Quantum annealing: A new method for minimizing multidimensional functions

Finnila, Aleta; Gomez, Maria A.; Sebenik, C.; Stenson, C.; Doll, J. D.

doi:10.1016/0009-2614(94)00117-0

Cited by 645 publications

(562 citation statements)

References 11 publications

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“…Quantum Annealing (QA) [1][2][3][4] -essentially equivalent to a form of quantum computation known as Adiabatic Quantum Computation (AQC) 5 -was originally introduced as an alternative to classical simulated annealing 6 for optimization and has become a very active field of research in the last few years, due to the availability of QA programmable machines based on superconducting flux quantum bits 7,8 .…”

Section: Introductionmentioning

confidence: 99%

Dissipative Landau-Zener problem and thermally assisted Quantum Annealing

et al. 2017

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We revisit here the issue of thermally assisted Quantum Annealing by a detailed study of the dissipative Landau-Zener problem in presence of a Caldeira-Leggett bath of harmonic oscillators, using both a weak-coupling quantum master equation and a quasi-adiabatic path-integral approach. Building on the known zero-temperature exact results (Wubs et al., PRL 97, 200404 (2006)), we show that a finite temperature bath can have a beneficial effect on the ground-state probability only if it couples also to a spin-direction that is transverse with respect to the driving field, while no improvement is obtained for the more commonly studied purely longitudinal coupling. In particular, we also highlight that, for a transverse coupling, raising the bath temperature further improves the ground-state probability in the fast-driving regime. We discuss the relevance of these findings for the current quantum-annealing flux qubit chips.

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Section: Introductionmentioning

confidence: 99%

Dissipative Landau-Zener problem and thermally assisted Quantum Annealing

et al. 2017

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“…The realization of QA consists of employing adjustable quantum fluctuations into the problem instead of a thermal one (Kadowaki and Nishimori 1998, Amara et al 1993, Finnila et al 1994). In order to do that, one needs to introduce an artificial quantum kinetic term Γ(t)H kin , which does not commute with the classical Hamiltonian H C representing the cost function.…”

Section: Quantum Annealingmentioning

confidence: 99%

Colloquium: Quantum annealing and analog quantum computation

2008

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We review here the recent success in quantum annealing, i.e., optimization of the cost or energy functions of complex systems utilizing quantum fluctuations. The concept is introduced in successive steps through the studies of mapping of such computationally hard problems to the classical spin glass problems. The quantum spin glass problems arise 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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“…This has spurred the arrival of alternative quantum computing devices that sacrifice universality in order to allow for more rapid progress and thus hopefully usher in the era of quantum computing, albeit for a limited set of computational tasks, such as quantum simulation [3][4][5]. Another example is quantum annealing [6][7][8][9][10][11], an analog quantum approach for solving optimization problems [12,13], that may offer a quicker route than the standard circuit model towards the demonstration of the utility of quantum computation. The task addressed by quantum annealing is the well-known NPhard problem of solving for the ground state of a classical Ising Hamiltonian [14],…”

Section: Introductionmentioning

confidence: 99%

Performance of two different quantum annealing correction codes

Mishra

Albash

Lidar

2015

Quantum Inf Process

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Quantum annealing is a promising approach for solving optimization problems, but like all other quantum information processing methods, it requires error correction to ensure scalability. In this work we experimentally compare two quantum annealing correction codes in the setting of antiferromagnetic chains, using two different quantum annealing processors. The lower temperature processor gives rise to higher success probabilities. The two codes differ in a number of interesting and important ways, but both require four physical qubits per encoded qubit. We find significant performance differences, which we explain in terms of the effective energy boost provided by the respective redundantly encoded logical operators of the two codes. The code with the higher energy boost results in improved performance, at the expense of a lower degree encoded graph. Therefore, we find that there exists an important tradeoff between encoded connectivity and performance for quantum annealing correction codes.

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Quantum annealing: A new method for minimizing multidimensional functions

Cited by 645 publications

References 11 publications

Dissipative Landau-Zener problem and thermally assisted Quantum Annealing

Dissipative Landau-Zener problem and thermally assisted Quantum Annealing

Colloquium: Quantum annealing and analog quantum computation

Performance of two different quantum annealing correction codes

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