马尔可夫链生成的离散化及其在多重正则方法中的应用
Parallelization of Markov chain generation and its application to the multicanonical method
摘要：
我们开发了一个简单的算法来并行化马尔可夫链的生成过程。在该算法中，多个马尔可夫链并行生成，并连接在一起，使一个更长的马尔可夫链。使用细致平衡来处理组成马尔可夫链之间的连接。我们将并行化算法应用于二维伊辛模型的多规范计算，并证明了多规范权重的准确估计。
英文摘要：
We develop a simple algorithm to parallelize generation processes of Markov chains. In this algorithm, multiple Markov chains are generated in parallel and jointed together to make a longer Markov chain. The joints between the constituent Markov chains are processed using the detailed balance. We apply the parallelization algorithm to multicanonical calculations of the two-dimensional Ising model and demonstrate accurate estimation of multicanonical weights.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
