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Physically motivated classical heuristic optimization algorithms such as simulated annealing (SA) treat the objective function as an energy landscape, and allow walkers to escape local minima.
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images
S. Geman and D. Geman · 1984
Earlier work this paper cites.
Nonstationary markov chains and convergence of the annealing algorithm
B. Gidas · 1985
Earlier work this paper cites.
Convergence and finite-time behavior of simulated annealing
D. Mitra, F. Romeo, and A. Sangiovanni-Vincentelli · 1986
Earlier work this paper cites.
Cooling schedules for optimal annealing
B. Hajek · 1988
Earlier work this paper cites.
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Earlier work this paper cites.
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The quantum adiabatic optimization algorithm and local minima
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Earlier work this paper cites.
Bounds for the adiabatic approximation with applications to quantum computation
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Earlier work this paper cites.
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Simulated quantum annealing can be exponentially faster than classical simulated annealing
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The performance of the quantum adiabatic algorithm on spike hamiltonians
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D. Wecker, M. B. Hastings, and M. Troyer · 2016
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