Novel approaches to interacting and disordered systems

交互和无序系统的新方法

• 批准号: 2737041
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2737041
• 关键词: Novel; approaches; interacting; disordered; systems

Disordered quantum systems continue to play a key role in theoretical developments of modern condensed matter physics. Originally, this is due to Anderson's realization in 1958 that the quantum wave nature of condensed matter can lead to interference effects that suppress the classically expected charge transport mechanisms - the birth of Anderson localization. Already in Anderson's paper, it was discussed how the situation might be influenced by many-body effects. In the last decade, following the increase in computational power to allow the construction of meaningfully large Hilbert spaces even for interacting systems, this interplay of disorder and many-body physics has received much attention but remains restricted to small system sizes. What really is needed is a novel approach at solving the underlying Schrödinger equations. Recently, machine learning and deep learning have emerged as numerical techniques that use strategies of artificial intelligence to predict outcomes of numerical experiments. It therefore seems possible to use DL techniques to speed up such sparse matrix codes to construct well-approximated eigenstates for very large system size.

量子不断地在1958年认识到现代凝结物质的关键作用。这种情况可能会受到多体的影响，遵循计算能力的增加，即使是互动系统的限制，也可以解决基本的Schrödinger方程。该技术使用人工智能的策略来预测这种稀疏的矩阵代码。