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arXiv 2408.00299cond-mat.stat-mech
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使用从属格式模拟连续时间随机游走

Simulation of the continuous-time random walk using subordination schemes

Danhua Jiang, Yuanze Hong, Wanli Wang

AI总结:

本文提出一种利用从属公式在长时间极限下生成连续时间随机游走数据的算法,并通过多种常用观测量验证其结果完全吻合。

摘要:

连续时间随机游走模型已被广泛应用于物理、生物、化学、金融、社会现象等多个领域。在本工作中,我们提出了一种算法,利用从属公式在长时间极限下生成连续时间随机游走的数据。该算法已通过常用观测量进行验证,包括位置分布的典型涨落、稀有涨落、位置的均值和方差,以及具有时间依赖偏置的穿透曲线,结果表明完全吻合。

英文摘要:

The continuous time random walk model has been widely applied in various fields, including physics, biology, chemistry, finance, social phenomena, etc. In this work, we present an algorithm that utilizes a subordinate formula to generate data of the continuous time random walk in the long time limit. The algorithm has been validated using commonly employed observables, such as typical fluctuations of the positional distribution, rare fluctuations, the mean and the variance of the position, and breakthrough curves with time-dependent bias, demonstrating a perfect match.

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。

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