探测宏观自旋液体预选拓扑扇区内的空间与时间磁关联
Probing magnetic correlations in space and time within predefined topological sectors of a macroscopic spin liquid
浏览论文内容
中文总结 AI 辅助
通过宏观人工三角伊辛反铁磁体实验，验证了极低能物理与真实基态可达性，并在预选基态区域探测磁性质，模拟拓扑扇区行为，开辟多体现象可视化新途径。
中文摘要 AI 辅助
三角伊辛反铁磁体，以其在绝对零度下的残余熵密度和临界关联，是二维自旋液体的原型。其基态被划分为由环绕晶格边界的全局自旋翻转事件连接的拓扑扇区，这些事件在热力学极限下变得统计上无关紧要，此时磁涨落被限制在主导扇区内。迄今为止，这些性质主要从理论角度进行研究，人们可能想知道它们在多大程度上可以移植到真实材料中。在这里，我们展示了在人工的、宏观尺度的三角伊辛反铁磁体实现中获得的实验观测结果，该实现由毫米级NdFeB圆柱体组成的晶格构成，这些圆柱体通过机械振动器驱动运动。具体而言，我们证明了该模型的极低能物理和真实基态可以在实验上达到。此外，我们能够在空间和时间上探测基态流形中手动预选区域内的磁性质，这些区域在良好近似下模拟了不同拓扑扇区中的行为。我们的方法为裸眼可视化和手动操控与受挫磁性及统计物理模型相关的多体现象开辟了新途径。
英文摘要
The triangular Ising antiferromagnet, with its residual entropy density and critical correlations at absolute zero, is the archetype of a two-dimensional spin liquid. Its ground state is partitioned into topological sectors connected by global spin flip events that wrap the lattice boundaries, and become statistically irrelevant in the thermodynamic limit where magnetic fluctuations are restricted to the dominant sector. Thus far, these properties have been mainly investigated from a theoretical perspective, and one might wonder to what extent they can be transposed to real materials. Here, we present experimental observations obtained in an artificial, macroscopic realisation of the seminal triangular Ising antiferromagnet that consists of a lattice of millimeter-sized NdFeB cylinders put into motion by a mechanical shaker. Specifically, we demonstrate that the very-low-energy physics and the true ground state of this model can be reached experimentally. Besides, we are able to probe, in space and time, the magnetic properties within manually preselected pockets of the ground-state manifold that emulate, to a good approximation, the behaviour in distinct topological sectors. Our approach opens new avenues for naked-eye visualisation and hand manipulation of many-body phenomena associated to frustrated magnetism and models of statistical physics.
发表机构
- Université Grenoble Alpes, CNRS, Institut NEEL, Grenoble INP（格勒诺布尔阿尔卑斯大学，法国国家科学研究中心，NEEL研究所，格勒诺布尔理工学院）
机构由 AI 辅助整理，请以论文原文为准。
