Phase transitions in random circuit sampling
成果类型：
Article
署名作者：
Morvan, A.; Villalonga, B.; Mi, X.; Mandra, S.; Bengtsson, A.; Klimov, P. V.; Chen, Z.; Hong, S.; Erickson, C.; Drozdov, I. K.; Chau, J.; Laun, G.; Movassagh, R.; Asfaw, A.; Brandao, L. T. A. N.; Peralta, R.; Abanin, D.; Acharya, R.; Allen, R.; Andersen, T. I.; Anderson, K.; Ansmann, M.; Arute, F.; Arya, K.; Atalaya, J.; Bardin, J. C.; Bilmes, A.; Bortoli, G.; Bourassa, A.; Bovaird, J.; Brill, L.; Broughton, M.; Buckley, B. B.; Buell, D. A.; Burger, T.; Burkett, B.; Bushnell, N.; Campero, J.; Chang, H. -S.; Chiaro, B.; Chik, D.; Chou, C.; Cogan, J.; Collins, R.; Conner, P.; Courtney, W.; Crook, A. L.; Curtin, B.; Debroy, D. M.; Barba, A. Del Toro; Demura, S.; Di Paolo, A.; Dunsworth, A.; Faoro, L.; Farhi, E.; Fatemi, R.; Ferreira, V. S.; Burgos, L. Flores; Forati, E.; Fowler, A. G.; Foxen, B.; Garcia, G.; Genois, E.; Giang, W.; Gidney, C.; Gilboa, D.; Giustina, M.; Gosula, R.; Dau, A. Grajales; Gross, J. A.; Habegger, S.; Hamilton, M. C.; Hansen, M.; Harrigan, M. P.; Harrington, S. D.; Heu, P.; Hoffmann, M. R.; Huang, T.; Huff, A.; Huggins, W. J.; Ioffe, L. B.; Isakov, S. V.; Iveland, J.; Jeffrey, E.; Jiang, Z.; Jones, C.; Juhas, P.; Kafri, D.; Khattar, T.; Khezri, M.; Kieferova, M.; Kim, S.; Kitaev, A.; Klots, A. R.; Korotkov, A. N.; Kostritsa, F.; Kreikebaum, J. M.; Landhuis, D.; Laptev, P.; Lau, K. -M.; Laws, L.; Lee, J.; Lee, K. W.; Lensky, Y. D.; Lester, B. J.; Lill, A. T.; Liu, W.; Livingston, W. P.; Locharla, A.; Malone, F. D.; Martin, O.; Martin, S.; McClean, J. R.; McEwen, M.; Miao, K. C.; Mieszala, A.; Montazeri, S.; Mruczkiewicz, W.; Naaman, O.; Neeley, M.; Neill, C.; Nersisyan, A.; Newman, M.; Ng, J. H.; Nguyen, A.; Nguyen, M.; Niu, M. Yuezhen; O'Brien, T. E.; Omonije, S.; Opremcak, A.; Petukhov, A.; Potter, R.; Pryadko, L. P.; Quintana, C.; Rhodes, D. M.; Rocque, C.; Rosenberg, E.; Rubin, N. C.; Saei, N.; Sank, D.; Sankaragomathi, K.; Satzinger, K. J.; Schurkus, H. F.; Schuster, C.; Shearn, M. J.; Shorter, A.; Shutty, N.; Shvarts, V.; Sivak, V.; Skruzny, J.; Smith, W. C.; Somma, R. D.; Sterling, G.; Strain, D.; Szalay, M.; Thor, D.; Torres, A.; Vidal, G.; Heidweiller, C. Vollgraff; White, T.; Woo, B. W. K.; Xing, C.; Yao, Z. J.; Yeh, P.; Yoo, J.; Young, G.; Zalcman, A.; Zhang, Y.; Zhu, N.; Zobrist, N.; Rieffel, E. G.; Biswas, R.; Babbush, R.; Bacon, D.; Hilton, J.; Lucero, E.; Neven, H.; Megrant, A.; Kelly, J.; Roushan, P.; Aleiner, I.; Smelyanskiy, V.; Kechedzhi, K.; Chen, Y.; Boixo, S.
署名单位：
Alphabet Inc.; Google Incorporated; National Aeronautics & Space Administration (NASA); NASA Ames Research Center; University of Connecticut; National Institute of Standards & Technology (NIST) - USA; National Institute of Standards & Technology (NIST) - USA; University of Massachusetts System; University of Massachusetts Amherst; Auburn University System; Auburn University; University of Technology Sydney; University of California System; University of California Riverside; Harvard University; University of California System; University of California Riverside
刊物名称：
Nature
ISSN/ISSBN：
0028-5117
DOI：
10.1038/s41586-024-07998-6
发表日期：
2024-10-10
关键词：
quantum computational advantage
supremacy
摘要：
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 processors1. 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 available2-8. 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. By implementing random circuit sampling, experimental and theoretical results establish the existence of transitions to a stable, computationally complex phase that is reachable with current quantum processors.