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Related papers: Aging, memory, and nonhierarchical energy landscap…

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We introduce magnetization to the Multi-layer Random Energy Model which has a hierarchical structure, and perform Monte Carlo simulation to observe the behavior of ac-susceptibility. We find that this model is able to reproduce three…

Disordered Systems and Neural Networks · Physics 2009-10-31 Munetaka Sasaki , Koji Nemoto

We show numerically that a three-dimensional model for structural glass displays aging, rejuvenation and memory effects when submitted to a temperature cycle. These effects indicate that the free energy landscape of structural glasses may…

Soft Condensed Matter · Physics 2019-07-03 Camille Scalliet , Ludovic Berthier

We present a statistical method for complex energy landscape exploration which provides information on the metastable states--or valleys--actually explored by an unperturbed aging process following a quench. Energy fluctuations of record…

Statistical Mechanics · Physics 2009-11-10 Jesper Dall , Paolo Sibani

In this paper, we review the general features of the out-of-equilibrium dynamics of spin glasses. We use this example as a guideline for a brief description of glassy dynamics in other disordered systems like structural and polymer glasses,…

Disordered Systems and Neural Networks · Physics 2009-11-03 Eric Vincent

A spin glass is a diluted magnetic material in which the magnetic moments are randomly interacting, with a huge number of metastable states which prevent reaching equilibrium. Spin-glass models are conceptually simple, but require very…

Disordered Systems and Neural Networks · Physics 2023-03-03 Eric Vincent

Magnetizations are introduced to the Generalized Random Energy Model (GREM) and numerical simulations on ac susceptibility is made for direct comparison with experiments in glassy materials. Prominent dynamical natures of spin glasses, {\it…

Disordered Systems and Neural Networks · Physics 2009-10-31 Munetaka Sasaki , Koji Nemoto

We introduce an efficient dynamical tree method that enables us, for the first time, to explicitly demonstrate thermo-remanent magnetization memory effect in a hierarchical energy landscape. Our simulation nicely reproduces the nontrivial…

Disordered Systems and Neural Networks · Physics 2023-03-21 Depei Zhang , Tianran Chen , Marija Vucelja , Seung-Hun Lee , Gia-Wei Chern

The spin glasses are disordered and frustrated magnetic systems. They show aging phenomena which are also a characteristic feature of structural glasses, polymers, dielectrics, colloids, etc. Under a strong enough magnetic field variation,…

Disordered Systems and Neural Networks · Physics 2007-05-23 V. Dupuis , E. Vincent , F. Bert , D. Herisson , J. Hammann , M. Ocio

We offer an alternative real-space description, based purely on activated processes, for the understanding of relaxation dynamics in hierarchical landscapes. To this end, we use the cluster model, a coarse-grained lattice model of a jammed…

Soft Condensed Matter · Physics 2024-06-27 Mahajabin Rahman , Stefan Boettcher

Energy landscapes are high-dimensional surfaces representing the dependence of system energy on variable configurations, which determine crucially the system's emergent behavior but are difficult to be analyzed due to their high-dimensional…

Disordered Systems and Neural Networks · Physics 2024-05-24 Ho Fai Po , Chi Ho Yeung

Fossil amber offers the unique opportunity of investigating an amorphous material which has been exploring its energy landscape for more than 110 Myears of natural aging. By applying different x-ray scattering methods to amber before and…

Disordered Systems and Neural Networks · Physics 2019-01-30 E. A. A. Pogna , A. I. Chumakov , C. Ferrante , M. A. Ramos , T. Scopigno

Many dense magnetic nanoparticle systems exhibit slow dynamics which is qualitatively indistinguishable from that observed in atomic spin glasses and its origin is attributed to dipole interactions among particle moments (or superspins).…

Disordered Systems and Neural Networks · Physics 2009-11-10 M. Sasaki , P. E. Jönsson , H. Takayama , H. Mamiya

Spin glasses are notoriously difficult to study both analytically and numerically due to the presence of frustration and metastability. Their highly non-convex landscapes require collective updates to explore efficiently. Currently, most…

Disordered Systems and Neural Networks · Physics 2022-01-03 Yan Ru Pei , Massimiliano Di Ventra

The magnetisation relaxations of three different types of geometrically frustrated magnetic systems have been studied with the same experimental procedures as previously used in spin glasses. The materials investigated are Y$_2$Mo$_2$O$_7$…

Disordered Systems and Neural Networks · Physics 2009-11-10 F. Ladieu , F. Bert , V. Dupuis , E. Vincent , J. Hammann

We numerically analyse the landscape governing the evolution of the vibrational dynamics of hard disk glasses as the density increases towards jamming. We find that the dynamics becomes slow, spatially correlated, and starts to display…

Disordered Systems and Neural Networks · Physics 2019-03-22 Qinyi Liao , Ludovic Berthier

Glasses possess complex energy landscapes and exhibit non-equilibrium aging dynamics. Here, we propose a generalized trap model for activated aging based on a key static property of the energy landscape: the distribution of energy barriers.…

Disordered Systems and Neural Networks · Physics 2026-01-22 Bin Li , Deng Pan , Ting Qu , Yuliang Jin

The aging dynamics of a simple model glass is numerically investigated observing how it takes place in the potential energy landscape $V$. Partitioning the landscape in basins of minima of $|\nabla V|^2$, we are able to elucidate some…

Soft Condensed Matter · Physics 2017-08-23 R. Di Leonardo , L. Angelani , G. Parisi , G. Ruocco , A. Scala , F. Sciortino

Many recent experiments probed the off equilibrium dynamics of spin glasses and other glassy systems through temperature cycling protocols and observed memory and rejuvenation phenomena. Here we show through numerical simulations, using…

Disordered Systems and Neural Networks · Physics 2009-09-29 Florent Krzakala , Federico Ricci-Tersenghi

Aging phenomena have been studied in very different materials like polymers, supercooled liquids or disordered orientational crystals. We recall here the main features of aging in spin glasses, and use this example of magnetic systems as a…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. Hammann , E. Vincent , V. Dupuis , M. Alba , M. Ocio , J. -P. Bouchaud

The slow dynamics and concomitant memory (aging) effects seen in nanomagnetic systems are analyzed on the basis of two separate paradigms : superparamagnets and spinglasses. It is argued that in a large class of aging phenomena it suffices…

Statistical Mechanics · Physics 2009-11-11 Malay Bandyopadhyay , Sushanta Dattagupta
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