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Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets
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 emer...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892843/ https://www.ncbi.nlm.nih.gov/pubmed/33602927 http://dx.doi.org/10.1038/s41467-021-20901-5 |
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author | 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. |
author_facet | 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. |
author_sort | King, Andrew D. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7892843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78928432021-03-03 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. Nat Commun Article 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. Nature Publishing Group UK 2021-02-18 /pmc/articles/PMC7892843/ /pubmed/33602927 http://dx.doi.org/10.1038/s41467-021-20901-5 Text en © 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/. |
spellingShingle | Article 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 |
title | Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets |
title_full | Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets |
title_fullStr | Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets |
title_full_unstemmed | Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets |
title_short | Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets |
title_sort | scaling advantage over path-integral monte carlo in quantum simulation of geometrically frustrated magnets |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892843/ https://www.ncbi.nlm.nih.gov/pubmed/33602927 http://dx.doi.org/10.1038/s41467-021-20901-5 |
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