Search results for "Condensed Matter - Disordered Systems and Neural Networks"

showing 10 items of 142 documents

Wave-Vector Dependence of the Dynamics in Supercooled Metallic Liquids

2020

Physical review letters 125(5), 055701 (2020). doi:10.1103/PhysRevLett.125.055701

Materials scienceGeneral Physics and AstronomyFOS: Physical sciencesCondensed Matter - Soft Condensed Matter01 natural sciencesMolecular physics530Amorphous materials[SPI]Engineering Sciences [physics]Dynamic light scatteringPhase (matter)0103 physical sciences[CHIM]Chemical SciencesWave vectorddc:530010306 general physicsSupercoolingMetallic glasses[PHYS]Physics [physics]Dynamical phase transitionsScattering500LiquidsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksX-ray photon correlation spectroscopyParticleRelaxation (physics)Soft Condensed Matter (cond-mat.soft)Glass transition
researchProduct

Glassy dynamics in monodisperse hard ellipsoids

2008

We present evidence from computer simulations for glassy dynamics in suspensions of monodisperse hard ellipsoids. In equilibrium, almost spherical ellipsoids show a first order transition from an isotropic phase to a rotator phase. When overcompressing the isotropic phase into the rotator regime, we observe super-Arrhenius slowing down of diffusion and relaxation, accompanied by two-step relaxation in positional and orientational correlators. The effects are strong enough for asymptotic laws of mode-coupling theory to apply. Glassy dynamics are unusual in monodisperse systems. Typically, polydispersity in size or a mixture of particle species is prerequisite to prevent crystallization. Here…

Materials scienceIsotropyDynamics (mechanics)Dispersity: Physics [G04] [Physical chemical mathematical & earth Sciences]General Physics and AstronomyFOS: Physical sciencesDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Soft Condensed MatterCondensed Matter - Disordered Systems and Neural NetworksEllipsoidlaw.inventionCondensed Matter::Soft Condensed Matter: Physique [G04] [Physique chimie mathématiques & sciences de la terre]lawChemical physicsPhase (matter)Relaxation (physics)ParticleSoft Condensed Matter (cond-mat.soft)CrystallizationDiffusion (business)
researchProduct

Molecular Dynamics Simulations

2003

A tutorial introduction to the technique of Molecular Dynamics (MD) is given, and some characteristic examples of applications are described. The purpose and scope of these simulations and the relation to other simulation methods is discussed, and the basic MD algorithms are described. The sampling of intensive variables (temperature T, pressure p) in runs carried out in the microcanonical (NVE) ensemble (N= particle number, V = volume, E = energy) is discussed, as well as the realization of other ensembles (e.g. the NVT ensemble). For a typical application example, molten SiO2, the estimation of various transport coefficients (self-diffusion constants, viscosity, thermal conductivity) is d…

Materials scienceParticle numberSampling (statistics)FOS: Physical sciencesDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsShear (sheet metal)ViscosityMolecular dynamicsThermal conductivityVolume (thermodynamics)General Materials ScienceStatistical physicsRealization (systems)
researchProduct

Aging as dynamics in configuration space

1999

The relaxation dynamics of many disordered systems, such as structural glasses, proteins, granular materials or spin glasses, is not completely frozen even at very low temperatures. This residual motion leads to a change of the properties of the material, a process commonly called aging. Despite recent advances in the theoretical description of such aging processes, the microscopic mechanisms leading to the aging dynamics are still a matter of dispute. In this Letter we investigate the aging dynamics of a simple glass former by means of molecular dynamics computer simulation. Using the concept of the inherent structure we give evidence that aging dynamics can be understood as a decrease of …

Materials scienceSpin glassStatistical Mechanics (cond-mat.stat-mech)Dynamics (mechanics)General Physics and AstronomyFOS: Physical sciencesDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Soft Condensed MatterCondensed Matter - Disordered Systems and Neural NetworksGranular materialMolecular dynamicsChemical physicsRelaxation (physics)Soft Condensed Matter (cond-mat.soft)Configuration spaceCondensed Matter - Statistical Mechanics
researchProduct

Coarsened Lattice Model for Random Granular Systems

1998

In random systems consisting of grains with size distributions the transport properties are difficult to explore by network models. However, the concentration dependence of effective conductivity and its critical properties can be considered within coarsened lattice model proposed that takes into account information from experimentally known size histograms. For certain classes of size distributions the specific local arrangements of grains can induce either symmetrical or unsymmetrical critical behaviour at two threshold concentrations. Using histogram related parameters the non-monotonic behaviour of the conductor-insulator and conductor-superconductor threshold is demonstrated.

Materials scienceStatistical Mechanics (cond-mat.stat-mech)Critical phenomenaFOS: Physical sciencesDisordered Systems and Neural Networks (cond-mat.dis-nn)ConductivityCondensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsGrain sizeElectronic Optical and Magnetic MaterialsDistribution functionPercolationHistogramStatistical physicsLattice model (physics)Condensed Matter - Statistical MechanicsNetwork model
researchProduct

Slow dynamics in ion-conducting sodium silicate melts: Simulation and mode-coupling theory

2005

A combination of molecular-dynamics (MD) computer simulation and mode-coupling theory (MCT) is used to elucidate the structure-dynamics relation in sodium-silicate melts (NSx) of varying sodium concentration. Using only the partial static structure factors from the MD as an input, MCT reproduces the large separation in relaxation time scales of the sodium and the silicon/oxygen components. This confirms the idea of sodium diffusion channels which are reflected by a prepeak in the static structure factors around 0.95 A^-1, and shows that it is possible to explain the fast sodium-ion dynamics peculiar to these mixtures using a microscopic theory.

Materials scienceStatistical Mechanics (cond-mat.stat-mech)SiliconSodiumFOS: Physical sciencesGeneral Physics and Astronomychemistry.chemical_elementSodium silicateDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksOxygenIonchemistry.chemical_compoundchemistryChemical physicsMode couplingDiffusion (business)Microscopic theoryCondensed Matter - Statistical MechanicsEurophysics Letters (EPL)
researchProduct

Statics and dynamics of colloid-polymer mixtures near their critical point of phase separation: A computer simulation study of a continuous Asakura–O…

2008

We propose a new coarse-grained model for the description of liquid-vapor phase separation of colloid-polymer mixtures. The hard-sphere repulsion between colloids and between colloids and polymers, which is used in the well-known Asakura-Oosawa (AO) model, is replaced by Weeks-Chandler-Anderson potentials. Similarly, a soft potential of height comparable to thermal energy is used for the polymer-polymer interaction, rather than treating polymers as ideal gas particles. It is shown by grand-canonical Monte Carlo simulations that this model leads to a coexistence curve that almost coincides with that of the AO model and the Ising critical behavior of static quantities is reproduced. Then the …

Materials sciencecritical pointsMonte Carlo methodFOS: Physical sciencesGeneral Physics and AstronomyThermodynamicsCondensed Matter - Soft Condensed MatterCritical point (mathematics)Molecular dynamicscolloidspolymer solutionsPhysical and Theoretical Chemistryliquid-vapour transformationsBinodalliquid mixturesLennard-Jones potentialMonte Carlo methodsDisordered Systems and Neural Networks (cond-mat.dis-nn)Statistical mechanicsCondensed Matter - Disordered Systems and Neural Networksself-diffusionIdeal gasliquid theoryCondensed Matter::Soft Condensed Mattermolecular dynamics methodLennard-Jones potentialSoft Condensed Matter (cond-mat.soft)Ising modelstatistical mechanicsphase separationThe Journal of Chemical Physics
researchProduct

Channel Formation and Intermediate Range Order in Sodium Silicate Melts and Glasses

2004

We use inelastic neutron scattering and molecular dynamics simulation to investigate the interplay between the structure and the fast sodium ion diffusion in various sodium silicates. With increasing temperature and decreasing density the structure factors exhibit an emerging prepeak around 0.9 A^-1. We show, that this prepeak has its origin in the formation of sodium rich channels in the static structure. The channels serve as preferential ion conducting pathways in the relative immobile Si-O matrix. On cooling below the glass transition this intermediate range order is frozen in.

Models MolecularSiliconSodiumNeutron diffractionFOS: Physical sciencesGeneral Physics and Astronomychemistry.chemical_elementSodium silicateInelastic scatteringInelastic neutron scatteringIonDiffusionchemistry.chemical_compoundIonic conductivityIonsModels StatisticalPhysicsSilicatesSodiumTemperatureDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksOxygenchemistryChemical physicsGlassGlass transitionPhysical Review Letters
researchProduct

Superfluid density and quasi-long-range order in the one-dimensional disordered Bose–Hubbard model

2015

We study the equilibrium properties of the one-dimensional disordered Bose-Hubbard model by means of a gauge-adaptive tree tensor network variational method suitable for systems with periodic boundary conditions. We compute the superfluid stiffness and superfluid correlations close to the superfluid to glass transition line, obtaining accurate locations of the critical points. By studying the statistics of the exponent of the power-law decay of the correlation, we determine the boundary between the superfluid region and the Bose glass phase in the regime of strong disorder and in the weakly interacting region, not explored numerically before. In the former case our simulations are in agreem…

Monte Carlo methodGeneral Physics and AstronomyBoundary (topology)FOS: Physical sciencesBose–Hubbard model01 natural sciencesCondensed Matter::Disordered Systems and Neural Networks010305 fluids & plasmasSuperfluidityPhysics and Astronomy (all)Bose glass; disorder-driven phase transition; numerical simulation of quantum many-body systems; Physics and Astronomy (all)0103 physical sciencesnumerical simulation of quantum many-body systemsPeriodic boundary conditionsTensor010306 general physicsPhysicsCondensed Matter::Quantum GasesQuantum PhysicsCondensed matter physicsdisorder-driven phase transitionCondensed Matter::OtherBose glassDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural Networks16. Peace & justiceVariational methodExponentQuantum Physics (quant-ph)
researchProduct

Multitasking associative networks.

2012

We introduce a bipartite, diluted and frustrated, network as a sparse restricted Boltzman machine and we show its thermodynamical equivalence to an associative working memory able to retrieve multiple patterns in parallel without falling into spurious states typical of classical neural networks. We focus on systems processing in parallel a finite (up to logarithmic growth in the volume) amount of patterns, mirroring the low-level storage of standard Amit-Gutfreund-Sompolinsky theory. Results obtained trough statistical mechanics, signal-to-noise technique and Monte Carlo simulations are overall in perfect agreement and carry interesting biological insights. Indeed, these associative network…

NeuronsRestricted Boltzmann machineTheoretical computer scienceArtificial neural networkComputer scienceMonte Carlo methodComplex systemGeneral Physics and AstronomyFOS: Physical sciencesStatistical mechanicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksPhysics and Astronomy (all)Human multitaskingNeural Networks ComputerNerve NetEquivalence (measure theory)Associative propertyPhysical review letters
researchProduct