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9 results for “non-equilibrium dynamics”
Performance of wave function and Green's function methods for non-equilibrium many-body dynamics
<p>In this repository we have compiled 1-RDMs on a time grid obtained from various methods, namely, time-dependent full configuration interaction (TD-FCI), time-dependent coupled cluster (TD-CC), time-dpendent Hartree-Fock (TD-HF), Kadanoff-Baym Equations, and generalized Kadanoff-Baym approximation (GKBA). We have evaluated the 1-RDMs from Hubbard model in presence of an external drive. We have included a PySCF script to generate the integrals with a specific choice for various parameters. One can reproduce the HF results from that script. The Python script to evaluate various observables that we have analyzed in our article, namely, time-dependent dipole moment, Von-Neumann entropy are also added. </p>
Shear viscosity coefficient of acqueous glycerol from non-equilibrium Molecular Dynamics simulations
<p>This dataset contains the results of non-equilibrium atomistic Molecular Dynamics simulations of water-glycerol liquid mixtures, at various relative concentrations. The goal of the simulations is to quantify the shear viscosity coefficient of said mixtures using the periodic perturbation technique [1]. </p> <p>The pattern "Glycerol***" refers to the mass fraction of glycerol ("000": pure water, "100": pure glycerol). Each folder contains three sets of simulations, with different perturbation force parameters ("Em*"), where configuration files necessary to reproduce molecular simulations simulations are provided. Maps of density and velocity field are in "Em*"->"Flow".</p> <p>A small self-contained Python script to fit the velocity fields to a periodic cosine perturbation is provided (fit-periodic.py). Alternatively, viscosity can be obtained from energy outputs by running:</p> <pre><code>gmx energy -f ener.edr</code></pre> <p>and selecting "1/Viscosity". Simulations are performed with Gromacs. We refer to the code documentation for further information (<a href="https://manual.gromacs.org/">https://manual.gromacs.org/</a>).</p> <p>References:</p> <p>[1] B. Hess, Determining the shear viscosity of model liquids from molecular dynamics simulations, J. Chem. Phys. 116, 209–217 (2002) <a href="https://doi.org/10.1063/1.1421362">https://doi.org/10.1063/1.1421362</a></p>
Thermal conductivity of hydrous wadsleyite determined by non-equilibrium molecular dynamics based on machine learning
<p>This repository contains data used in "Thermal conductivity of hydrous wadsleyite determined by non-equilibrium molecular dynamics based on machine learning" submitted by Dong Wang, Zhongqing Wu and Xin Deng.</p> <p>Figure S4 : "MLP test-Energy" in <strong><a href="https://zenodo.org/api/files/353c5b70-3e53-4192-92af-7bf7f12328fd/Data%20for%20Figures.xlsx?versionId=96ac296c-13f9-4871-976a-d7ad087e0b62">Data for Figures.xlsx</a></strong>、<strong><a href="https://zenodo.org/api/files/353c5b70-3e53-4192-92af-7bf7f12328fd/MLP%20test-force.txt?versionId=acfeccd1-ecbf-42c8-a6a3-0d6daf72b078">MLP test-force.txt</a></strong></p> <p>Figure 1 : "MLP test-NEMD" in <strong><a href="https://zenodo.org/api/files/353c5b70-3e53-4192-92af-7bf7f12328fd/Data%20for%20Figures.xlsx?versionId=96ac296c-13f9-4871-976a-d7ad087e0b62">Data for Figures.xlsx</a></strong></p> <p>Figure 3 : "Modeing" in <strong><a href="https://zenodo.org/api/files/353c5b70-3e53-4192-92af-7bf7f12328fd/Data%20for%20Figures.xlsx?versionId=96ac296c-13f9-4871-976a-d7ad087e0b62">Data for Figures.xlsx</a></strong></p>
Data from: A model for non-equilibrium metapopulation dynamics utilizing data on species occupancy, patch ages and landscape history
1. The distribution pattern of many species reflects the past rather than the current structure of landscapes. Consequently, species are most often not in equilibrium with the current landscape structure. Yet this is a well-known fact, there is no appropriate approach to estimate the colonization rate of non-equilibrium species based on only data on the species occurrence pattern in the landscape. 2. We present an approach to estimate the colonization rate of non-equilibrium metapopulations. The approach requires only data on species presence/absence among its patches (occurrence pattern), data on patch ages and data on the historic distribution of the patches in the landscape. By estimating the past occurrence patterns and colonization events leading to the current pattern of occupied and non-occupied patches, we estimate the colonization rate, including the dispersal kernel. We also show how to estimate effects of local patch conditions and how to include an independent estimate of the local extinction rate based on other data. We use nine epiphytic lichen species confined to beech trees to illustrate the method. 3. Five species had restricted dispersal range, between 200 and 4700 m, and their colonization rate decreased with increasing fragmentation. Species colonization rates were related to niche width. Among the demographic parameters, the force of colonization was more important than the dispersal range in explaining the colonization rates. Local patch conditions did not explain the colonization probability of any species. In metapopulation projections that did not account for restricted dispersal range, higher future metapopulation sizes were projected. 4. Synthesis. The presented approach uses data on only species occurrence, patch age and landscape history to estimate the species colonization rate and dispersal kernel. It can also utilize independent data on local extinction rate. Rather than identifying factors explaining the occurrence pattern, the model estimates the rate of change in the occurrence pattern. This dynamic modelling allows testing general and applied questions on the dynamics or viability of metapopulations of sessile species. The approach is applicable for species whose distribution pattern reflects the past rather than the current landscape structure, e.g. certain epiphytes and ground-floor plants.
Using Molecular Dynamics Simulations to Interrogate T Cell Receptor Non-Equilibrium Kinetics
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Data from: Non-equilibrium dynamics of hard spheres in the fluid, crystalline, and glassy regimes
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Data from: A model for non-equilibrium metapopulation dynamics utilizing data on species occupancy, patch ages and landscape history
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Data from: Incorporating non-equilibrium dynamics into demographic history inferences of a migratory marine species
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Data from: Non-equilibrium dynamics and floral trait interactions shape extant angiosperm diversity
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Allen Brain Atlas
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.