Path Integral Quantum Spin Dynamics

磁性材料对于技术应用特别重要。在过去的50年里，它们一直被用作计算机数据存储的主要来源，促进了计算和互联网的大规模扩张。自旋电子学等较新的领域希望利用磁性和电子学来制造新的设备，这些设备将两个世界的优点联合收割机结合在一起，例如磁性隧道结，现在全球所有主要的铸造厂都在制造这种结，用作随机存取存储器。人们提出了模仿大脑工作方式的新型计算方法，磁性材料在其中扮演着重要角色。随着量子计算和超导计算的快速发展，科学家们正在考虑如何将磁性材料用于设备。了解磁铁的稳定性至关重要。信息通常通过将磁铁置于两种相反状态之一来编码。有可能磁铁会改变状态，我们会丢失信息。设备必须仔细设计，这样就不太可能发生这种情况。主要问题来自热量，但量子力学也会引起诸如“隧道效应”之类的效应，即磁体可以自发地改变状态。量子效应在器件较小、温度较低以及某些类型的磁体（如反铁磁体）中变得更加显著。虽然一般原理已经被理解，但我们目前还没有工具来模拟特定材料和设备的这些效应，以了解它们如何影响磁性材料的新应用。本研究项目是建立一个新的工具来模拟磁性材料中的量子效应，并使用它来研究反铁磁体，这是未来存储设备的有力候选者。我们将使用理查德·费曼创建的一种称为路径积分的数学技术，它允许量子系统由更大的经典系统模型化。这使我们能够以相对较低的计算成本在非常大的规模上包括量子效应。这种建模已被证明是非常成功的分子动力学建模，但尚未被应用到自旋动力学建模磁铁。在开发基本方法的同时，我们还将创建一个软件包，以便世界各地的研究人员可以使用该方法来预测材料特性和解释实验。该项目将使磁性材料的定量建模超越目前的可能性，并推动未来的研究。

Magnetic materials are particularly important for technological applications. They have been used for the last 50 years as the main source of computer data storage, facilitating the massive expansion in computing and the internet. Newer fields such as spintronics hope to use the magnetism alongside electronics to make new devices which combine the best of both worlds, for example magnetic tunnel junctions which are now being manufactured by all of the major global foundries for use as random access memories. New types of computing which mimic how the brain works have been suggested and magnetic materials look to play an important role in these. With quantum computing and superconducting computing developing at a rapid pace, scientists are considering how magnetic materials will be used devices. It's vitally important that we understand how stable magnets are. Information is normally encoded by putting magnets into one of two opposite states. There is a probability that the magnet can change state and we lose information. Devices have to be carefully designed so that this is very unlikely. The main issue comes from heat, but quantum mechanics can also cause effects such as 'tunnelling', where the magnet can spontaneously change state. Quantum effects become more significant when devices are smaller, temperatures are lower, and in some types of magnets such as antiferromagnets. While the general principle is understood, we don't currently have the tools to simulate these effects for specific materials and devices to understand how they might impact the new applications for magnetic materials.This research project is to build a new tool for modelling quantum effects in magnetic materials and to use it to study antiferromagnets which are a strong candidate for use in future memory devices. We will use a mathematical technique created by Richard Feynman called path integrals which allow quantum systems to be modelled by a larger set of classical systems. This allows us to include quantum effects on a very large scale with relatively low computational costs. This sort of modelling has proved very successful in molecular dynamics modelling but has not yet been applied to spin dynamics for modelling magnets. As well as developing the fundamental method we will create a software package so that researchers around the world can use the method in their efforts to predict material properties and interpret experiments. The project will enable quantitative modelling of magnetic materials beyond what is currently possible and drive future research.