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Cited by 700Quantum Computing Algorithms and ArchitectureQuantum many-body systemsTheoretical and Computational Physics

Colloquium : Quantum annealing and analog quantum computation

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Das, Arnab, Chakrabarti, Bikas K.·2008·Reviews of Modern Physics
DOI 10.1103/revmodphys.80.1061
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Abstract

The recent success in quantum annealing, i.e., optimization of the cost or energy functions of complex systems utilizing quantum fluctuations is reviewed here. The concept is introduced in successive steps through studying the mapping of such computationally hard problems to classical spin-glass problems, quantum spin-glass problems arising with the introduction of quantum fluctuations, and the annealing behavior of the systems as these fluctuations are reduced slowly to zero. This provides a general framework for realizing analog quantum computation.

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  • Mean field, DFT, and DMFT have limitations, for example they are essentially designed for weakly correlated systems.

    “Mean field [85], DFT [86, 87], or DMFT [88], finally, have other limitations, e.g., they are essentially designed for weakly-correlated systems.”

    From Can one trust quantum simulators? (2012) · cites this paper as [88]

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Research works printed but not linked: 11

  1. Apolloni, B., C. Carvalho, and D. de Falco, 1989, Stochastic Proc. Appl. 33, 233.
  2. Battaglia, D. A., L. Stella, O. Zagordi, G. E. Santoro, and E. Tosatti, 2005, in Quantum Annealing and Related Optimiza- tion Methods, edited by A. Das and B. K. Chakrabarti, Lec- ture Notes in Physics No. 679 ͑Springer-Verlag, Heidelberg͒, pp. 171-204.
  3. Bearwood, J., J. H. Halton, and J. H. Hammersley, 1959, Proc. Cambridge Philos. Soc. 55, 299.
  4. Das, A., 2007, unpublished ͑see also Ph.D. thesis, Jadavpur University, Kolkata, 2008͒.
  5. Das, A., and B. K. Chakrabarti, 2005, Eds., Quantum Anneal- ing and Related Optimization Methods, Lecture Notes in Physics No. 679 ͑Springer-Verlag, Heidelberg͒.
  6. Geman, S., and D. Geman, 1984, IEEE Trans. Pattern Anal. Mach. Intell. 6, 721.
  7. Hartmann, A., and H. Rieger, 2002, Optimization in Physics ͑Wiley VCH, Darmstadt͒.
  8. Inoue, J.-I., 2005, in Quantum Annealing and Related Optimi- zation Methods, edited by A. Das and B. K. Chakrabarti, Lecture Notes in Physics No. 679 ͑Springer-Verlag, Heidel- berg͒, pp. 259-296.
  9. Mezard, M., G. Parisi, and M. A. Virasoro, 1987, Spin Glass Theory and Beyond, Lecture Note in Physics No. 9 ͑World Scientific, Singapore͒, and references therein.
  10. Rieger, H., 2005, in Quantum Annealing and Related Optimi- zation Methods, edited by A. Das and B. K. Chakrabarti, Lecture Notes in Physics No. 679 ͑Springer-Verlag, Heidel- berg͒, pp. 69-97.
  11. Suzuki, S., and M. Okada, 2005b, in Quantum Annealing and Related Optimization Methods, edited by A. Das and B. K. Chakrabarti, Lecture Notes in Physics No. 679 ͑Springer- Verlag, Heidelberg͒.

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Authors
Das, A., & Chakrabarti, B. K.
Affiliations
Saha Institute of Nuclear Physics (IN)
ORCID
Venue
Reviews of Modern Physics
Publisher
American Physical Society (APS)
Published
2008-09-05
Volume
80
Issue
3
Pages
1061-1081
ISSN
  • 0034-6861 (ISSN-L)
  • 1539-0756
DOI
10.1103/revmodphys.80.1061
OpenAlex
W174492123
Cited by
700
References
93
Citations by year
2026: 40 · 2025: 72 · 2024: 54 · 2023: 60 · 2022: 64 · 2021: 62 · 2020: 52 · 2019: 44 · 2018: 44 · 2017: 34 · 2016: 45 · 2015: 34 · 2014: 22 · 2013: 12 · 2012: 19
FWCI
22.16
Type
journal article
Language
en
Open access
Licence
link.aps.org/licenses/aps-default-license (vor)
Locations
  • Reviews of Modern Physics (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • HAL (submittedVersion, other-oa)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
  • Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Theoretical and Computational Physics
Keywords
quantum annealing, quantum fluctuations, spin glass, quantum spin glass, combinatorial optimization, annealing behavior

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