# Stochastic Tools Hidden Behind the Empirical Dielectric Relaxation Laws

## TL;DR

This paper reviews stochastic modeling techniques for dielectric relaxation in disordered systems, highlighting their ability to explain universal kinetic patterns across various complex materials.

## Contribution

It introduces recent stochastic tools and probabilistic models that analyze the relaxation phenomena and their universal features in complex disordered systems.

## Key findings

- Stochastic models explain universal dielectric relaxation patterns.
- Diffusion and tempered processes provide insights into anomalous dynamics.
- Relationships among stochastic approaches enhance understanding of relaxation mechanisms.

## Abstract

The paper is devoted to recent advances in stochastic modeling of anomalous kinetic processes observed in dielectric materials which are prominent examples of disordered (complex) systems. Theoretical studies of dynamical properties of those "structures with variations" [Goldenfield and Kadanoff 1999 Science 284 87--9] require application of such mathematical tools by means of which their random nature can be analyzed and, independently of the details differing various systems (dipolar materials, glasses, semiconductors, liquid crystals, polymers, etc.), the empirical universal kinetic patterns can be derived. We begin with a brief survey of the historical background of the dielectric relaxation study. After a short outline of the theoretical ideas providing the random tools applicable to modeling of relaxation phenomena, we present probabilistic implications for the study of the relaxation-rate distribution models. In the framework of the probability distribution of relaxation rates we consider description of complex systems, in which relaxing entities form random clusters interacting with each other and single entities. Then we focus on stochastic mechanisms of the relaxation phenomenon. We discuss the diffusion approach and its usefulness for understanding of anomalous dynamics of the relaxing systems. We also discuss extensions of the diffusive approach to the systems under tempered random processes. Useful relationships among different stochastic approaches to the anomalous dynamics of complex systems allow us to get a fresh look on this subject. The paper closes with a final discussion on achievements of stochastic tools describing the anomalous time evolution of the complex systems.