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We introduce a variational algorithm based on Matrix Product States that is trained by minimizing a generalized free energy defined using Tsallis entropy instead of the standard Gibbs entropy. As a result, our model can generate the…

Statistical Mechanics · Physics 2024-09-16 Pablo Díez-Valle , Fernando Martínez-García , Juan José García-Ripoll , Diego Porras

We present a Gaussian ensemble of random cyclic matrices on the real field and study their spectral fluctuations. These cyclic matrices are shown to be pseudo-symmetric with respect to generalized parity. We calculate the joint probability…

Mathematical Physics · Physics 2013-02-13 Sudhir R. Jain , Shashi C. L. Srivastava

This paper investigates Gaussian Markov random field approximations to nonstationary Gaussian fields using graph representations of stochastic partial differential equations. We establish approximation error guarantees building on the…

Methodology · Statistics 2021-04-28 Daniel Sanz-Alonso , Ruiyi Yang

We study the landscapes of multi-species spherical spin glasses. Our results determine the phase boundary for annealed trivialization of the number of critical points, and establish its equivalence with a quenched strong topological…

Probability · Mathematics 2025-05-27 Brice Huang , Mark Sellke

We study via RG, numerics, exact bounds and qualitative arguments the equilibrium Gibbs measure of a particle in a $d$-dimensional gaussian random potential with {\it translationally invariant logarithmic} spatial correlations. We show that…

Condensed Matter · Physics 2014-10-13 David Carpentier , Pierre Le Doussal

The richness of the mean-field solution of simple glasses leaves many of its features challenging to interpret. A minimal model that illuminates glass physics the same way the random energy model clarifies spin glass behavior would…

Disordered Systems and Neural Networks · Physics 2025-03-14 Gilles Bonnet , Patrick Charbonneau , Giampaolo Folena

We present a detailed analysis of glass transitions induced by pinning particles at random from an equilibrium configuration. We first develop a mean-field analysis based on the study of p-spin spherical disordered models and then obtain…

Disordered Systems and Neural Networks · Physics 2014-10-13 Chiara Cammarota , Giulio Biroli

We study the geometrical structure of the states in the low temperature phase of a mean field model for generalized spin glasses, the p-spin spherical model. This structure cannot be revealed by the standard methods, mainly due to the…

Disordered Systems and Neural Networks · Physics 2009-10-30 Andrea Cavagna , Irene Giardina , Giorgio Parisi

As a guideline for experimental tests of the ideal glass transition (Random Pinning Glass Transition, RPGT) that shall be induced in a system by randomly pinning particles, we performed first-principle computations within the Hypernetted…

Disordered Systems and Neural Networks · Physics 2017-03-07 Chiara Cammarota , Beatriz Seoane

The uncertainties in material and other properties of structures are usually spatially correlated. We introduce an efficient technique for representing and processing spatially correlated random fields in robust topology optimisation of…

Numerical Analysis · Mathematics 2023-12-27 Ismael Ben-Yelun , Ahmet Oguzhan Yuksel , Fehmi Cirak

The density matrix renormalization group (DMRG) has been extended to study quantum phase transitions on random graphs of fixed connectivity. As a relevant example, we have analysed the random Ising model in a transverse field. If the…

Disordered Systems and Neural Networks · Physics 2009-11-11 Javier Rodriguez-Laguna

Seismic tomography solves high-dimensional optimization problems to image subsurface structures of Earth. In this paper, we propose to use random batch methods to construct the gradient used for iterations in seismic tomography.…

Numerical Analysis · Mathematics 2023-02-14 Yixiao Hu , Lihui Chai , Zhongyi Huang , Xu Yang

Complex analysis is a powerful tool to study classical integrable systems, statistical physics on the random lattice, random matrix theory, topological string theory,... All these topics share certain relations, called "loop equations" or…

Mathematical Physics · Physics 2011-10-10 Gaëtan Borot

We study thermally activated dynamics using functional renormalization within the field theory of randomly pinned elastic systems, a prototype for glasses. It appears through an essentially non-perturbative boundary layer in the running…

Disordered Systems and Neural Networks · Physics 2007-05-23 Leon Balents , Pierre Le Doussal

This paper initiates the systematic study of thermal field theory for generic equilibrium density matrices, which feature arbitrary values not only of temperature and chemical potentials, but also of average angular momentum. The focus here…

High Energy Physics - Theory · Physics 2026-05-05 Alberto Salvio

Sampling the stationary points of a complicated potential energy landscape is a challenging problem. Here we introduce a sampling method based on relaxation from stationary points of the highest index of the Hessian matrix. We illustrate…

Statistical Mechanics · Physics 2014-07-25 Ciaran Hughes , Dhagash Mehta , David J Wales

We focus on spherical spin glasses whose Parisi distribution has support of the form $[0,q]$. For such models we construct paths from the origin to the sphere which consistently remain close to the ground-state energy on the sphere of…

Probability · Mathematics 2019-12-03 Eliran Subag

Correlation functions involving products and ratios of half-integer powers of characteristic polynomials of random matrices from the Gaussian Orthogonal Ensemble (GOE) frequently arise in applications of Random Matrix Theory (RMT) to…

Mathematical Physics · Physics 2015-04-23 Yan V. Fyodorov , André Nock

Motivated by numerous questions in random geometry, given a smooth manifold $M$, we approach a systematic study of the differential topology of Gaussian random fields (GRF) $X:M\to \mathbb{R}^k$, that we interpret as random variables with…

Differential Geometry · Mathematics 2021-01-25 Antonio Lerario , Michele Stecconi

We review the development of random-matrix theory (RMT) during the last decade. We emphasize both the theoretical aspects, and the application of the theory to a number of fields. These comprise chaotic and disordered systems, the…

Condensed Matter · Physics 2016-08-31 Thomas Guhr , Axel Mueller-Groeling , Hans A. Weidenmueller