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

King, Andrew D.; Raymond, Jack; Lanting, Trevor; Isakov, Sergei V.; Mohseni, Masoud; Poulin-Lamarre, Gabriel; Ejtemaee, Sara; Bernoudy, William; Ozfidan, Isil; Smirnov, Anatoly Yu.; Reis, Mauricio; Altomare, Fabio; Babcock, Michael; Baron, Catia; Berkley, Andrew J.; Boothby, Kelly; Bunyk, Paul I.; Christiani, Holly; Enderud, Colin; Evert, Bram; Harris, Richard; Hoskinson, Emile; Huang, Shuiyuan; Jooya, Kais; Khodabandelou, Ali; Ladizinsky, Nicolas; Li, Ryan; Lott, P. Aaron; MacDonald, Allison J. R.; Marsden, Danica; Marsden, Gaelen; Medina, Teresa; Molavi, Reza; Neufeld, Richard; Norouzpour, Mana; Oh, Travis; Pavlov, Igor; Perminov, Ilya; Prescott, Thomas; Rich, Chris; Sato, Yuki; Sheldan, Benjamin; Sterling, George; Swenson, Loren J.; Tsai, Nicholas; Volkmann, Mark H.; Whittaker, Jed D.; Wilkinson, Warren; Yao, Jason; Neven, Hartmut; Hilton, Jeremy P.; Ladizinsky, Eric; Johnson, Mark W.; Amin, Mohammad H.

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

Andrew D. King (), Jack Raymond, Trevor Lanting, Sergei V. Isakov, Masoud Mohseni, Gabriel Poulin-Lamarre, Sara Ejtemaee, William Bernoudy, Isil Ozfidan, Anatoly Yu. Smirnov, Mauricio Reis, Fabio Altomare, Michael Babcock, Catia Baron, Andrew J. Berkley, Kelly Boothby, Paul I. Bunyk, Holly Christiani, Colin Enderud, Bram Evert, Richard Harris, Emile Hoskinson, Shuiyuan Huang, Kais Jooya, Ali Khodabandelou, Nicolas Ladizinsky, Ryan Li, P. Aaron Lott, Allison J. R. MacDonald, Danica Marsden, Gaelen Marsden, Teresa Medina, Reza Molavi, Richard Neufeld, Mana Norouzpour, Travis Oh, Igor Pavlov, Ilya Perminov, Thomas Prescott, Chris Rich, Yuki Sato, Benjamin Sheldan, George Sterling, Loren J. Swenson, Nicholas Tsai, Mark H. Volkmann, Jed D. Whittaker, Warren Wilkinson, Jason Yao, Hartmut Neven, Jeremy P. Hilton, Eric Ladizinsky, Mark W. Johnson and Mohammad H. Amin
Additional contact information
Andrew D. King: D-Wave Systems
Jack Raymond: D-Wave Systems
Trevor Lanting: D-Wave Systems
Sergei V. Isakov: Google
Masoud Mohseni: Google
Gabriel Poulin-Lamarre: D-Wave Systems
Sara Ejtemaee: D-Wave Systems
William Bernoudy: D-Wave Systems
Isil Ozfidan: D-Wave Systems
Anatoly Yu. Smirnov: D-Wave Systems
Mauricio Reis: D-Wave Systems
Fabio Altomare: D-Wave Systems
Michael Babcock: D-Wave Systems
Catia Baron: D-Wave Systems
Andrew J. Berkley: D-Wave Systems
Kelly Boothby: D-Wave Systems
Paul I. Bunyk: D-Wave Systems
Holly Christiani: D-Wave Systems
Colin Enderud: D-Wave Systems
Bram Evert: D-Wave Systems
Richard Harris: D-Wave Systems
Emile Hoskinson: D-Wave Systems
Shuiyuan Huang: D-Wave Systems
Kais Jooya: D-Wave Systems
Ali Khodabandelou: D-Wave Systems
Nicolas Ladizinsky: D-Wave Systems
Ryan Li: D-Wave Systems
P. Aaron Lott: D-Wave Systems
Allison J. R. MacDonald: D-Wave Systems
Danica Marsden: D-Wave Systems
Gaelen Marsden: D-Wave Systems
Teresa Medina: D-Wave Systems
Reza Molavi: D-Wave Systems
Richard Neufeld: D-Wave Systems
Mana Norouzpour: D-Wave Systems
Travis Oh: D-Wave Systems
Igor Pavlov: D-Wave Systems
Ilya Perminov: D-Wave Systems
Thomas Prescott: D-Wave Systems
Chris Rich: D-Wave Systems
Yuki Sato: D-Wave Systems
Benjamin Sheldan: D-Wave Systems
George Sterling: D-Wave Systems
Loren J. Swenson: D-Wave Systems
Nicholas Tsai: D-Wave Systems
Mark H. Volkmann: D-Wave Systems
Jed D. Whittaker: D-Wave Systems
Warren Wilkinson: D-Wave Systems
Jason Yao: D-Wave Systems
Hartmut Neven: Google
Jeremy P. Hilton: D-Wave Systems
Eric Ladizinsky: D-Wave Systems
Mark W. Johnson: D-Wave Systems
Mohammad H. Amin: D-Wave Systems

Nature Communications, 2021, vol. 12, issue 1, 1-6

Abstract: 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.

Date: 2021
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DOI: 10.1038/s41467-021-20901-5

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