Abstract

We present new connections among linear anomalous diffusion (AD), normal diffusion (ND) and the Central Limit Theorem (CLT). This is done by defining a point transformation to a new position variable, which we postulate to be Cartesian, motivated by considerations from super-symmetric quantum mechanics. Canonically quantizing in the new position and momentum variables according to Dirac gives rise to generalized negative semi-definite and self-adjoint Laplacian operators. These lead to new generalized Fourier transformations and associated probability distributions, which are form invariant under the corresponding transform. The new Laplacians also lead us to generalized diffusion equations, which imply a connection to the CLT. We show that the derived diffusion equations capture all of the Fractal and Non-Fractal Anomalous Diffusion equations of O’Shaughnessy and Procaccia. However, we also obtain new equations that cannot (so far as we can tell) be expressed as examples of the O’Shaughnessy and Procaccia equations. The results show, in part, that experimentally measuring the diffusion scaling law can determine the point transformation (for monomial point transformations). We also show that AD in the original, physical position is actually ND when viewed in terms of displacements in an appropriately transformed position variable. We illustrate the ideas both analytically and with a detailed computational example for a non-trivial choice of point transformation. Finally, we summarize our results.

Highlights

  • The Central Limit Theorem (CLT) is closely related to the “normal diffusion” (ND) process and is relevant to many random processes [1] [2] [3] [4] [5]

  • We present new connections among linear anomalous diffusion (AD), normal diffusion (ND) and the Central Limit Theorem (CLT)

  • We show that the derived diffusion equations capture all of the Fractal and Non-Fractal Anomalous Diffusion equations of O’Shaughnessy and Procaccia

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Summary

Introduction

The Central Limit Theorem (CLT) is closely related to the “normal diffusion” (ND) process and is relevant to many random processes [1] [2] [3] [4] [5]. The CLT together with the assumed zero mean and independence of increments implies that regardless of the microscopic model, the transition probability at large scales is well approximated by a Gaussian [6]. We postulate the fact that these are computationally observed to be attractor solutions of the relevant differential equations implies that the standard CLT is “hidden” and applies to AD associated with the diffusion equations we derive.

Kouri et al DOI
Anomalous Diffusion and Normal Diffusion
A Computational Example for the Polynomial
Conclusions
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