Statistical mechanics of Monte Carlo sampling and the sign problem.
Monte Carlo sampling of any system may be analyzed in terms of an associated glass model - a variant of the Random Energy Model - with, whenever there is a sign problem, complex fields. This model has three types of phases (liquid, frozen and chaotic), as it, characteristic of glass models with complex parameters. Only the liquid one yields the correct answers for the original problem, and the task, is to design the simulation to stay inside it. The statistical convergence of the sampling to the correct expectation values may be studied in these terms, yielding a general lower bound for the computer time as a function of the free energy difference between the true system, and a reference one. In this way, importance-sampling strategies may be optimized.
Gustavo Duering Jorge Kurchan
Lahnralairr de Physique Statistique, Ecole Normale Suptrieare, UPMC Univ Paris 06. Univeni: Puris Di PMMH. ESPCl, 10 rue Vuuquelin, CNRS UMR 7636 . Paris, France 75005
国际会议
International Workshop on Statistical Physics and Computer Sciences(统计物理与计算机科学交叉研究国际研讨会 )
北京
英文
78-81
2010-07-08（万方平台首次上网日期，不代表论文的发表时间）