The applications of Machine Learning methods to classical and quantum problems in non-equilibrium

机器学习方法在非平衡经典和量子问题中的应用

• 批准号: 2275705
• 金额: --
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2275705
• 关键词: applications; Machine; Learning; methods; classical

This project will be about applying advanced machine learning methods to the study of complex collective non-equilibrium dynamics, both in classical stochastic systems and in open quantum systems. It will establish connections with approaches for sampling rare events, such as those based on large deviation theory. A particular focus will be the application of tensor network techniques and their integration to ML methods.

该项目将应用先进的机器学习方法来研究复杂的集体非平衡动力学，包括经典随机系统和开放量子系统。它将建立与稀有事件取样方法的联系，例如基于大偏差理论的方法。特别关注的是张量网络技术的应用及其与ML方法的集成。