Literature DB >> 21368829

Quantum Metropolis sampling.

K Temme1, T J Osborne, K G Vollbrecht, D Poulin, F Verstraete.   

Abstract

The original motivation to build a quantum computer came from Feynman, who imagined a machine capable of simulating generic quantum mechanical systems--a task that is believed to be intractable for classical computers. Such a machine could have far-reaching applications in the simulation of many-body quantum physics in condensed-matter, chemical and high-energy systems. Part of Feynman's challenge was met by Lloyd, who showed how to approximately decompose the time evolution operator of interacting quantum particles into a short sequence of elementary gates, suitable for operation on a quantum computer. However, this left open the problem of how to simulate the equilibrium and static properties of quantum systems. This requires the preparation of ground and Gibbs states on a quantum computer. For classical systems, this problem is solved by the ubiquitous Metropolis algorithm, a method that has basically acquired a monopoly on the simulation of interacting particles. Here we demonstrate how to implement a quantum version of the Metropolis algorithm. This algorithm permits sampling directly from the eigenstates of the Hamiltonian, and thus evades the sign problem present in classical simulations. A small-scale implementation of this algorithm should be achievable with today's technology.

Year:  2011        PMID: 21368829     DOI: 10.1038/nature09770

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  10 in total

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Authors:  E Farhi; J Goldstone; S Gutmann; J Lapan; A Lundgren; D Preda
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2.  Rejection-free geometric cluster algorithm for complex fluids.

Authors:  Jiwen Liu; Erik Luijten
Journal:  Phys Rev Lett       Date:  2004-01-23       Impact factor: 9.161

3.  Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.

Authors:  S Geman; D Geman
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4.  Nonuniversal critical dynamics in Monte Carlo simulations.

Authors: 
Journal:  Phys Rev Lett       Date:  1987-01-12       Impact factor: 9.161

5.  Sampling from the thermal quantum Gibbs state and evaluating partition functions with a quantum computer.

Authors:  David Poulin; Pawel Wocjan
Journal:  Phys Rev Lett       Date:  2009-11-24       Impact factor: 9.161

6.  Simulated quantum computation of molecular energies.

Authors:  Alán Aspuru-Guzik; Anthony D Dutoi; Peter J Love; Martin Head-Gordon
Journal:  Science       Date:  2005-09-09       Impact factor: 47.728

7.  Ab initio determination of light hadron masses.

Authors:  S Dürr; Z Fodor; J Frison; C Hoelbling; R Hoffmann; S D Katz; S Krieg; T Kurth; L Lellouch; T Lippert; K K Szabo; G Vulvert
Journal:  Science       Date:  2008-11-21       Impact factor: 47.728

8.  Optimization by simulated annealing.

Authors:  S Kirkpatrick; C D Gelatt; M P Vecchi
Journal:  Science       Date:  1983-05-13       Impact factor: 47.728

9.  Quantum simulations of classical annealing processes.

Authors:  R D Somma; S Boixo; H Barnum; E Knill
Journal:  Phys Rev Lett       Date:  2008-09-26       Impact factor: 9.161

10.  Universal Quantum Simulators

Authors: 
Journal:  Science       Date:  1996-08-23       Impact factor: 47.728

  10 in total
  8 in total

1.  A quantum-quantum Metropolis algorithm.

Authors:  Man-Hong Yung; Alán Aspuru-Guzik
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-03       Impact factor: 11.205

2.  Digital quantum simulation of the statistical mechanics of a frustrated magnet.

Authors:  Jingfu Zhang; Man-Hong Yung; Raymond Laflamme; Alán Aspuru-Guzik; Jonathan Baugh
Journal:  Nat Commun       Date:  2012-06-06       Impact factor: 14.919

3.  Quantum machine learning.

Authors:  Jacob Biamonte; Peter Wittek; Nicola Pancotti; Patrick Rebentrost; Nathan Wiebe; Seth Lloyd
Journal:  Nature       Date:  2017-09-13       Impact factor: 49.962

4.  Quantum speedup of Monte Carlo methods.

Authors:  Ashley Montanaro
Journal:  Proc Math Phys Eng Sci       Date:  2015-09-08       Impact factor: 2.704

5.  From transistor to trapped-ion computers for quantum chemistry.

Authors:  M-H Yung; J Casanova; A Mezzacapo; J McClean; L Lamata; A Aspuru-Guzik; E Solano
Journal:  Sci Rep       Date:  2014-01-07       Impact factor: 4.379

6.  Quantum Enhanced Inference in Markov Logic Networks.

Authors:  Peter Wittek; Christian Gogolin
Journal:  Sci Rep       Date:  2017-04-19       Impact factor: 4.379

Review 7.  Quantum machine learning: a classical perspective.

Authors:  Carlo Ciliberto; Mark Herbster; Alessandro Davide Ialongo; Massimiliano Pontil; Andrea Rocchetto; Simone Severini; Leonard Wossnig
Journal:  Proc Math Phys Eng Sci       Date:  2018-01-17       Impact factor: 2.704

8.  A variational eigenvalue solver on a photonic quantum processor.

Authors:  Alberto Peruzzo; Jarrod McClean; Peter Shadbolt; Man-Hong Yung; Xiao-Qi Zhou; Peter J Love; Alán Aspuru-Guzik; Jeremy L O'Brien
Journal:  Nat Commun       Date:  2014-07-23       Impact factor: 14.919

  8 in total

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