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Related papers: Real space analysis of inherent structures

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We use large-scale molecular dynamics simulations to study the kinetics of the liquid-gas phase separation if the temperature is lowered across the glass transition of the dense phase. We observe a gradual change from phase separated…

Statistical Mechanics · Physics 2011-06-01 Vincent Testard , Ludovic Berthier , Walter Kob

We consider the dynamics of a diluted mean-field spin glass model in the aging regime. The model presents a particularly rich heterogeneous behavior. In order to catch this behavior, we perform a **spin-by-spin analysis** for a **given…

Disordered Systems and Neural Networks · Physics 2009-11-07 Andrea Montanari , Federico Ricci-Tersenghi

We propose a general method for studying systems that display excitations with arbitrarily low energy in their low-temperature phase. We argue that in a rectangular right prism geometry, with longitudinal size much larger than the…

We investigate the energy landscape of two dimensional network models for covalent glasses by means of the lid algorithm. For three different particle densities and for a range of network sizes, we exhaustively analyse many configuration…

Statistical Mechanics · Physics 2009-10-31 J. Christian Schoen , Paolo Sibani

Exactly solvable models provide an opportunity to study different aspects of reduced quantum dynamics in detail. We consider the reduced dynamics of a single spin in finite XX and XY spin 1/2 chains. First we introduce a general expression…

Quantum Physics · Physics 2015-03-17 Oleg Lychkovskiy

In disordered systems, the amplitudes of the localized states will decrease exponentially away from their centers and the localization lengths are characterizing such decreasing. In this article, we find a model in which each eigenstate is…

Disordered Systems and Neural Networks · Physics 2023-09-04 Ye Xiong

Intracellular protein patterns regulate many vital cellular functions, such as the processing of spatiotemporal information or the control of shape deformations. To do so, pattern-forming systems can be sensitive to the cell geometry by…

Biological Physics · Physics 2024-05-15 Tom Burkart , Benedikt J. Müller , Erwin Frey

At low temperatures ultrasoft particle systems develop interesting phases via the self-assembly of particle clusters. In this study we develop a general zero-temperature analysis fully characterizing the ground state of such models in two…

Soft Condensed Matter · Physics 2025-02-25 Matheus de Mello , Rogelio Díaz-Méndez , Alejandro Mendoza-Coto

Within the environmental context, numerical modeling is a promising approach to assessing the energy efficiency of buildings. Resilient buildings need to be designed, and capable of adapting to future extreme heat. Simulations are required…

Computational Engineering, Finance, and Science · Computer Science 2022-06-20 Julien Berger , Cyrille Allery , Anaïs Machard

Besides the dynamical slowing down signaled by an enormous increase of the viscosity approaching the glass transition, structural glasses show interesting anomalous thermodynamic features at low temperatures that hint at peculiar deviations…

Disordered Systems and Neural Networks · Physics 2019-12-05 M. Paoluzzi , L. Angelani

Previous studies have suggested a conundrum in the relaxation dynamics of polydisperse supercooled liquids. It has been shown that in two dimensions, the relative relaxation times of particles of different sizes become more similar as the…

Soft Condensed Matter · Physics 2025-03-06 Ilian Pihlajamaa , Lotte van Gessel , Corentin Laudicina , Luc van Burik , Liesbeth Janssen

We show that recent results on randomized dimension reduction schemes that exploit structural properties of data can be applied in the context of persistent homology. In the spirit of compressed sensing, the dimension reduction is…

Computational Geometry · Computer Science 2019-09-09 Martin Lotz

We consider a diffusion on a bounded domain, assuming that the system is irreducible inside the domain and that the diffusion has varying degree of degeneracy on the domain's boundary. The long-term statistical properties of typical…

Probability · Mathematics 2025-08-29 Yuri Bakhtin , Renaud Raquépas , Lai-Sang Young

We investigate the presence of domain walls in models described by three real scalar fields. We search for stable defect structures which minimize the energy of the static field configurations. We work out explict orbits in field space and…

High Energy Physics - Theory · Physics 2009-11-07 D. Bazeia , L. Losano , C. Wotzasek

We study domain growth dynamics when the target state is suddenly changed on all length scales. This procedure mimics the `chaos' effect postulated by the droplet theory of spin-glasses, and allows us to investigate in details its various…

Disordered Systems and Neural Networks · Physics 2009-10-31 Hajime Yoshino , Anael Lemaitre , Jean-Philippe Bouchaud

We give a short introduction to the inherent structure approach, with particular emphasis on the Stillinger and Weber decomposition, of glassy systems. We present some of the results obtained in the framework of spin-glass models and…

Disordered Systems and Neural Networks · Physics 2009-11-07 A. Crisanti , F. Ritort

We investigate the static and dynamic properties of a weakly polydisperse hard sphere system in the deeply supercooled state, i.e. at densities higher than that corresponding to the mode-coupling transition. The structural analysis reveals…

Soft Condensed Matter · Physics 2017-12-27 C. Patrick Royall , Walter Kob

A general matrix-based scheme for analyzing the long-time dynamics in kinetically constrained models such as the East model is presented. The treatment developed here is motivated by the expectation that slowly-relaxing spin domains of…

Statistical Mechanics · Physics 2016-08-31 Ramses van Zon , Jeremy Schofield

We investigate the quantum dynamics of Two-Level Systems (TLS) in glasses at low temperatures (1 K and below). We study an ensemble of TLSs coupled to phonons. By integrating out the phonons within the framework of the…

Disordered Systems and Neural Networks · Physics 2021-06-30 Claudia Artiaco , Federico Balducci , Antonello Scardicchio

This paper provides an algorithmic pipeline for studying the intrinsic structure of a finite discrete dynamical system (DDS) modelling an evolving phenomenon. Here, by intrinsic structure we mean, regarding the dynamics of the DDS under…

Dynamical Systems · Mathematics 2022-12-20 Alberto Dennunzio , Enrico Formenti , Luciano Margara , Sara Riva