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Related papers: Exploring high-dimensional random landscapes: from…

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We propose a way to analyze the landscape geometry explored by a glassy system after a quench solely based on time series of energy values recorded during a simulation. Entry and exit times for landscape `valleys' are defined operationally…

Statistical Mechanics · Physics 2007-05-23 Paolo Sibani , Jesper Dall

We numerically study the potential energy landscape of a fragile glassy system and find that the dynamic crossover corresponding to the glass transition is actually the effect of an underlying geometric transition caused by a qualitative…

Disordered Systems and Neural Networks · Physics 2009-11-07 Tomas S. Grigera , Andrea Cavagna , Irene Giardina , Giorgio Parisi

The large N infinite range spin glass is considered, in particular the number of spin components k needed to form the ground state and the sample-to-sample fluctuations in the Lagrange multiplier field on each site. The physical…

Disordered Systems and Neural Networks · Physics 2015-06-25 M. B. Hastings

High-contrast scattering problems are special among classical wave systems as they allow for strong wave focusing and localisation at low frequencies. We use an asymptotic framework to develop a landscape theory for high-contrast systems…

Analysis of PDEs · Mathematics 2023-11-01 Bryn Davies , Yiqi Lou

Spin glass systems as lattices of disordered magnets with random interactions have important implications within the theory of magnetization and applications to a wide-range of hard combinatorial optimization problems. Nevertheless, despite…

Disordered Systems and Neural Networks · Physics 2025-10-28 Fredrik Hasselgren , Max O. Al-Hasso , Amy Searle , Joseph Tindall , Marko von der Leyen

Tensor models play an increasingly prominent role in many fields, notably in machine learning. In several applications, such as community detection, topic modeling and Gaussian mixture learning, one must estimate a low-rank signal from a…

Machine Learning · Statistics 2022-06-16 José Henrique de Morais Goulart , Romain Couillet , Pierre Comon

We present an exactly solvable random-subcube model inspired by the structure of hard constraint satisfaction and optimization problems. Our model reproduces the structure of the solution space of the random k-satisfiability and k-coloring…

Computational Complexity · Computer Science 2008-05-23 Thierry Mora , Lenka Zdeborova

Metastable states in Ising spin-glass models are studied by finding iterative solutions of mean-field equations for the local magnetizations. Two different equations are studied: the TAP equations which are exact for the SK model, and the…

Disordered Systems and Neural Networks · Physics 2009-11-11 T. Aspelmeier , R. A. Blythe , A. J. Bray , M. A. Moore

We propose damage spreading (DS) as a tool to investigate the topological features related to the ruggedness of the free energy landscape. We argue that DS measures the positiveness of the largest Lyapunov exponent associated to the basins…

Disordered Systems and Neural Networks · Physics 2009-10-31 Felix Ritort

In this talk we review our theoretical understanding of spin glasses paying a particular attention to the basic physical ideas. We introduce the replica method and we describe its probabilistic consequences (we stress the recently…

Disordered Systems and Neural Networks · Physics 2007-05-23 Giorgio Parisi

Machines that can replicate human intelligence with type 2 reasoning capabilities should be able to reason at multiple levels of spatio-temporal abstractions and scales using internal world models. Devising formalisms to develop such…

Artificial Intelligence · Computer Science 2025-07-01 Vaisakh Shaj

We analyze the properties of a Lennard-Jones system at the level of the potential energy landscape. After an exhaustive investigation of the topological features of the landscape of the systems, obtained studying small size sample, we…

Disordered Systems and Neural Networks · Physics 2016-08-31 L. Angelani , G. Parisi , G. Ruocco , G. Viliani

Recent work suggests that Heisenberg spin glasses may belong to the same universality class than structural glasses. Indeed, finding a lattice equivalent for supercooled liquids would probably allow easier numerical and analytical studies,…

Disordered Systems and Neural Networks · Physics 2015-03-31 Marco Baity-Jesi

Mean-field models of glasses that present a random first order transition exhibit highly non-trivial fluctuations. Building on previous studies that focused on the critical scaling regime, we here obtain a fully quantitative framework for…

Disordered Systems and Neural Networks · Physics 2022-08-09 Giampaolo Folena , Giulio Biroli , Patrick Charbonneau , Yi Hu , Francesco Zamponi

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…

Mathematical Physics · Physics 2018-01-09 Valentina Cammarota , Domenico Marinucci , Igor Wigman

The nature of the spin glass state is investigated by studying changes to the ground state when a weak perturbation is applied to the bulk of the system. We consider short range models in three and four dimensions and the infinite range…

Disordered Systems and Neural Networks · Physics 2009-10-31 Matteo Palassini , A. P. Young

The p-spin spin-glass model has been studied extensively at mean-field level because of the insights which it provides into the mode-coupling approach to structural glasses and the nature of the glass transition. We demonstrate explicitly…

Disordered Systems and Neural Networks · Physics 2009-11-07 M. A. Moore , Barbara Drossel

In principle, all of the dynamical complexities of many-body systems are encapsulated in the potential energy landscapes on which the atoms move - an observation that suggests that the essentials of the dynamics ought to be determined by…

Soft Condensed Matter · Physics 2007-12-12 Chengju Wang , Richard M. Stratt

In this work we discuss a short range version of the $p$-spin model. The model is provided with a parameter that allows to control the crossover with the mean field behaviour. We detect a discrepancy between the perturbative approach and…

Disordered Systems and Neural Networks · Physics 2009-10-31 Matteo Campellone , Giorgio Parisi , Paola Ranieri

Soil creeps imperceptibly downhill, but also fails catastrophically to create landslides. Despite the importance of these processes as hazards and in sculpting landscapes, there is no agreed upon model that captures the full range of…

Soft Condensed Matter · Physics 2018-04-25 Behrooz Ferdowsi , Carlos P. Ortiz , Douglas J. Jerolmack
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