Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2005-12-03
Phys. Rev. B 73, 144302 (2006)
Physics
Condensed Matter
Disordered Systems and Neural Networks
15 pages, 10 figures, REVTex 4
Scientific paper
10.1103/PhysRevB.73.144302
We present results for a variety of Monte Carlo annealing approaches, both classical and quantum, benchmarked against one another for the textbook optimization exercise of a simple one-dimensional double-well. In classical (thermal) annealing, the dependence upon the move chosen in a Metropolis scheme is studied and correlated with the spectrum of the associated Markov transition matrix. In quantum annealing, the Path-Integral Monte Carlo approach is found to yield non-trivial sampling difficulties associated with the tunneling between the two wells. The choice of fictitious quantum kinetic energy is also addressed. We find that a ``relativistic'' kinetic energy form, leading to a higher probability of long real space jumps, can be considerably more effective than the standard one.
Santoro Giuseppe E.
Stella Lorenzo
Tosatti Erio
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