arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1004.0931cond-mat.stat-mechphysics.chem-phphysics.comp-ph
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通过蒙特卡罗分析比较蒙特卡罗效率

Comparative Monte Carlo Efficiency by Monte Carlo Analysis

B. M. Rubenstein, J. E. Gubernatis, J. D. Doll

摘要:

提出了一种计算矩阵或连续算子次优势特征值$λ_2$的改进幂方法。在这里,我们专注于定义简单的蒙特卡罗方法,其应用。提出的方法使用混合符号的随机游动来表示次优势特征函数。因此,这些方法必须适当地消除这些符号,以便忠实地对该特征函数进行采样。我们提出了一个简单的程序来解决这个符号问题,然后通过计算各种马尔可夫链转移矩阵的$λ_2$来测试我们的Monte Carlo方法。我们首先计算${λ_2}$几个一维和二维伊辛模型,其中有一个离散的相空间,并比较了相对效率的大都市和热浴算法作为温度的函数,并施加磁场。其次,我们计算了具有多维连续相空间的相互作用气体模型的$λ_2$,并研究了Metropolis算法的效率与温度和最大允许步长$Δ$的关系。基于$λ_2$标准,我们发现的伊辛模型,小格子似乎给一个足够的图片比较效率和热浴算法是更有效的比大都市算法只有在低温下,这两种算法是低效的。对于谐波陷阱问题,我们发现调整$Δ$使Metropolis接受率在50%左右的传统经验法则通常是次优的。一般而言,作为温度或$Δ$的函数,该模型的$λ_2$显示出定义最佳效率的趋势,而验收比则没有。研究的案例还表明,连续模型的蒙特卡罗模拟可能比离散化模型更有效。

英文摘要:

We propose a modified power method for computing the subdominant eigenvalue $λ_2$ of a matrix or continuous operator. Here we focus on defining simple Monte Carlo methods for its application. The methods presented use random walkers of mixed signs to represent the subdominant eigenfuction. Accordingly, the methods must cancel these signs properly in order to sample this eigenfunction faithfully. We present a simple procedure to solve this sign problem and then test our Monte Carlo methods by computing the $λ_2$ of various Markov chain transition matrices. We first computed ${λ_2}$ for several one and two dimensional Ising models, which have a discrete phase space, and compared the relative efficiencies of the Metropolis and heat-bath algorithms as a function of temperature and applied magnetic field. Next, we computed $λ_2$ for a model of an interacting gas trapped by a harmonic potential, which has a mutidimensional continuous phase space, and studied the efficiency of the Metropolis algorithm as a function of temperature and the maximum allowable step size $Δ$. Based on the $λ_2$ criterion, we found for the Ising models that small lattices appear to give an adequate picture of comparative efficiency and that the heat-bath algorithm is more efficient than the Metropolis algorithm only at low temperatures where both algorithms are inefficient. For the harmonic trap problem, we found that the traditional rule-of-thumb of adjusting $Δ$ so the Metropolis acceptance rate is around 50% range is often sub-optimal. In general, as a function of temperature or $Δ$, $λ_2$ for this model displayed trends defining optimal efficiency that the acceptance ratio does not. The cases studied also suggested that Monte Carlo simulations for a continuum model are likely more efficient than those for a discretized version of the model.

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