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Related papers: Universality for Langevin-like spin glass dynamics

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We develop an instanton approach to the non-equilibrium dynamics in one-dimensional random environments. The long time behavior is controlled by rare fluctuations of the disorder potential and, accordingly, by the tail of the distribution…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. V. Lopatin , V. M. Vinokur

We establish relations between different characterizations of order in spin glass models. We first prove that the broadening of the replica overlap distribution indicated by a nonzero standard deviation of the replica overlap $R^{1,2}$…

Mathematical Physics · Physics 2024-02-27 Chigak Itoi , Hisamitsu Mukaida , Hal Tasaki

Spin-models, where the $N$ spins interact pairwise with a $SU(n_f)$ symmetry preserving hamiltonian, famously simplify in the large $n_f$, $N$ limits, as derived by Sachdev and Ye when exploring mean-field behavior of spin-glasses. We…

High Energy Physics - Theory · Physics 2025-04-15 Duff Neill , Hanqing Liu

We study the problem of predictability, or "nature vs. nurture", in several disordered Ising spin systems evolving at zero temperature from a random initial state: how much does the final state depend on the information contained in the…

Statistical Mechanics · Physics 2017-04-18 J. Ye , R. Gheissari , J. Machta , C. M. Newman , D. L. Stein

The observed general time-asymmetric behavior of macroscopic systems -- embodied in the second law of thermodynamics -- arises naturally from time-symmetric microscopic laws due to the great disparity between macro and micro-scales. More…

Condensed Matter · Physics 2007-05-23 Joel L. Lebowitz

We revisit the long time dynamics of the spherical fully connected $p = 2$-spin glass model when the number of spins $N$ is large but {\it finite}. At $T=0$ where the system is in a (trivial) spin-glass phase, and on long time scale $t…

Disordered Systems and Neural Networks · Physics 2016-01-08 Yan V. Fyodorov , Anthony Perret , Gregory Schehr

The unifying feature of glass formers (such as polymers, supercooled liquids, colloids, granulars, spin glasses, superconductors, ...) is a sluggish dynamics at low temperatures. Indeed, their dynamics is so slow that thermal equilibrium is…

We study the chaotic behavior of the Gibbs state of spin-glasses under the application of an external magnetic field, in the crossover region where the field intensity scales proportional to $1/\sqrt{N}$, being $N$ the system size. We show…

We study the probability distribution P(E) of the ground state energy E in various Ising spin glasses. In most models, P(E) seems to become Gaussian with a variance growing as the system's volume V. Exceptions include the…

Disordered Systems and Neural Networks · Physics 2009-11-07 J. -P. Bouchaud , F. Krzakala , O. C. Martin

We review a model--based rather than phenomenological approach to low--temperature anomalies in glasses. Specifically, we present a solvable model inspired by spin--glass theory that exhibits both, a glassy low--temperature phase, and a…

Statistical Mechanics · Physics 2009-10-31 Reimer Kuehn , Uta Horstmann

We prove that the Sherrington-Kirkpatrick model of spin glasses is chaotic under small perturbations of the couplings at any temperature in the absence of an external field. The result is proved for two kinds of perturbations: (a)…

Probability · Mathematics 2009-11-24 Sourav Chatterjee

We investigate a quantum Heisenberg model with both antiferromagnetic and disordered nearest-neighbor couplings. We use an extended dynamical mean-field approach, which reduces the lattice problem to a self-consistent local impurity problem…

Disordered Systems and Neural Networks · Physics 2009-11-13 S. Burdin , D. R. Grempel , M. Grilli

We revisit the Haake-Lewenstein-Wilkens (HLW) approach to Edwards-Anderson (EA) model of Ising spin glass [Phys. Rev. Lett. 55, 2606 (1985)]. This approach consists in evaluation and analysis of the probability distribution of…

Dilute magnetic nanoparticle systems exhibit slow dynamics [1] due to a broad distribution of relaxation times that can be traced to a correspondingly broad distribution of particle sizes [1]. However, at higher concentrations interparticle…

Disordered Systems and Neural Networks · Physics 2007-05-23 Derek Walton

We compute exactly the distribution of the occupation time in a discrete {\em non-Markovian} toy sequence which appears in various physical contexts such as the diffusion processes and Ising spin glass chains. The non-Markovian property…

Statistical Mechanics · Physics 2009-11-07 Satya N. Majumdar , David S. Dean

The evolution of finitely many particles obeying Langevin dynamics is described by Dean-Kawasaki equations, a class of stochastic equations featuring a non-Lipschitz multiplicative noise in divergence form. We derive a regularised…

Probability · Mathematics 2019-09-10 Federico Cornalba , Tony Shardlow , Johannes Zimmer

The slow non-equilibrium dynamics of the Edwards-Anderson spin glass model on a hierarchical lattice is studied by means of a coarse-grained description based on renormalization concepts. We evaluate the isothermal aging properties and show…

Disordered Systems and Neural Networks · Physics 2009-11-10 Falk Scheffler , Hajime Yoshino , Philipp Maass

We introduce a simple two-dimensional spin model with short-range interactions which shows glassy behavior despite a Hamiltonian which is completely homogeneous and possesses no randomness. We solve exactly for both the static partition…

Statistical Mechanics · Physics 2009-10-30 M. E. J. Newman , Cristopher Moore

Recent rapid advances in single particle tracking and supercomputing techniques resulted in an unprecedented abundance of diffusion data exhibiting complex behaviours, such the presence of power law tails of the msd and memory functions,…

Statistical Mechanics · Physics 2018-10-08 Jakub Ślęzak

We consider finite and infinite systems of particles on the real line and half-line evolving in continuous time. Hereby, the particles are driven by i.i.d. L\'{e}vy processes endowed with rank-dependent drift and diffusion coefficients. In…

Probability · Mathematics 2011-12-30 Mykhaylo Shkolnikov
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