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Random constraint satisfaction problems are interesting model systems for spin-glasses and glassy dynamics studies. As the constraint density of such a system reaches certain threshold value, its solution space may split into extremely many…

Disordered Systems and Neural Networks · Physics 2015-05-14 Haijun Zhou

There are deep analogies between the melting dynamics in systems with a first order phase transition and the dynamics from equilibrium in super-cooled liquids. For a class of Ising spin models undergoing a first order transition - namely…

Statistical Mechanics · Physics 2011-01-25 Florent Krzakala , Lenka Zdeborová

We investigate the balanced $M=4$, $p=4$ spin-glass model for a one-dimensional long-range proxy for the finite dimensional short-range $p$-spin glass model to examine the nature of the glass transition beyond mean-field theory. We perform…

Disordered Systems and Neural Networks · Physics 2026-04-20 Prerak Gupta , Auditya Sharma , Bharadwaj Vedula , J. Yeo , M. A. Moore

We use a simple mode-coupling approach to investigate glassy dynamics of partially pinned fluid systems. Our approach is different from the mode-coupling theory developed by Krakoviack [Phys. Rev. Lett. 94, 065703 (2005), Phys. Rev. E 84,…

Disordered Systems and Neural Networks · Physics 2015-06-04 Grzegorz Szamel , Elijah Flenner

We study the low temperature properties of p-spin glass models with finite connectivity and of some optimization problems. Using a one-step functional replica symmetry breaking Ansatz we can solve exactly the saddle-point equations for…

Disordered Systems and Neural Networks · Physics 2009-11-07 S. Franz , M. Leone , F. Ricci-Tersenghi , R. Zecchina

One-dimensional systems exhibiting a continuous symmetry can host quantum phases of matter with true long-range order only in the presence of sufficiently long-range interactions. In most physical systems, however, the interactions are…

Heuristic methods for solution of problems in the NP-Complete class of decision problems often reach exact solutions, but fail badly at "phase boundaries", across which the decision to be reached changes from almost always having one value…

Disordered Systems and Neural Networks · Physics 2007-05-23 R. Monasson , R. Zecchina , S. Kirkpatrick , B. Selman , L. Troyansky

The Sherrington-Kirkpatrick (SK) is a foundational model for understanding spin glass systems. It is based on the pairwise interaction between each two spins in a fully connected lattice with quenched disordered interactions. The nature of…

Disordered Systems and Neural Networks · Physics 2025-06-30 Ali Talebi

The study of spin-glass dynamics, long considered the paradigmatic complex system, has reached important milestones. The availability of single crystals has allowed the experimental measurement of spin-glass coherence lengths of almost…

We introduce a hierarchical class of approximations of the random Ising spin glass in $d$ dimensions. The attention is focused on finite clusters of spins where the action of the rest of the system is properly taken into account. At the…

Disordered Systems and Neural Networks · Physics 2009-10-30 R. Baviera , M. Pasquini , M. Serva

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

We study order-parameter fluctuations (OPF) in disordered systems by considering the behavior of some recently introduced paramaters $G,G_c$ which have proven very useful to locate phase transitions. We prove that both parameters G (for…

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

The Sherrington-Kirkpatrick spin glass model has been studied as a source of insight into the statistical mechanics of systems with highly diversified collections of competing low energy states. The goal of this summary is to present some…

Mathematical Physics · Physics 2008-09-29 Michael Aizenman , Robert Sims , Shannon L. Starr

Across many scientific and engineering disciplines, it is important to consider how much the output of a given system changes due to perturbations of the input. Here, we investigate the glassy phase of $\pm J$ spin glasses at zero…

Disordered Systems and Neural Networks · Physics 2022-10-24 Vaibhav Mohanty , Ard A. Louis

We present details of the phase diagrams of fermionic systems with random and frustrated interactions, emphasizing the important role of the chemical potential. The insulating fermionic Ising spin glass model is shown to reveal different…

Disordered Systems and Neural Networks · Physics 2007-05-23 R. Oppermann , B. Rosenow

Parisi demonstrated in 1979 that pairwise interactions exhibit a glass spin phase when there is disorder. While he discovered an equilibrium solution of the Sherrington-Kirkpatrick (SK) spin-glass model and we know it as a continuous phase…

Disordered Systems and Neural Networks · Physics 2023-04-27 M. Bagherikalhor , B. Askari , G. R. Jafari

We introduce a family of glassy models having a parameter, playing the role of an interaction range, that may be varied continuously to go from a system of particles in d dimensions to a mean-field version of it. The mean-field limit is…

Statistical Mechanics · Physics 2015-05-27 Romain Mari , Jorge Kurchan

We study first order quantum phase transitions in mean-field spin glasses. We solve the quantum Random Energy Model using elementary methods and show that at the transition the eigenstate suddenly projects onto the unperturbed ground state…

Quantum Physics · Physics 2008-10-02 Thomas Jorg , Florent Krzakala , Jorge Kurchan , A. C. Maggs

In this paper we study the critical properties of a finite dimensional generalization of the p-spin model. We find evidence that in dimension three, contrary to its mean field limit, the glass transition is associated to a diverging…

Disordered Systems and Neural Networks · Physics 2009-10-31 Silvio Franz , Giorgio Parisi

We study Ising spin models on finitely connected random interaction graphs which are drawn from an ensemble in which not only the degree distribution $p(k)$ can be chosen arbitrarily, but which allows for further fine-tuning of the topology…

Disordered Systems and Neural Networks · Physics 2009-11-13 C. J. Perez-Vicente , A. C. C. Coolen