Method for Generating Long-Range Correlations for Large Systems

TL;DR

This paper introduces a novel method for generating long-range correlated random sequences that improves upon existing techniques, enabling better modeling of complex systems with power-law correlations.

Contribution

It presents a new algorithm that overcomes previous limitations in generating long-range correlations for large systems, applicable to various physical models.

Findings

Successfully generates long-range power-law correlations in large systems

Improves upon existing methods for correlation generation

Applicable to models like diffusion, self-affine surfaces, and percolation

Abstract

We propose a new method to generate a sequence of random numbers with long-range power-law correlations that overcomes known difficulties associated with large systems. The new method presents an improvement on the commonly-used methods. We apply the algorithm to generate enhanced diffusion, isotropic and anisotropic self-affine surfaces, and isotropic and anisotropic correlated percolation.