熵和扩散之间的关系：Rosenfeld表达式的统计力学推导，用于崎岖的能量景观
Relationship between Entropy and Diffusion: A statistical mechanical derivation of Rosenfeld expression for a rugged energy landscape
摘要：
在许多系统中，扩散（动力学的量度）和熵（系统中无序的量度）被发现是密切相关的，并且这种相关性通常是强非线性的。通过研究一个点布朗粒子在一个凹凸不平的模型势能面上的扩散，我们探索了这种复杂依赖关系的起源。如果我们假设粗糙度具有高斯分布，那么对于这个模型，可以精确地获得任何维度的超额熵。通过使用平均首次通过时间（MFPT）的表达式，我们提出了一个著名的和良好的测试罗森菲尔德之间的扩散和过剩熵的标度关系的统计力学推导。在预期罗森菲尔德扩散熵标度（RDES）关系可能继续有效，在更高的维度（平均首次通过时间的方法是不可用的），我们进行了有效的介质近似（EMA）为基础的分析的有效过渡率，因此有效的扩散系数。我们表明，EMA表达式可以用来推导RDES标度关系的任何维度高于单位。然而，RDES的能源景观值之间的空间相关性的存在下，打破。
英文摘要：
Diffusion-a measure of dynamics, and entropy-a measure of disorder in the system, are found to be intimately correlated in many systems, and the correlation is often strongly non-linear. We explore the origin of this complex dependence by studying diffusion of a point Brownian particle on a model potential energy surface characterized by ruggedness. If we assume that the ruggedness has a Gaussian distribution then for this model, one can obtain the excess entropy exactly for any dimension. By using the expression for the mean first passage time (MFPT), we present a statistical mechanical derivation of the well-known and well-tested scaling relation proposed by Rosenfeld between diffusion and excess entropy. In anticipation that Rosenfeld diffusion-entropy scaling (RDES) relation may continue to be valid in higher dimensions (where the mean first passage time approach is not available), we carry out an effective medium approximation (EMA) based analysis of the effective transition rate, and hence of the effective diffusion coefficient. We show that the EMA expression can be used to derive the RDES scaling relation for any dimension higher than unity. However, RDES is shown to break down in the presence of spatial correlation among the energy landscape values.
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