Literature DB >> 32235066

Perspectives of quantum annealing: methods and implementations.

Philipp Hauke1, Helmut G Katzgraber, Wolfgang Lechner, Hidetoshi Nishimori, William D Oliver.   

Abstract

Quantum annealing is a computing paradigm that has the ambitious goal of efficiently solving large-scale combinatorial optimization problems of practical importance. However, many challenges have yet to be overcome before this goal can be reached. This perspectives article first gives a brief introduction to the concept of quantum annealing, and then highlights new pathways that may clear the way towards feasible and large scale quantum annealing. Moreover, since this field of research is to a strong degree driven by a synergy between experiment and theory, we discuss both in this work. An important focus in this article is on future perspectives, which complements other review articles, and which we hope will motivate further research.

Year:  2020        PMID: 32235066     DOI: 10.1088/1361-6633/ab85b8

Source DB:  PubMed          Journal:  Rep Prog Phys        ISSN: 0034-4885


  6 in total

Review 1.  Practical quantum advantage in quantum simulation.

Authors:  Andrew J Daley; Immanuel Bloch; Christian Kokail; Stuart Flannigan; Natalie Pearson; Matthias Troyer; Peter Zoller
Journal:  Nature       Date:  2022-07-27       Impact factor: 69.504

2.  Analytical solution for nonadiabatic quantum annealing to arbitrary Ising spin Hamiltonian.

Authors:  Bin Yan; Nikolai A Sinitsyn
Journal:  Nat Commun       Date:  2022-04-25       Impact factor: 14.919

3.  QuASeR: Quantum Accelerated de novo DNA sequence reconstruction.

Authors:  Aritra Sarkar; Zaid Al-Ars; Koen Bertels
Journal:  PLoS One       Date:  2021-04-12       Impact factor: 3.240

4.  Sampling electronic structure quadratic unconstrained binary optimization problems (QUBOs) with Ocean and Mukai solvers.

Authors:  Alexander Teplukhin; Brian K Kendrick; Susan M Mniszewski; Sergei Tretiak; Pavel A Dub
Journal:  PLoS One       Date:  2022-02-11       Impact factor: 3.240

5.  Lossy compression of statistical data using quantum annealer.

Authors:  Boram Yoon; Nga T T Nguyen; Chia Cheng Chang; Ermal Rrapaj
Journal:  Sci Rep       Date:  2022-03-09       Impact factor: 4.379

6.  Sampling rare conformational transitions with a quantum computer.

Authors:  Danial Ghamari; Philipp Hauke; Roberto Covino; Pietro Faccioli
Journal:  Sci Rep       Date:  2022-09-29       Impact factor: 4.996

  6 in total

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