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arXiv 2110.07573cond-mat.stat-mechmath.PR
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具有全局动力学约束的随机轨迹生成

Generating stochastic trajectories with global dynamical constraints

Benjamin De Bruyne, Satya N. Majumdar, Henri Orland, Gregory Schehr

摘要:

我们提出了一种方法来精确地生成布朗路径$x_c(t)$,这些路径被约束为在未来的某个时间$t_f$返回原点,其轨迹下具有给定的固定区域$A_f = \int_0^{t_f}dt\, x_c(t)$。我们推导出一个精确的有效朗之万方程的有效力,占约束。此外,我们开发了相应的离散时间随机游走的方法,任意跳跃分布,包括Lévy航班,我们得到一个有效的跳跃分布,编码的约束。最后,我们推广我们的方法,以其他类型的动态约束,如固定的占用时间的正轴$T_f=\int_0^{t_f}dt\, Θ\left[x_c(t)\right]$或固定的广义二次面积$\mathcal{A}_f=\int_0^{t_f}dt \,x_c^2(t)$。

英文摘要:

We propose a method to exactly generate Brownian paths $x_c(t)$ that are constrained to return to the origin at some future time $t_f$, with a given fixed area $A_f = \int_0^{t_f}dt\, x_c(t)$ under their trajectory. We derive an exact effective Langevin equation with an effective force that accounts for the constraint. In addition, we develop the corresponding approach for discrete-time random walks, with arbitrary jump distributions including Lévy flights, for which we obtain an effective jump distribution that encodes the constraint. Finally, we generalise our method to other types of dynamical constraints such as a fixed occupation time on the positive axis $T_f=\int_0^{t_f}dt\, Θ\left[x_c(t)\right]$ or a fixed generalised quadratic area $\mathcal{A}_f=\int_0^{t_f}dt \,x_c^2(t)$.

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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