Gibbs sampling of complex-valued distributions
Gibbs sampling of complex-valued distributions
复制标题
复值分布的吉布斯采样
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
L. L. Salcedo
中科院分区：
文献类型：
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作者：
L. L. Salcedo
探索了复值分布蒙特卡罗抽样的一种新方法。该方法基于热浴法，用复平面上条件概率的正表示来代替条件概率。文中还介绍了构造这种表示的有效方法。在小格子和大格子上用二次最近邻复耦合的$lambdaphi^4$理论测试了算法的性能。该方法适用于中等复杂的耦合，重现重权和复朗之万结果，并满足各种Schwinger-Dyson关系。
A new technique is explored for the Monte Carlo sampling of complex-valued distributions. The method is based on a heat bath approach where the conditional probability is replaced by a positive representation of it on the complex plane. Efficient ways to construct such representations are also introduced. The performance of the algorithm is tested on small and large lattices with a $lambdaphi^4$ theory with quadratic nearest-neighbor complex coupling. The method works for moderate complex couplings, reproducing reweighting and complex Langevin results and fulfilling various Schwinger-Dyson relations.
随机量化可以避免符号问题吗？
影响因子：
8.6
作者：
Aarts G
通讯作者：
Aarts G