Titlebook: Quantum Annealing and Related Optimization Methods; Arnab Das,Bikas Chakrabarti Book 2005 Springer-Verlag Berlin Heidelberg 2005 combinato

极小

Deterministic and Stochastic Quantum Annealing Approaches,g a certain cost (or energy) function in a large configuration space is tackled by the introduction of a fictitious temperature, which is slowly lowered in the course of a Monte Carlo or Molecular Dynamics simulation [1]. This device allows an exploration of the configuration space of the problem at

Repetitions

战役

外形

Quantum Spin Glasses Quantum Annealing, and Probabilistic Information Processing,2–4] and references therein) and error-correcting codes [5] are most suitable subjects. In the field of error-correcting codes, Sourlas [5] showed that the convolution codes can be constructed by an infinite range spin-glass Hamiltonian and the decoded message should correspond to the zero temperatu

铁塔等

Combinatorial Optimization and the Physics of Disordered Systems,ve interesting applications in the physics of disordered systems. These are solid materials which contain a substantial degree of quenched disorder, have been an experimental and a theoretical challenge for physicists for many decades. The different thermodynamic phases emerging in random magnets, t

Malfunction

Dynamical Frustration in ANNNI Model and Annealing, with many spurious minima. There are certain other systems, however, which have very simple energy landscape picture and ground states, but still the system fails to reach its ground state during a energy-lowering dynamical process. This situation corresponds to “dynamical frustration ”. We have sp

AER

ARK

Deterministic and Stochastic Quantum Annealing Approaches, hand, effectively avoiding trapping at unfavorable local minima through thermal hopping above energy barriers. It makes for a very robust and effective minimization tool, often much more effective than standard, gradient-based, minimization methods.

心胸开阔

Exploring Complex Landscapes with Classical Monte Carlo,uld say that Nature is trying to solve an Optimization problem: the variables to play with are the atomic positions, while the cost function to be minimized is the potential energy. The configuration that minimizes the cost function is the perfect crystal, and a slow annealing schedule allows Nature to find good crystals.

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