Nearest-Neighbor Functions for Disordered Stealthy Hyperuniform Many-Particle Systems

TL;DR

This paper derives analytical formulas for the nearest-neighbor functions of disordered stealthy hyperuniform systems, compares their behavior to crystalline lattices, and discusses implications for hole size probabilities and sampling challenges.

Contribution

It introduces new analytical formulas and theoretical insights for understanding nearest-neighbor functions in disordered stealthy hyperuniform systems, extending previous knowledge.

Findings

Bounded hole sizes in stealthy systems.

Disordered systems have rarer large holes than ordered ones.

New analytical formula for underconstrained regimes.

Abstract

Disordered stealthy many-particle systems in $\mathbb{R}^d$ are exotic states of matter that suppress single scattering events for a finite range of wavenumbers around the origin in reciprocal space. We derive analytical formulas for the nearest-neighbor functions of disordered stealthy systems. First, we analyze asymptotic small-$r$ approximations and bounding expressions of the nearest-neighbor functions based on the pseudo-hard-sphere ansatz. We then determine how many of the standard $n$-point correlation functions are needed to determine the nearest neighbor functions, and find that a finite number suffice. Via theoretical and computational methods, we compare the large-$r$ behavior of these functions for disordered stealthy systems to those belonging to crystalline lattices. Such ordered and disordered stealthy systems have bounded hole sizes. However, we find that the approach to the critical-hole size can be quantitatively different. We argue that the probability of finding a hole close to the critical-hole size should decrease as a power law with an exponent only dependent on the space dimension $d$ for ordered systems, but that this probability decays asymptotically faster for disordered systems. This implies that holes close to the critical-hole size are rarer in disordered systems. The rarity of observing large holes in disordered systems creates substantial numerical difficulties in sampling the nearest neighbor distributions near the critical-hole size. This motivates both the need for new computational methods for efficient sampling and the development of novel theoretical methods. We also devise a simple analytical formula that accurately describes these systems in the underconstrained regime for all $r$. These results provide a foundation for the analytical description of the nearest-neighbor functions of stealthy systems in the disordered, underconstrained regime.