论文标题
指数尾巴和不对称关系,以传播有偏见的随机步行
Exponential Tails and Asymmetry Relations for the Spread of Biased Random Walks
论文作者
论文摘要
在他对错误分析的背景下,Laplace研究了指数型函数的衰减,而不是高斯。最近在众多实验系统中观察到了这种拉普拉斯传播器,用于无序培养基中单个颗粒的扩散运动。当施加外部驱动力时,这种普遍性会发生什么?使用无处不在的连续时间随机随机随机随机行走,并与大偏差理论结合使用骗子的关系,我们得出了位置概率密度函数$ p_f(x,t)$的两种属性,这些属性适用于各种随机步行模型:(i)通用的不对称的指数衰减,以$ p_f(x,x,x,x,x,x,x,x,x,x | | | | | | | | | | $ | x | $允许在无偏过程的传播器(在较短的时间)中表达$ p_f(x,t)$。这些发现使我们能够确定在许多无偏过程中测量的对称指数状的尾巴如何在施加外力时会转变为不对称的拉普拉斯尾巴。
Exponential, and not Gaussian, decay of probability density functions was studied by Laplace in the context of his analysis of errors. Such Laplace propagators for the diffusive motion of single particles in disordered media were recently observed in numerous experimental systems. What will happen to this universality when an external driving force is applied? Using the ubiquitous continuous time random walk with bias, and the Crooks relation in conjunction with large deviations theory, we derive two properties of the positional probability density function $P_F(x,t)$ that hold for a wide spectrum of random walk models: (I) Universal asymmetric exponential decay of $P_F(X,t)$ for large $|X|$, and (II) Existence of a time transformation that for large $|X|$ allows to express $P_F(X,t)$ in terms of the propagator of the unbiased process (measured at a shorter time). These findings allow us to establish how the symmetric exponential-like tails, measured in many unbiased processes, will transform into asymmetric Laplace tails when an external force is applied.