Diffusion Simulation via Green Function Evaluation

IF 1.1 4区 数学 Q1 MATHEMATICS Communications in Mathematics and Statistics Pub Date : 2024-04-23 DOI:10.1007/s40304-023-00384-0
Lin Sun, Shuaishuai Chen, Gang Wei
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Abstract

In the present paper, a scheme of path sampling is explored for stochastic diffusion processes. The core issue is the evaluation of the diffusion propagators (spatial–temporal Green functions) by solving the corresponding Kolmogorov forward equations with Dirac delta functions as initials. The technique can be further used in evaluating general functional of path integrals. The numerical experiments demonstrated that the simulation scheme based on this approach overwhelms the popular Euler scheme and Exact Algorithm in terms of accuracy and efficiency in fairly general settings. An example of likelihood inference for the diffusion driven Cox process is provided to show the scheme’s potential power in applications.

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通过绿色函数评估进行扩散模拟
本文探讨了随机扩散过程的路径采样方案。核心问题是以 Dirac delta 函数为初始,通过求解相应的 Kolmogorov 正向方程来评估扩散传播者(时空格林函数)。该技术可进一步用于评估路径积分的一般函数。数值实验表明,在相当普遍的情况下,基于这种方法的模拟方案在精确度和效率上都压倒了流行的欧拉方案和精确算法。我们还提供了一个扩散驱动考克斯过程的似然推理实例,以展示该方案在应用中的潜在能力。
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来源期刊
Communications in Mathematics and Statistics
Communications in Mathematics and Statistics Mathematics-Statistics and Probability
CiteScore
1.80
自引率
0.00%
发文量
36
期刊介绍: Communications in Mathematics and Statistics is an international journal published by Springer-Verlag in collaboration with the School of Mathematical Sciences, University of Science and Technology of China (USTC). The journal will be committed to publish high level original peer reviewed research papers in various areas of mathematical sciences, including pure mathematics, applied mathematics, computational mathematics, and probability and statistics. Typically one volume is published each year, and each volume consists of four issues.
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