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      Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets

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      Nature Communications
      Nature Publishing Group UK
      Computational science, Phase transitions and critical phenomena, Quantum simulation

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          Abstract

          The promise of quantum computing lies in harnessing programmable quantum devices for practical applications such as efficient simulation of quantum materials and condensed matter systems. One important task is the simulation of geometrically frustrated magnets in which topological phenomena can emerge from competition between quantum and thermal fluctuations. Here we report on experimental observations of equilibration in such simulations, measured on up to 1440 qubits with microsecond resolution. By initializing the system in a state with topological obstruction, we observe quantum annealing (QA) equilibration timescales in excess of one microsecond. Measurements indicate a dynamical advantage in the quantum simulation compared with spatially local update dynamics of path-integral Monte Carlo (PIMC). The advantage increases with both system size and inverse temperature, exceeding a million-fold speedup over an efficient CPU implementation. PIMC is a leading classical method for such simulations, and a scaling advantage of this type was recently shown to be impossible in certain restricted settings. This is therefore an important piece of experimental evidence that PIMC does not simulate QA dynamics even for sign-problem-free Hamiltonians, and that near-term quantum devices can be used to accelerate computational tasks of practical relevance.

          Abstract

          Experimental demonstration of quantum speedup that scales with the system size is the goal of near-term quantum computing. Here, the authors demonstrate such scaling advantage for a D-Wave quantum annealer over analogous classical algorithms in simulations of frustrated quantum magnets.

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          Most cited references32

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          Quantum supremacy using a programmable superconducting processor

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            Quantum Computing in the NISQ era and beyond

            Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the near future. Quantum computers with 50-100 qubits may be able to perform tasks which surpass the capabilities of today's classical digital computers, but noise in quantum gates will limit the size of quantum circuits that can be executed reliably. NISQ devices will be useful tools for exploring many-body quantum physics, and may have other useful applications, but the 100-qubit quantum computer will not change the world right away - we should regard it as a significant step toward the more powerful quantum technologies of the future. Quantum technologists should continue to strive for more accurate quantum gates and, eventually, fully fault-tolerant quantum computing.
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              Quantum annealing with manufactured spins.

              Many interesting but practically intractable problems can be reduced to that of finding the ground state of a system of interacting spins; however, finding such a ground state remains computationally difficult. It is believed that the ground state of some naturally occurring spin systems can be effectively attained through a process called quantum annealing. If it could be harnessed, quantum annealing might improve on known methods for solving certain types of problem. However, physical investigation of quantum annealing has been largely confined to microscopic spins in condensed-matter systems. Here we use quantum annealing to find the ground state of an artificial Ising spin system comprising an array of eight superconducting flux quantum bits with programmable spin-spin couplings. We observe a clear signature of quantum annealing, distinguishable from classical thermal annealing through the temperature dependence of the time at which the system dynamics freezes. Our implementation can be configured in situ to realize a wide variety of different spin networks, each of which can be monitored as it moves towards a low-energy configuration. This programmable artificial spin network bridges the gap between the theoretical study of ideal isolated spin networks and the experimental investigation of bulk magnetic samples. Moreover, with an increased number of spins, such a system may provide a practical physical means to implement a quantum algorithm, possibly allowing more-effective approaches to solving certain classes of hard combinatorial optimization problems.
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                Author and article information

                Contributors
                aking@dwavesys.com
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                18 February 2021
                18 February 2021
                2021
                : 12
                : 1113
                Affiliations
                [1 ]GRID grid.421761.7, ISNI 0000 0004 0450 6527, D-Wave Systems, ; Burnaby, BC Canada
                [2 ]GRID grid.472568.a, Google, ; Zurich, Switzerland
                [3 ]GRID grid.420451.6, Google, ; Venice, CA USA
                [4 ]GRID grid.61971.38, ISNI 0000 0004 1936 7494, Department of Physics, , Simon Fraser University, ; Burnaby, BC Canada
                Author information
                http://orcid.org/0000-0001-8362-8941
                http://orcid.org/0000-0002-2602-6255
                http://orcid.org/0000-0002-4235-8452
                http://orcid.org/0000-0001-9799-1872
                http://orcid.org/0000-0001-8989-3199
                http://orcid.org/0000-0002-0456-3244
                Article
                20901
                10.1038/s41467-021-20901-5
                7892843
                33602927
                8474da7c-a022-4ca1-9c31-a3caaa2d3301
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 July 2020
                : 22 December 2020
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                © The Author(s) 2021

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                computational science,phase transitions and critical phenomena,quantum simulation

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