Quantum Spin Glass in the Two-Dimensional Disordered Heisenberg Model via Foundation Neural-Network Quantum States

TL;DR

This paper uses neural network quantum states to study a disordered 2D quantum Heisenberg model, revealing a stable quantum spin glass phase that persists despite quantum fluctuations, contrasting classical behavior.

Contribution

It introduces a neural network-based variational approach to analyze the quantum spin glass phase in a disordered 2D Heisenberg model, demonstrating the phase's stability against quantum fluctuations.

Findings

Identification of a stable quantum spin glass phase in 2D

Long-range magnetic order vanishes in the thermodynamic limit

Quantum spin glass persists despite quantum fluctuations

Abstract

We investigate the two-dimensional frustrated quantum Heisenberg model with bond disorder on nearest-neighbor couplings using the recently introduced Foundation Neural-Network Quantum States framework, which enables accurate and efficient computation of disorder-averaged observables with a single variational optimization. Simulations on large lattices reveal an extended region of the phase diagram where long-range magnetic order vanishes in the thermodynamic limit, while the overlap order parameter, which characterizes quantum spin glass states, remains finite. These findings, supported by a semiclassical analysis based on a large-spin expansion, provide compelling evidence that the spin glass phase is stable against quantum fluctuations, unlike the classical case where it disappears at any finite temperature.