Abstract

This paper examines a range of results that can be derived from Einstein’s evolution equation focusing on the effect of introducing a Lévy distribution into the evolution equation. In this context, we examine the derivation (derived exclusively from the evolution equation) of the classical and fractional diffusion equations, the classical and generalised Kolmogorov–Feller equations, the evolution of self-affine stochastic fields through the fractional diffusion equation, the fractional Poisson equation (for the time independent case), and, a derivation of the Lyapunov exponent and volatility. In this way, we provide a collection of results (which includes the derivation of certain fractional partial differential equations) that are fundamental to the stochastic modelling associated with elastic scattering problems obtained under a unifying theme, i.e., Einstein’s evolution equation. This includes an analysis of stochastic fields governed by a symmetric (zero-mean) Gaussian distribution, a Lévy distribution characterised by the Lévy index γ ∈ [ 0 , 2 ] and the derivation of two impulse response functions for each case. The relationship between non-Gaussian distributions and fractional calculus is examined and applications to financial forecasting under the fractal market hypothesis considered, the reader being provided with example software functions (written in MATLAB) so that the results presented may be reproduced and/or further investigated.

Highlights

  • We study one of the principal field equations in statistical mechanics, namely, Einstein’s evolution equation (EEE or E3)

  • From these results it is clear that the accuracy improves significantly with the extent of the pre-filtering that is applied to the time series before computation of the Lyapunov-to-volatility ratio (LVR)

  • We show how the classical diffusion equation is a result of considering a Gaussian probability density function (PDF) in E3 and the non-classical fractional diffusion equation is the result of considering a non-Gaussian PDF, in particular, a Lévy distribution and undertaken using the associated characteristic functions

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Summary

Introduction

We study one of the principal field equations in statistical mechanics, namely, Einstein’s evolution equation (EEE or E3). E3 models the random motion and (elastic) interactions of a canonical ensemble of particles It provides a description for the time evolution of the spatial density field that represents the concentration of such particles in a macroscopic sense. The scattering angle θ is taken to be conform to a distribution of angles Pr[θ(r)], r ∈ Rn and the (free) propagation length is taken to conform to some distribution of lengths Pr[L(r)] whose mean value defines the mean free path (MFP). This was the basis for Albert Einstein’s original study of Brownian motion in 1905 [1], albeit for the one-dimensional case

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