Non-Gaussian tail in the force distribution: A hallmark of correlated disorder in the host media of elastic objects

TL;DR

This paper introduces a method to identify the dominant type of disorder in media hosting elastic objects by analyzing the distribution of interaction forces, revealing non-Gaussian tails as signatures of correlated disorder.

Contribution

The study demonstrates that force distribution tails can distinguish between point-like and correlated disorder in vortex systems, providing a new diagnostic tool.

Findings

Gaussian force distributions in point-disordered media

Non-Gaussian algebraic tails in media with correlated disorder

Force distribution analysis as a fingerprint of disorder type

Abstract

Inferring the nature of disorder in the media where elastic objects are nucleated is of crucial importance for many applications but remains a challenging basic-science problem. Here we propose a method to discern whether weak-point or strong-correlated disorder dominates based on characterizing the distribution of the interaction forces between objects mapped in large fields-of-view. We illustrate our proposal with the case-study system of vortex structures nucleated in type-II superconductors with different pinning landscapes. Interaction force distributions are computed from individual vortex positions imaged in thousands-vortices fields-of-view in a two-orders-of-magnitude-wide vortex-density range. Vortex structures nucleated in point-disordered media present Gaussian distributions of the interaction force components. In contrast, if the media have dilute and randomly-distributed correlated disorder, these distributions present non-Gaussian algebraically-decaying tails for large force magnitudes. We propose that detecting this deviation from the Gaussian behavior is a fingerprint of strong disorder, in our case originated from a dilute distribution of correlated pinning centers.