Nature Communications (Feb 2021)

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,
  • Mohammad H. Amin

DOI
https://doi.org/10.1038/s41467-021-20901-5
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 6

Abstract

Read online

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.