标题： 二维无序海森堡模型中的量子自旋玻璃通过基础神经网络量子态 显示英文标题

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

摘要： 我们使用最近引入的Foundation Neural-Network Quantum States框架，研究了具有最近邻耦合键无序的二维受挫量子海森堡模型，该框架能够通过一次变分优化准确且高效地计算无序平均可观测量。在大晶格上的模拟揭示了相图中一个扩展区域，在热力学极限下长程磁序消失，而表征量子自旋玻璃态的重叠序参数保持有限。这些发现得到了基于大自旋展开的半经典分析的支持，提供了有力的证据表明，自旋玻璃相在量子涨落下是稳定的，这与经典情况下在任何有限温度下自旋玻璃相消失的情况不同。 显示英文摘要

摘要： 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.