Google Research, Mountain View, CA, USA.; Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA., Bilmes A; Google Research, Mountain View, CA, USA., Bortoli G; Google Research, Mountain View, CA, USA., Bourassa A; Google Research, Mountain View, CA, USA., Bovaird J; Google Research, Mountain View, CA, USA., Brill L; Google Research, Mountain View, CA, USA., Broughton M; Google Research, Mountain View, CA, USA., Buckley BB; 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Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA., Hansen M; Google Research, Mountain View, CA, USA., Harrigan MP; Google Research, Mountain View, CA, USA., Harrington SD; Google Research, Mountain View, CA, USA., Heu P; Google Research, Mountain View, CA, USA., Hoffmann MR; Google Research, Mountain View, CA, USA., Huang T; Google Research, Mountain View, CA, USA., Huff A; Google Research, Mountain View, CA, USA., Huggins WJ; Google Research, Mountain View, CA, USA., Ioffe LB; Google Research, Mountain View, CA, USA., Isakov SV; Google Research, Mountain View, CA, USA., Iveland J; Google Research, Mountain View, CA, USA., Jeffrey E; Google Research, Mountain View, CA, USA., Jiang Z; Google Research, Mountain View, CA, USA., Jones C; Google Research, Mountain View, CA, USA., Juhas P; Google Research, Mountain View, CA, USA., Kafri D; Google Research, Mountain View, CA, USA., Khattar T; Google Research, Mountain View, CA, USA., Khezri M; Google Research, Mountain View, CA, USA., Kieferová M; Google Research, Mountain View, CA, USA.; QSI, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, New South Wales, Australia., Kim S; Google Research, Mountain View, CA, USA., Kitaev A; Google Research, Mountain View, CA, USA., Klots AR; Google Research, Mountain View, CA, USA., Korotkov AN; Google Research, Mountain View, CA, USA.; Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA., Kostritsa F; Google Research, Mountain View, CA, USA., Kreikebaum JM; Google Research, Mountain View, CA, USA., Landhuis D; Google Research, Mountain View, CA, USA., Laptev P; Google Research, Mountain View, CA, USA., Lau KM; Google Research, Mountain View, CA, USA., Laws L; Google Research, Mountain View, CA, USA., Lee J; Google Research, Mountain View, CA, USA.; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA., Lee KW; Google Research, Mountain View, CA, USA., Lensky YD; Google Research, Mountain View, CA, USA., Lester BJ; 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Google Research, Mountain View, CA, USA., Smelyanskiy V; Google Research, Mountain View, CA, USA., Kechedzhi K; Google Research, Mountain View, CA, USA. kostyantyn@google.com., Chen Y; Google Research, Mountain View, CA, USA., Boixo S; Google Research, Mountain View, CA, USA.
Jazyk: angličtina
Zdroj: Nature [Nature] 2024 Oct; Vol. 634 (8033), pp. 328-333. Date of Electronic Publication: 2024 Oct 09.
DOI: 10.1038/s41586-024-07998-6
Abstrakt: Undesired coupling to the surrounding environment destroys long-range correlations in quantum processors and hinders coherent evolution in the nominally available computational space. This noise is an outstanding challenge when leveraging the computation power of near-term quantum processors 1 . It has been shown that benchmarking random circuit sampling with cross-entropy benchmarking can provide an estimate of the effective size of the Hilbert space coherently available 2-8 . Nevertheless, quantum algorithms' outputs can be trivialized by noise, making them susceptible to classical computation spoofing. Here, by implementing an algorithm for random circuit sampling, we demonstrate experimentally that two phase transitions are observable with cross-entropy benchmarking, which we explain theoretically with a statistical model. The first is a dynamical transition as a function of the number of cycles and is the continuation of the anti-concentration point in the noiseless case. The second is a quantum phase transition controlled by the error per cycle; to identify it analytically and experimentally, we create a weak-link model, which allows us to vary the strength of the noise versus coherent evolution. Furthermore, by presenting a random circuit sampling experiment in the weak-noise phase with 67 qubits at 32 cycles, we demonstrate that the computational cost of our experiment is beyond the capabilities of existing classical supercomputers. Our experimental and theoretical work establishes the existence of transitions to a stable, computationally complex phase that is reachable with current quantum processors.
(© 2024. The Author(s).)
Databáze: MEDLINE
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