Statistical mechanics of a single particle in a multiscale random potential: Parisi landscapes in finite dimensional Euclidean spaces

TL;DR

This paper constructs a multiscale Gaussian landscape in high dimensions and analyzes the statistical mechanics of a particle within it, revealing connections to Parisi's replica symmetry breaking and Derrida's GREM.

Contribution

It introduces a multiscale, translation-invariant Gaussian landscape model and derives exact solutions for free energy and overlap functions using replica methods.

Findings

Exact free energy and overlap functions in high dimensions

Identification of K-step replica symmetry breaking for K discrete scales

Connection to Derrida's GREM and implications for multifractality

Abstract

We construct a N-dimensional Gaussian landscape with multiscale, translation invariant, logarithmic correlations and investigate the statistical mechanics of a single particle in this environment. In the limit of high dimension N>>1 the free energy of the system and overlap function are calculated exactly using the replica trick and Parisi's hierarchical ansatz. In the thermodynamic limit, we recover the most general version of the Derrida's Generalized Random Energy Model (GREM). The low-temperature behaviour depends essentially on the spectrum of length scales involved in the construction of the landscape. If the latter consists of K discrete values, the system is characterized by a K-step Replica Symmetry Breaking solution. We argue that our construction is in fact valid in any finite spatial dimensions $N\ge 1$. We discuss implications of our results for the singularity spectrum describing multifractality of the associated Boltzmann-Gibbs measure. Finally we discuss several generalisations and open problems, the dynamics in such a landscape and the construction of a Generalized Multifractal Random Walk.