有偏置的 metropolis 算法的应用：从质子到蛋白质。
Application of Biased Metropolis Algorithms: From protons to proteins.
作者信息
Bazavov Alexei, Berg Bernd A, Zhou Huan-Xiang
机构信息
Department of Physics, Florida State University, Tallahassee, FL 32306-4350, United States ; School of Computational Science, Florida State University, Tallahassee, FL 32306-4120, United States.
Department of Physics, Florida State University, Tallahassee, FL 32306-4350, United States ; School of Computational Science, Florida State University, Tallahassee, FL 32306-4120, United States ; Institute of Molecular Biophysics, Florida State University, Tallahassee, FL 32306-4380, United States.
出版信息
Math Comput Simul. 2010 Feb;80(6):1056-1067. doi: 10.1016/j.matcom.2009.05.005.
We show that sampling with a biased Metropolis scheme is essentially equivalent to using the heatbath algorithm. However, the biased Metropolis method can also be applied when an efficient heatbath algorithm does not exist. This is first illustrated with an example from high energy physics (lattice gauge theory simulations). We then illustrate the Rugged Metropolis method, which is based on a similar biased updating scheme, but aims at very different applications. The goal of such applications is to locate the most likely configurations in a rugged free energy landscape, which is most relevant for simulations of biomolecules.
我们表明，使用有偏的 metropolis 方案进行采样本质上等同于使用热浴算法。然而，当不存在高效的热浴算法时，有偏的 metropolis 方法也可以应用。这首先通过高能物理（晶格规范理论模拟）中的一个例子来说明。然后我们阐述了崎岖 metropolis 方法，它基于类似的有偏更新方案，但针对的是非常不同的应用。此类应用的目标是在崎岖的自由能景观中找到最可能的构型，这与生物分子模拟最为相关。
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