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47 results for “equation of state”
Bayesian analysis of the equation of state of quantum chromodynamics from a holographic model
<p>Prior and posterior samples obtained from a Bayesian analysis of the equation of state of quantum chromodynamics (QCD) within a holographic Einstein-Maxwell-Dilaton model, constrained by state-of-the art lattice QCD results at a vanishing net density of baryons.</p> <p>Samples contain metadata, model parameters, and model predictions for the location of the QCD critical point.</p> <p>Supplement to <a title="Bayesian location of the QCD critical point from a holographic perspective" href="https://arxiv.org/abs/2309.00579">arXiv:2309.00579</a>.</p>
Dataset for "Modeling Dipolar Nonprotogenic Solvents with PC-SAFT-Type Equations of State: Pure Substance Properties"
<p>Dipolar nonprotogenic solvents (DNS) are important chemical substances used across a wide range of applications, including renewable green solvent media, sustainable energy sources, and as efficient solvents for fabricating and processing semiconductive materials used in organic photovoltaics. Therefore, for efficient solvent screening or process design, a description and prediction of the thermodynamic properties of DNS using thermodynamic models is essential. This dataset contains calculation results of four different modeling strategies within the PC-SAFT equation of state for pure-substance properties of six DNSs: gamma-valerolactone, propylene carbonate, acetonitrile, dihydrolevoglucosenone, 1-methyl-2-pyrrolidone, and sulfolane. The modeling strategies differ in the treatment of the strong dipolar interactions of DNSs. The pure-substance properties include liquid density, vapor pressure, enthalpy of vaporization, and residual isobaric liquid heat capacity. The PC-SAFT performance was analyzed and evaluated based on the calculated data. Additionally, the dataset includes input files for quantum mechanical calculations of optimal molecular geometries and dipole moments of the considered DNSs using Gaussian 16 software.</p>
Relativistic description of dense matter equation of state and compatibility with neutron star observables: a Bayesian approach
<p>The general behavior of the nuclear equation of state (EOS), relevant for the description of neutron stars (NS), is studied within a Bayesian approach applied to a set of models based on a density-dependent relativistic mean-field description of nuclear matter <a href="https://arxiv.org/abs/2201.12552">Malik et al 2022</a>. The EOS is subjected to a minimal number of constraints based on nuclear saturation properties and the low-density pure neutron matter EOS obtained from a precise next-to-next-to-next-to-leading order (N$^{3}$LO) calculation in chiral effective field theory ($\chi$EFT). The number of final sample parameters corresponding to the posterior sets is around fourteen thousand. We present five EOSs among them, namely DDBl, DDBm, DDBu1, DDBu2, and DDBx. The DDBl, DDBm, DDBu2 were chosen so that the radius of the 1.4$M_\odot$ star has the lower limit, a medium value, and the upper limit of the 90% CI for the conditional probabilities $P(R|M)$. We have also included DDBu1 that has a slightly lower $R_{1.4}$ than the upper limit but lies completely inside the 90% CI for the conditional probabilities $P(R|M)$. The DDBx is the one that predicts a maximum mass of 2.5$M_\odot$ and has the following nuclear matter properties, $K_0=300$ MeV, $J_{sym,0}=30$ MeV and $L_{sym,0}=39$ MeV.</p> <p>We also release our entire sets of ~14K NS matter EOS. All the EOSs are for NS core and starting baryon density is 0.04 fm$^{-3}$. One needs to add their own choice of crust EOS for the star properties calculation. The uncertainty in star properties for the choice of the different crust has been discussed in Section 2.1 of the manuscript (arxiv: 2201.12552). </p> <pre> To extract the entire sets of ~14K NS matter EOS files, one needs to follow the steps, 1) unzip DDB_EOS_14K.zip ----------------------------Note------------------------------------- All the eos files have three columns baryon density (fm-3), energy density (MeV.fm-3), and pressure (MeV.fm-3). The starting density is 0.04 fm-3, as it is NS core eos. One needs to add their own choice of crust eos in order to calculate NS properties. ---------------------------------------------------------------</pre> <p> </p> <p> </p>
An Explicit Primitive Conservative Solver for the Euler Equations with Arbitrary Equation of State: Dataset
<p>Contains the files for all simulations related to the publication:</p> <p>"An Explicit Primitive Conservative Solver for the Euler Equations with Arbitrary Equation of State: Dataset"</p> <p>paper: https://doi.org/10.1016/j.compfluid.2024.106340</p> <p>pre-print: https://doi.org/10.48550/arXiv.2404.07710</p>
Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac–Coulomb(–Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states: Figures
<p>This entry contains the figures included in the paper titled "Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac--Coulomb(--Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states", by Avijit Shee, Trond Saue, Lucas Visscher and Andre Severo Pereira Gomes.</p> <p>It accompanies the dataset found at the DOI: 10.5281/zenodo.1320320</p> <p>There are three figures that use the (original) png files included in <a href="https://zenodo.org/api/files/7bda2e2b-ac69-41aa-a21e-821e88bfb973/original-figures.tar.bz2">original-figures.tar.bz2 </a>:</p> <p>figure 1: Potential energy curves of the spin-orbit split X<sup>2</sup>Π and A<sup>2</sup>Π states of the XO molecules, obtained with EOM-IP and the <sup>2</sup>DCG<sup>M</sup> Hamiltonian.</p> <p>figure 2: Internuclear distances (in Angstrom), harmonic vibrational frequencies (in cm<sup>−1</sup>) and the vertical Ω = 3/2 − 1/2 energy difference (in eV) for the X<sup>2</sup>Π and A<sup>2</sup>Π states of the XO molecules, obtained with EOM-IP and the <sup>2</sup>DCG<sup>M</sup> Hamiltonian.</p> <p>figure 3: SO-ZORA/QZ4P/Hartree-Fock (ADF) spinor magnetization plots (isosurfaces at 0.03 a.u.) and energies (in Eh) for the valence spinors of the XO<sup>−</sup> species (from left to right: X = Cl, Br, I, At, Ts).</p>
Optimal neutron-star mass ranges to constrain the equation of state of nuclear matter with electromagnetic and gravitational-wave observations: EOS library
<p>This repository includes a library of equations of state (EOS) and stellar models presented in the publications Weih et al. (2019) (see also the related identifier) and Most et al. (2018). The library includes ~ 3 Million physically plausible EOSs that fulfill a number of astrophysical and nuclear constraints. See the README for more information. </p>
Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter: Neutron star equation of state posterior samples
<p>Equation of state posterior samples associated with Legred et al., "Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter," Phys. Rev. D 104, 063003 (2021); doi:10.1103/PhysRevD.104.063003</p> <p> </p> <p>Three sets of 1e4 samples from the posterior distribution over equations of state are provided. These sets are drawn from the posterior conditioned on different combinations of radio pulsar observations, gravitational wave data, and NICER x-ray measurements. The data release contains the equation of state table and the corresponding table of neutron star observables for each sample. The posterior distributions one can generate from these samples approximate those plotted in Figs. 1-6 of the accompanying paper.</p> <p> </p> <p>Refer to the readme for usage information.</p>
Astrophysical constraints on neutron star f -modes with a nonparametric equation of state representation
<p>Data release for Mohanty et al. "<em>Astrophysical constraints on neutron star f-modes with a nonparametric equation of state representation"</em></p> <p>The data release consists of three files: </p> <ol> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR.h5</a> </li> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR+GW.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR+GW.h5</a> </li> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR+GW+NICER.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR+GW+NICER.h5</a> </li> </ol> <p>Each file contains 9,835 samples of EOS draws. The equation of state id's matches those of Legred et. al. 2022</p> <p>The data structure follows Legred, I. (2022) “<em>Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter: Neutron star equation of state posterior samples</em>”. Zenodo. doi: 10.5281/zenodo.6502467.</p> <p>Samples were generated using stanspy, a general relativistic neutron star code written by Sailesh Ranjan Mohanty. </p> <p>Please see the readme (adapted from Legred et. al. 2022 Zenodo. doi: 10.5281/zenodo.6502467) </p>
Data supplement for "Localized states in coupled Cahn-Hilliard equations"
<p>Data set and plotting codes for all figures of "Localized states in coupled Cahn-Hilliard equations". Additionally, it includes Matlab codes for numerical path continuation and python codes for time simulation which can be used to reproduce the data.</p> <p>For more information, please see the included README.md</p>
Constraining the dense matter equation of state with joint analysis of NICERand LIGO/Virgo measurements: Data for generating plots
<p>In this repository you will find a Jupyter notebook with code to generate the plots from the paper <em>Constraining the dense matter equation of state with joint analysis of NICER and LIGO/Virgo measurements</em> by Raaijmakers et al. (2020).</p>
Equation of State Effects on Gravitational Waves from Rotating Core Collapse
<p>Gravitational waveforms from 1824 fiducial and detailed electron capture simulations, sampled at 65535 Hz. The file is in HDF5 format, using the flags {dtype="f4",compression="gzip",shuffle=True,fletcher32=True}. Each group is contained in the "waveforms" top-level group and is named with the "A" and "omega_0" values from Equation 5 and the EOS. In each sub-group is a dataset containing timestamps in seconds (t=0 is core bounce) and a dataset containing the strain multiplied by the distance in centimeters. The values of A in kilometers, omega_0 in radians/s, and the EOS are stored as attributes of each group.</p> <p>In addition, the Ye(rho) profiles are stored in the "yeofrho" top-level group. Each sub-group is labeled by the EOS used to generate the profile.</p> <p>Finally, select reduced data is stored in the "reduced_data" top-level group. The following quantities are each stored as a 1824-element array, where elements of the same index from different datasets correspond to the same 2D simulation.</p> <p>A(km) -- differential rotation parameter in Equation 5<br> D*bounce_amplitude_1(cm) -- The minimum of the first (negative) GW strain peak, multiplied by distance.<br> D*bounce_amplitude_2(cm) -- The maximum of the second (positive) GW strain peak, multiplied by distance.<br> EOS -- the equation of state used in the simulation<br> MbarICgrav(Msun) -- gravitational mass of the inner core, averaged over time after core bounce<br> Mgrav1_IC_b(Msun) -- gravitational mass of the inner core at bounce<br> Mrest_IC_b(Msun) -- rest mass of the inner core at bounce<br> SNR(aLIGOfrom10kpc) -- signal to noise ratio of the GW signal, assuming a distance of 10kpc and aLIGO sensitivity<br> T_c_b(MeV) -- central temperature at bounce<br> Ye_c_b -- central electron fraction at bounce<br> alpha_c_b -- central lapse at bounce<br> beta1_IC_b -- ratio of rotational kinetic to gravitational potential energy of the inner core at bounce<br> fpeak(Hz) -- frequency of the post-bounce GW oscillations<br> j_IC_b() -- angular momentum of the inner core at bounce<br> omega_0(rad|s) -- initial (pre-collapse) rotation rate used in Equation 5<br> omega_max(rad|s) -- maximum rotation rate achieved outside of 5km<br> rPNSequator_b(km) -- radius of the rho=10^11 g/ccm contour along the equator at bounce<br> rPNSpole_b(km) -- radius of the rho=10^11 g/ccm contour along the pole at bounce<br> r_omega_max(km) -- radius where omega_max occurs<br> rho_c_b(g|ccm) -- central density at bounce (not time averaged)<br> rhobar_c_postbounce(g|ccm) -- central density time averaged after bounce<br> s_c_b(kB|baryon) -- central entropy at bounce<br> t_postbounce_end(s) -- time of the end of the postbounce signal (t=0 is core bounce)<br> tbounce(s) -- time of core bounce (t=0 is the beginning of the simulation)<br> </p>
Constraining the dense matter equation of state with new NICER mass-radius measurements and new chiral effective field theory constraints: prior and posterior samples and scripts for generating plots
<p>Full reproduction package accompanying the paper: <em>Constraining the dense matter equation of state with new NICER mass-radius measurements and </em><em>new chiral effective field theory inputs</em></p> <p> </p> <p><em>*Note, the changes made from version to version are made visible in the CHANGELOG.rst file</em></p>
Binary data file needed for the Shen et al. (2011) equation of state implemented in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** this file is downloaded automatically from this repository on running Phantom **</p> <p>Contains information needed to load the <a href="http://adsabs.harvard.edu/abs/2011PhRvC..83c5802S">Shen, Horowitz & Teige (2011)</a> equation of state for nuclear matter in Phantom simulations</p> <p>The data file is a binary data file that enables a fast read of the information listed in the ascii tables given in the supplementary material of the Shen et al paper. The original ascii data files can be found here:</p> <p><a href="https://journals.aps.org/prc/supplemental/10.1103/PhysRevC.83.035802">https://journals.aps.org/prc/supplemental/10.1103/PhysRevC.83.035802</a></p> <p>For information on how to read this file, see the Phantom source code (<a href="https://github.com/danieljprice/phantom/blob/master/src/main/eos_shen.f90">eos_shen.f90</a>)</p>
Data files for the tabulated MESA equation of state in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<div> <div> <div> <p>** These tables are automatically downloaded from this repository when running phantom **<br><br>This tabulated equation of state in PHANTOM is adapted from the logPgas − Temperature equation of state tables provided with the open source package Modules for Experiments in Stellar Astrophysics MESA (Paxton et al. 2011). Details of the data, originally compiled from blends of equations of state from Saumon, Chabrier, & van Horn (1995) (SCVH), Timmes & Swesty (2000), Rogers & Nayfonov (2002, also the 2005 update), Potekhin & Chabrier (2010) and for an ideal gas, are outlined by Paxton et al. (2011).</p> <p>Code to read these tables is available as part of phantom (<a href="https://github.com/danieljprice/phantom/blob/master/src/main/eos_mesa_microphysics.f90">src/main/eos_mesa.f90</a>). The original version of these tables and the module to read them was contributed by Tom Constantino from the MUSIC code (<a href="https://ui.adsabs.harvard.edu/abs/2017A&A...600A...7Ga">Goffrey et al. 2017</a>), and the phantom implementation described in <a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. (2018)</a>.The current tables were created by Tom Reichardt for the paper Reichardt et al. (2020):<br><br><a href="https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.5333R/abstract">https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.5333R/abstract</a></p> </div> </div> </div> <p>Figure 1 in Reichardt et al. (2020) shows the pressure, temperature, Gamma and P/Pideal shown as a function of internal energy and density from these tables</p>
Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac--Coulomb(--Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states: Dataset
<p>This dataset collects the unprocessed (= outputs from calculations) and processed (= outputs from fits for obtaining spectroscopic constants) results discussed in the paper titled "Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac--Coulomb(--Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states", by Avijit Shee, Trond Saue, Lucas Visscher and Andre Severo Pereira Gomes.</p>
Constraining the Neutron Star Mass-Radius Relation and Dense Matter Equation of State with NICER. I. The Millisecond Pulsar X-Ray Data Set
<p>This deposit includes the cleaned, filtered and phase folded NICER event data set for the millisecond pulsar (MSP) PSR J0030+0451 in the 0.25-3 keV band. The data processing and filtering was performed using HEASoft 6.251 and NICERDAS version 5.0; the specific parameters and filtering criteria used are detailed in the ApJ Letter listed above. This event list was used to produce what is shown for PSR J0030+0451 in Figures 2, 3, and 4 in the accepted ApJ Letter listed above and was also used for the neutron star mass-radius and equation of state inference analyses presented in the companion papers (Miller et al. 2019, Riley et al. 2019, and Raaijmakers et al. 2019).</p> <p>The event file and its MD5 checksum is:<br> J0030+0451_merged_phase_0.25-3keV.fits (463bbac7203bb45bb02ea0deed49f083)<br> </p>
Equation of state tables used in the paper: "Exploring the Catastrophic Regime: Thermodynamics and Disintegration in Head-On Planetary Collisions"
<p>The EoS (Equation of State) tables for iron and forsterite used in the paper "<span>Exploring the Catastrophic Regime: Thermodynamics and Disintegration</span><br><span>in Head-On Planetary Collisions</span>" are available here for use.</p> <p>These tables can be directly integrated into the SPH (Smoothed Particle Hydrodynamics) code <a href="https://swift.strw.leidenuniv.nl/">SWIFT</a> to conduct simulations of planetary giant impacts.</p> <p>The tables were generated using the GitHub repository maintained by Sarah T. Stewart, specifically for <a href="https://github.com/ststewart/aneos-iron-2020">iron</a> and <a href="https://github.com/ststewart/aneos-forsterite-2019">forsterite</a>.</p> <p>All tables were created with the tension regions of the materials removed.</p> <p>Table "ANEOS_iron_S20_100gcc_denseTgrid_NOTension.txt" was generated with denser grid at temperate range 1e5 to 1e6 to using for impacts with target mass above 10 Earth mass.</p> <p>Table "ANEOS_forsterite_S19_80gcc_NOTension.txt" was generated with dense grid in both rho and temperate dimention.</p> <p>"ANEOS_iron_S20_100gcc_denseTgrid_NOTension.txt" and "ANEOS_forsterite_S19_80gcc_NOTension.txt" were generated to deal with extreme cases that impact speeds and target masses are very high. </p> <p>Most of the simulations were run with "ANEOS_forsterite_S19.txt" and "ANEOS_iron_S20.txt".</p> <p> </p>
Bayesian inference of the dense matter equation of state built upon extended Skyrme interactions [Data Set]
<pre> </pre> <p>We provide the posterior distributions of the input parameters of the five main runs considered in the article "Bayesian inference of the dense matter equation of state built upon extended Skyrme interactions" (accepted to Phys. Rev. C, arXiv: 2403.19325).</p> <p>Each row in each file corresponds to one equation of state. It contains 13 input parameters of the extend Skyrme interaction that define the effective interaction and that can be used in order to construct equations of state. The input parameters (columns, from left to right) and their dimensions are: </p> <p>C_0 (MeV*fm^3); D_0 (MeV*fm^3); C_3 (MeV*fm^{3+3*sigma}); D_3 (MeV*fm^{3+3*sigma}); C_eff (MeV*fm^5); D_eff (MeV*fm^5); t_4 (MeV*fm^{5+3*beta}); t_5 (MeV*fm^{5+3*gamma}); x_4; x_5; sigma; beta; gamma.</p> <p>See the article for more details.</p>
Datasets for "Needle in a Bayes Stack: a Hierarchical Bayesian Method for Constraining the Neutron Star Equation of State with an Ensemble of Binary Neutron Star Post-merger Remnants"
<p>All data used for "Needle in a Bayes Stack: a Hierarchical Bayesian Method for Constraining the Neutron Star Equation of State with an Ensemble of Binary Neutron Star Post-merger Remnants", Criswell, A.W., et al. (2022). The code used to create the paper results from this data can be found at <a href="https://github.com/criswellalexander/hbpm_paper">https://github.com/criswellalexander/hbpm_paper</a> and the underlying software package can be found at <a href="https://github.com/criswellalexander/bayestack">https://github.com/criswellalexander/bayestack</a>.</p>
The equation of state for neutron star matter has been obtained through Bayesian inference utilizing a relativistic mean field model with a non-linear mesonic interaction.
<p>The equation of state for matter in neutron stars has been obtained through Bayesian inference utilizing a relativistic mean field model with a non-linear mesonic interaction.</p> <p>----------------------------<br> Dr. Tuhin Malik<br> Department of Physics, University of Coimbra<br> tm@uc.pt<br> Date: 22 Apr 2023<br> -----------------------------<br> The high density behavior of nuclear matter is analyzed within a relativistic mean field description with non-linear meson interactions. To assess the model parameters and their output, a Bayesian inference technique is used. The Bayesian setup is limited only by a few nuclear saturation properties, the neutron star maximum mass larger than 2 M$_\odot$, and the low-density pure neutron matter equation of state (EOS) produced by an accurate N$^3$LO calculation in chiral effective field theory. Depending on the strength of the non-linear scalar vector field contribution, we have found three distinct classes of EOSs, each one correlated to different star properties distributions. If the non-linear vector field contribution is absent, the gravitational maximum mass and the sound velocity at high densities are the greatest. However, it also gives the smallest speed of sound at densities below three times saturation density. On the other hand, models with the strongest non-linear vector field contribution, predict the largest radii and tidal deformabilities for 1.4 M$_\odot$ stars, together with the smallest mass for the onset of the nucleonic direct Urca processes and the smallest central baryonic densities for the maximum mass configuration. {These models have the largest speed of sound below three times saturation density, but the smallest at high densities, in particular, above four times saturation density the speed of sound decreases approaching approximately $\sqrt{0.4}c$ at the center of the maximum mass star. On the contrary, a weak non-linear vector contribution gives a monotonically increasing speed of sound.} {A 2.75 M$_\odot$ NS maximum mass was obtained in the tail of the posterior with a weak non-linear vector field interaction. This indicates that the secondary object in GW190814 could also be an NS. {The possible onset of hyperons and the compatibility of the different sets of models with pQCD are discussed. It is shown that pQCD favors models with a large contribution from the non-linear vector field term or which include hyperons.}}</p> <p>The article e-Print: <a href="https://arxiv.org/abs/2301.08169">2301.08169</a></p> <p>We release model parameters, its nuclear saturation properties, equation of state, and TOV solutions derived from Bayesian Inference with Prior Set 0, 1, 2, and 3. We also share Set 0 with Hyperon. <br> <br> For every Set, our data release packet contains four CSV files, namely "set{X}_prop.csv", "set{X}_eos.csv", "set{X}_tov.csv", and "set{X}_cs2.csv", where X in [0,1,2,3 and 0_hyp].<br> <br> set{X}_prop.csv:<br> The file contains the parameters for the RMF model, as well as a few NS properties and nuclear saturation properties. It has the following columns:<br> model name,gs,gv,gr,B,C,xi,lam,rho0,e0,k0,q0,z0,jsym0,lsym0,<br> ksym0,qsym0,zsym0,m_max,r_max,r14,lam14,cs2_max, ec,rhoc,rho_durca.<br> It is to be noted that the parameter B and C are the 10^3*b and 10^3 c (see article for details). <br> <br> set{X}_eos.csv:<br> For those models in set{X}_prop.csv, it is the NS matter EOS file. It has the following columns: model name, baryon number density, energy density and pressure. The units for baryon number density is fm-3 and MeV/fm3 is for both energy density and pressure. The EOS is for the core only. The crust is not added. <br> <br> set{X}_tov.csv:<br> For those models in set{X}_prop.csv, it is the TOV solution. It has the following columns: model name, ns radius (km), ns mass (msun), and dimensionless tidal deformability lambda. </p> <p>set{X}_cs2.csv:<br> For those models in set{X}_prop.csv, it is the square of the speed of sound over density. It has the following columns: model name, number density fm-3, and square of the speed of sound c2. <br> -------------------------------------------------------------------------</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.