复杂系统的统计物理学:玻璃、自旋玻璃、连续约束满足问题、高维推理和神经网络

Pierfrancesco Urbani
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引用次数: 0

摘要

本手稿旨在回顾我最近在三个主要研究课题上的活动。首先是低温无定形固体的性质及其与磁场中自旋玻璃化转变的关系。这是第一章的主题,我讨论了一个新模型,即 KHGPS 模型,该模型取得了一些进展。在第二章中,我回顾了第二条研究路线,即研究粒子系统模型中的刚性/干扰转变及其与约束满足和高维度优化问题的关系。最后一章,我回顾了自己在高维推理和监督学习问题中学习算法动力学问题上的研究活动。
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Statistical physics of complex systems: glasses, spin glasses, continuous constraint satisfaction problems, high-dimensional inference and neural networks
The purpose of this manuscript is to review my recent activity on three main research topics. The first concerns the nature of low temperature amorphous solids and their relation with the spin glass transition in a magnetic field. This is the subject of the first chapter where I discuss a new model, the KHGPS model, which allows to make some progress. In the second chapter I review a second research line that concerns the study of the rigidity/jamming transitions in particle system models and their relation to constraint satisfaction and optimization problems in high dimension. Finally in the last chapter I review my activity on the problem of the dynamics of learning algorithms in high-dimensional inference and supervised learning problems.
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