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High-dimensional random landscapes underlie phenomena as diverse as glassy physics and optimization in machine learning, and even their simplest toy models already display extraordinarily rich behavior. This thesis aims to deepen our…

无序系统与神经网络 · 物理学 2025-10-28 Alessandro Pacco

We study rough high-dimensional landscapes in which an increasingly stronger preference for a given configuration emerges. Such energy landscapes arise in glass physics and inference. In particular we focus on random Gaussian functions, and…

无序系统与神经网络 · 物理学 2019-01-09 Valentina Ros , Gerard Ben Arous , Giulio Biroli , Chiara Cammarota

We describe a numerical study of the potential energy landscape for the two-dimensional XY model (with no disorder), considering up to 100 spins and CPU and GPU implementations of local optimization, focusing on minima and saddles of index…

统计力学 · 物理学 2013-11-27 Dhagash Mehta , Ciaran Hughes , Mario Schröck , David J. Wales

Many cognitive processes, including working memory, recruit multiple distributed interacting brain regions to encode information. How to understand the underlying cognition function mechanism of working memory is a challenging problem,…

神经元与认知 · 定量生物学 2022-09-13 Leijun Ye , Chunhe Li

It has previously been shown that the network of connected minima on a potential energy landscape is scale-free, and that this reflects a power-law distribution for the areas of the basins of attraction surrounding the minima. Here, we set…

统计力学 · 物理学 2007-09-19 Claire P. Massen , Jonathan P. K. Doye

This paper focuses on characterizing the energy profile along pathways connecting different regions of configuration space in the context of a prototypical glass model, the pure spherical $p$-spin model with $p=3$. The study investigates…

无序系统与神经网络 · 物理学 2023-12-01 Alessandro Pacco , Giulio Biroli , Valentina Ros

The quantum-classical correspondence between local minima on the classical energy landscape and excited eigenstates in the energy spectrum is studied within the context of many-body quantum spin systems. In mean-field approximations of a…

无序系统与神经网络 · 物理学 2023-06-23 Yang Wei Koh

We use the Kac-Rice formula and results from random matrix theory to obtain the average number of critical points of a family of high-dimensional empirical loss functions, where the data are correlated $d$-dimensional Gaussian vectors,…

机器学习 · 计算机科学 2026-01-14 Theodoros G. Tsironis , Aris L. Moustakas

By dividing potential energy landscapes into basins of attractions surrounding minima and linking those basins that are connected by transition state valleys, a network description of energy landscapes naturally arises. These networks are…

统计力学 · 物理学 2007-05-23 Jonathan P. K. Doye , Claire P. Massen

We start with a rather detailed, general discussion of recent results of the replica approach to statistical mechanics of a single classical particle placed in a random $N (\gg 1)$-dimensional Gaussian landscape and confined by a…

无序系统与神经网络 · 物理学 2008-01-03 Yan V Fyodorov , Ian Williams

We focus on the energy landscape of a simple mean-field model of glasses and analyze activated barrier-crossing by combining the Kac-Rice method for high-dimensional Gaussian landscapes with dynamical field theory. In particular, we…

无序系统与神经网络 · 物理学 2021-01-06 V. Ros , G. Biroli , C. Cammarota

A novel method for glassy landscape exploration is presented which utilizes a time series of energy values collected during an isothermal relaxation after a thermal quench. A sub-series of increasingly rare events, or quakes, which are…

统计力学 · 物理学 2007-05-23 Paolo Sibani , Jesper Dall

We consider a process where a spin hops across a discrete network and at certain sites couples to static spins. While this setting is implementable in various scenarios (e.g quantum dots or coupled cavities) the physics of such processes is…

量子物理 · 物理学 2011-06-08 Francesco Ciccarello

The random-field Ising model (RFIM), one of the basic models for quenched disorder, can be studied numerically with the help of efficient ground-state algorithms. In this study, we extend these algorithm by various methods in order to…

无序系统与神经网络 · 物理学 2015-05-13 M. Zumsande , A. K. Hartmann

We discuss the properties of the distributions of energies of minima obtained by gradient descent in complex energy landscapes. We find strikingly similar phenomenology across several prototypical models. We particularly focus on the…

统计力学 · 物理学 2021-01-27 Horst-Holger Boltz , Jorge Kurchan , Andrea J. Liu

A study is presented of a two-dimensional frustrated and dimerized quantum spin-system which models the effect of inter-chain coupling in a spin-Peierls compound. Employing a bond-boson method to account for quantum disorder in the ground…

强关联电子 · 物理学 2009-10-30 Wolfram Brenig

The mixed spherical models were recently found to violate long-held assumptions about mean-field glassy dynamics. In particular, the threshold energy, where most stationary points are marginal and that in the simpler pure models attracts…

无序系统与神经网络 · 物理学 2024-01-03 Jaron Kent-Dobias

S=1/2 quantum spin chains and ladders with random exchange coupling are studied by using an effective low-energy field theory and transfer matrix methods. Effects of the nonlocal correlations of exchange couplings are investigated…

无序系统与神经网络 · 物理学 2007-05-23 K. Takeda , I. Ichinose

We study the 3-spin spherical model with mean-field interactions and Gaussian random couplings. For moderate system sizes of up to 20 spins, we obtain all stationary points of the energy landscape by means of the numerical polynomial…

统计力学 · 物理学 2015-03-20 Dhagash Mehta , Daniel A. Stariolo , Michael Kastner

We study the limiting distribution of critical points and extrema of random spherical harmonics, in the high energy limit. In particular, we first derive the density functions of extrema and saddles; we then provide analytic expressions for…

数学物理 · 物理学 2018-01-09 Valentina Cammarota , Domenico Marinucci , Igor Wigman
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