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36 results for “star clusters”
RESCUER: Cosmological K-corrections for star clusters
<p>**RESCUER: Cosmological K-corrections for star clusters**<br>Authors: Marta Reina-Campos and William E. Harris<br>Date: May 2024</p> <p>Manuscript arXiV ID: arXiv:2310.02307 -- Accepted by MNRAS on May 2024</p> <p>* These tables contain the K-corrections and their uncertainties calculated for star clusters using the E-MILES stellar library.<br>* The authors assumed that star clusters are well represented by single-age and metallicity simple stellar populations (SSPs) described by the BaSTi stellar isochrones and the Chabrier 2003 initial mass function.<br>* Each table corresponds to the K-corrections and their uncertainties for a given combination of filters. The authors considered eleven broad-band filters from the HST/ACS and the JWST/NIRCam cameras. <br>* The uncertainties are estimated using all models within 0.3 dex and 20% in metallicity and age space, respectively, of the target model, and they correspond to the distances to the 10-90th percentiles of the K-corrections of these models.<br>* The tables labeled "csv_homo_filter_X_" correspond to homochromatic K-corrections within the wavelength range of the filter X, whereas those labeled "csv_hetero_filter_X_filter_Y_" contain the K-correction from the observed filter X to the rest-frame filter Y.</p> <p>Within every table:<br>* The K-corrections are given in AB mags<br>* The first column represents the redshift at which the K-correction has been calculated<br>* All of the subsequent columns correspond to the redshift evolution of the K-correction (_target) and their asymmetric uncertainties (_lower and _upper) for a given stellar population, as indicated at the top<br>* The stellar populations are labeled as in the E-MILES stellar library: e.g. "Ech1.30Zm2.27T01.0000", corresponds to a SSP of [M/H] = -2.27 and 1 Gyr old<br>* Dummy values of -100 are placed in the redshifts larger than than the one allowed by the Planck 2018 cosmology.<br>* When an uncertainty equals zero indicates that the target K-correction was smaller/larger than the 10th/90th percentile of the distribution of K-corrections. This typically occurs in models at the edge of the grid of models (i.e. at a corner).</p>
Data: Dynamics of star clusters with tangentially anisotropic velocity distribution (Pavlik+ 2024)
<p>This dataset represents the results of our <em>N</em>-body simulations of star clusters (SCs). The initial conditions of the models are fully described in the referenced journal article. In short, the SCs start from isotropic, radially anisotropic or tangentially anisotropic initial velocity distributions, and each model is evolved in an external Galactic tidal field, for two different choices of the filling factor.</p>
Dataset from the paper "Eccentric black hole mergers via three-body interactions in young, globular and nuclear star clusters"
<p>This repository contains several data from the paper "Eccentric black hole mergers via three-body interactions in young, globular and nuclear star clusters".</p> <p> </p> <p><strong>BBH_mergers_cat_*.dat</strong> contains the data for the BBH merger population produced by the three-body simulations. These data can be used to reproduce figures 4,5, and 8 of the paper. The file is organized in columns as:</p> <ul> <li>ID of the simulation.</li> <li>outcome of the simulation (12, merger triggered by a flyby event, 13 and 23 merger triggered after an exchange event in which the secondary (primary) BH is replaced by the intruder, 123 second generation BBH merger.</li> <li>mass of the primary BH in solar masses</li> <li>mass of the secondary BH in solar masses</li> <li>Chirp mass of the system in solar masses</li> <li>coalescence time since the beginning of the simulation in year (note that all the simulation with tcoal<1e5 yr have merged during the direct N-body simulation, while all the mergers that take place after this value are evolved with the equations by Peters 1964)</li> <li>eccentricity of the binary at 10 Hz in the detector frame</li> <li>tilt angle in radiant, defined as the angle between the orbital plane of the initial binary at the beginning of the simulation and the orbital plane of the final binary at the end of the simulation.</li> </ul> <p>The files named <strong>data_*.txt</strong> contains the masses, the position and the velocities at each timestep for the three simulations showed in fig.1 in the paper. The data are referred to the center-of-mass of the three-body system. The file is organized as follows:</p> <ul> <li>The first line of the file reports the masses in solar masses of the three BHs.</li> <li>Column 0 reports the time in yr</li> <li>Colum 1-3 report the x,y,z position for the m1 BH in parsec</li> <li>Colum 4-6 report the x,y,z position for the m2 BH in parsec</li> <li>Colum 7-9 report the x,y,z position for the m3 BH in parsec</li> <li>Colum 10-12 report the x,y,z components of the velocities of the m1 BH in km/s</li> <li>Colum 13-15 report the x,y,z components of the velocities of the m1 BH in km/s</li> <li>Colum 16-18 report the x,y,z components of the velocities of the m1 BH in km/s</li> </ul> <p>Finally, <strong>outcomes_*.dat</strong> contains two columns:</p> <ul> <li>Column 0 reports the ID of the simulation</li> <li>Column 1 reports the outcome of the simulation as: 12 flyby (or merger after a flyby), 13 and 23 exchange (or merger after an exchange) in which the secondary (primary) BH is replaced by the intruder, 0 in the system is ionized in three single BHs, 3 if the system is still interacting at 1Myr, i.e. when we stop our simulation.</li> </ul> <p>This file might be useful to train a machine-lerning classificator, and can be used to reproduce Fig. 2 of the paper.</p> <p> </p> <p><strong>Contacts:</strong></p> <p>Marco Dall'Amico</p> <p>marco.dallamico@phd.studenti.unipd.it</p> <p>marco.dallamico@pd.infn.it</p>
Simulations from "Using Molecular Gas Observations to Guide Initial Conditions for Star Cluster Simulations"
<p>This dataset contains the simulation results from the article "Using Molecular Gas Observations to Guide Initial Conditions for Star Cluster Simulations" (submitted to MNRAS).</p> <p><br> The data is grouped by simulation and by particle type (gas, sinks and stars). Gas is uploaded with one snapshot per 0.05 Myr, sinks and stars with one snapshot per 0.01 Myr. The data is stored in AMUSE data format, which uses hdf5.</p>
Science ready spectra of star clusters and their best-fitting models described in the research paper "Using Star Clusters as Tracers of Star Formation and Chemical Evolution: the Chemical Enrichment History of the Large Magellanic Cloud" by Chilingarian & Asa'd
<p>Science ready spectra of star clusters in the Large Magellanic Cloud and their best-fitting templates (alpha-enhanced MILES based simple stellar population models) obtained using the NBursts full spectrum fitting code. Each spectrum is presented as a binary FITS table, which contains a spectrum (wavelength, flux, uncertainties), best-fitting template, best-fitting parameters (radial velocity, age, metallicity), and a pixel mask used in the fitting procedure. For each cluster, 5 spectra are provided, which correspond to [alpha/Fe] values from 0.0 to 0.4 dex with a step of 0.1 dex. The only exception is NGC2249, for which only 3 models are provided. The alpha-enhancement value of a model grid used in the fitting procedure is given in the FITS keyword MGFEGRID.</p>
Reproduction package for the paper "Two waves of massive stars running away from the young cluster R136"
<h2>Reproduction package for the paper "Two waves of massive stars running away from the young cluster R136".</h2> <ul> <li>This reproduction package aims for open science, with the internal API designation of 'Gold'</li> <li>Authors: M. Stoop, A. de Koter, L. Kaper, S. Brands, S. Portegies Zwart, H. Sana, F. Stoppa, M. Gieles, L. Mahy, T. Shenar, D. Guo, G. Nelemans, S. Rieder</li> <li>Paper DOI: https://doi.org/10.1038/s41586-024-08013-8</li> <li>Zenodo DOI: http://doi.org/10.5281/zenodo.10058762</li> <li>Published in Nature (date of publication: 2024/10/09)</li> </ul> <h2>Hardware</h2> <ul> <li>Tested on a MacBook Pro (13-inch, 2020, Four Thunderbolt 3 ports)</li> <li>Processor: 2 GHz Quad-Core Intel Core i5</li> <li>Memory: 32 GB 3733 MHz LPDDR4X</li> <li>Graphics: Intel Iris Plus Graphics 1536 MB</li> </ul> <h2>Required non-standard hardware</h2> <ul> <li>None</li> </ul> <h2>Software dependencies</h2> <ul> <li>Jupyterlab (4.0.8)</li> <li>Notebook (7.0.6)</li> <li>Programming languages used: Python (3.11.7)</li> <li>Python packages used: numpy (1.25.2), pandas (2.1.4), matplotlib (3.8.0), os (comes with Python) scipy (1.11.4), gaiadr3-zeropoint (0.0.4) https://gitlab.com/icc-ub/public/gaiadr3_zeropoint), astroquery (0.4.6), pymc (5.6.1), corner (2.2.2), arviz (0.16.0), pytensor (2.12.3), lmfit (1.2.2), powerlaw (1.5), rpy2 (3.5.16), seaborn (0.12.2), consistencytest (0.0.2)</li> </ul> <h2>Instructions</h2> <ul> <li>The Anaconda conda environment is given should this be needed</li> <li>All Jupyter Notebooks are ready-made to produce the raw data, intermediate and end data products</li> <li>Gaia raw data is downloaded in the Jupyter Notebook "R136_runaway_candidates.ipynb"</li> <li>Data from the literature is given in the subdirectory /tables/ or /input_files/</li> <li>Input images and files are given in the subdirectory /input_files/</li> <li>Intermediate and end data products are given in /output_files/</li> <li>Figures in the paper are produced in the Jupyter Notebooks in the subdirectory /figures/ and stored in the subdirectory /figures/figures_paper/</li> </ul> <h2>Expected Output</h2> <ul> <li>Jupyter Notebooks can be executed by "Run" -> "Run All Cells"</li> <li>The Jupyter Notebook show the expected output in their respective cell</li> <li>Expected runtime are given at the top of each Jupyter Notebook</li> <li>The Jupyter Notebook which takes the longest "R136_runaway_search.ipynb" takes 7-8 hours for the entire dataset</li> <li>A small dataset has been given in this Jupyter Notebook as a proof-of-concept</li> </ul> <h2>Instructions for use</h2> <ul> <li>Jupyter Notebooks can be executed by "Run" -> "Run All Cells"</li> </ul> <h2>Figures</h2> <ul> <li>Figures can be reproduced from the /figures/ folder.</li> <li>All material and data used are available either in the Raw Data or in the Intermediate Data</li> <li>The figures shown in the paper will be saved in ./figures/figures_paper/ folder.</li> </ul> <pre> </pre>
Magellan/M2FS and MMT/Hectochelle Spectroscopy of Dwarf Galaxies and Faint Star Clusters within the Galactic Halo
<p>m2fs_HiRes_catalog_public.fits: public catalog of measurements derived from spectroscopic observations of individual targets with the Magellan/M2FS spectrograph in HiRes configuration</p> <p>m2fs_MedRes_catalog_public.fits: public catalog of measurements derived from spectroscopic observations of individual targets with the Magellen/M2FS spectrograph in MedRes configuration</p> <p>hecto_catalog_public.fits: public catalog of measurements derived from spectroscopic observations of individual targets with the MMT/Hectochelle spectrograph</p> <p>fits_files.tar.gz: Supplementary data products, including all sky-subtracted spectra from individual targets and best-fitting model spectra.</p> <p>template_spectra.tar.gz: synthetic template spectra (columns are wavelength in air (Angstroms), normalized flux)</p>
Dynamical Parameters and Clustering Results for Four-hundred Very Metal-Poor Stars Studied with LAMOST and Subaru
<p>This is the data associated with the paper "Four-hundred Very Metal-Poor Stars Studied with LAMOST and Subaru. III. Dynamically Tagged Groups and Chemodynamical Properties" by Zhang, Matsuno, Li et al. 2024. Table "LSVMP_HRdata_dynamics.csv" contains the dynamical parameters and clustering results of the HR sample in this paper. File "readme.txt" describes the meaning of each column in the table and the notes for the flag of stars. </p> <p>This sample is obtained by the LAMOST/Subaru joint project. See our paper I (DOI: 10.3847/1538-4357/ac6515) for detailed descriptions of target selection and observations, paper II (DOI: 10.3847/1538-4357/ac6514) for the chemical abundance analysis, and paper III (DOI: 10.3847/1538-4357/ad31a6) for clustering and chemodynamical analysis.</p> <p>If you have any questions about this data, please contact lhn@nao.cas.cn or rz.richie.zhang@gmail.com for more information.</p>
SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream.
Turbulence pattern files used for star cluster formation in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** these files are automatically downloaded by Phantom on running the code **</p> <p>The files here are sample cubes containing turbulent driving patterns for the velocity field (vx, vy and vz) used to initiate star cluster formation simulations in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code</p> <p>These can be used to set up initial conditions for a set of simulations similar to those shown in <a href="http://adsabs.harvard.edu/abs/2003MNRAS.339..577B">Bate, Bonnell & Bromm (2003)</a>. The files here are not the original driving patterns used in the BBB03 simulations, but have the same structure, and give a default driving pattern that can be used without having to re-generate the files. A similar set of files was used for the simulations published in <a href="https://ui.adsabs.harvard.edu/abs/2017MNRAS.465..105L">Liptai et al. (2017)</a>.</p> <p>The files were generated with a piece of code written by Volker Bromm, which was originally part of Matthew Bate's sphNG simulation code.</p> <p>For details of how to read these files, see the Phantom source code (<a href="https://github.com/danieljprice/phantom/blob/master/src/setup/velfield_fromcubes.f90">src/setup/velfield_fromcubes.f90</a>)</p>
The Ones That Got Away: Chemical Tagging of Globular Cluster-Origin Stars with Gaia BP/RP Spectra
<p>Catalog of predictions associated with <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240900197K/abstract" target="_blank" rel="noopener">the paper "The Ones That Got Away: Chemical Tagging of Globular Cluster-Origin Stars with Gaia BP/RP Spectra."</a> The columns of the included tables are described in Appendix A.</p> <p>xp-validation_v1.fits is the predictions for the validation dataset (stars with known APOGEE abundances)</p> <p>xp-n-catalog_v1.fits is the catalog of new abundance predictions from the Gaia XP (BP/RP) spectra</p> <p>prediction-variances_v1.fits is the table of variances for each network output across 100 network predictions. The Gaia DR3 source ID is also included and corresponds to a source ID in the xp-n-catalog.</p>
Forest Fire Clustering: A Novel Tool for Identifying Star Members of Clusters
<p>In Tables 4 and 5, the <strong>Cluster</strong> column represents the name of the cluster. </p> <p><strong>Table 4</strong>: The columns <strong>ra</strong>, <strong>dec</strong>, <strong>pmra</strong>, <strong>pmdec</strong>, and <strong>parallax</strong> correspond to the median values for the cluster's position, parallax, and proper motions, respectively. The <strong>[Fe/H]</strong> and <strong>[Fe/H]_err</strong> columns indicate the cluster's [Fe/H] and its associated error. The <strong>logt</strong> and <strong>log_t_err</strong> columns represent the logarithmic age and its error, while the <strong>m-M</strong> and <strong>m-M_err</strong> columns denote the distance modulus and its error. Additionally, the <strong>E(BP-RP)</strong> and <strong>E(BP-RP)_err</strong> columns specify the cluster's reddening and its error, and the <strong>A_V</strong> and <strong>A_V_err</strong> columns represent the extinction and its error.</p> <p><strong>Table 5</strong>: The <strong>rc_pc</strong> and <strong>e_rc_pc</strong> columns indicate the core radius and its error, while the <strong>rt_pc</strong> and <strong>e_rt_pc</strong> columns represent the tidal radius and its error. The <strong>rh_pc</strong> column provides the radius containing half of the total number of stars in the cluster, and the <strong>rhm_pc</strong> column gives the half-mass radius. The <strong>R_J</strong> and <strong>R_J_err</strong> columns represent the Jacobi radius and its error. The <strong>mass</strong> and <strong>mass_err</strong> columns show the total mass of the cluster and its error, and the <strong>fb</strong> column denotes the binary fraction of the cluster. Finally, the <strong>trlx</strong> and <strong>trlx_err</strong> columns represent the relaxation time and its error. The units of<strong> trlx</strong> and <strong>trlx_err</strong> are Myr</p> <p>Note: NULL values for <strong>rc_pc, e_rc_pc, rt_pc, </strong>and <strong>e_rt_pc </strong>indicate the inapplicability of the RDP method. For <strong>Bootes I, NGC 104, NGC 3201, NGC 6121, NGC 6544, </strong>and <strong>NGC 6656</strong>, the parameters listed as “N/A”—including <strong>rhm, rJ, rJ_err, mass, mass_err, fb, trlx_Myr,</strong> and<strong> trlx_err</strong>—cannot be determined using our methods due to their faint magnitudes. This limitation arises because Gaia’s observational capacity extends only to 21 mag.</p> <p> </p>
LISC catalogue of Galactic disk star clusters in Gaia EDR3
<p>This is a database of the color-magnitude diagrams (CMDs) and fundamental parameters of star clusters in LISC catalogue.</p> <p>It corresponds to the study of Zhongmu Li et al. in 2021, which was submitted to ApJS. When one use these data, please cite to that work.</p> <p>Note that (V-I) color and V magnitude in the observed CMD data which are given in the database are transformed from the Gaia EDR3 magnitudes using some fitting correlations. </p> <p>The database contains three directories. These directories are explained as follows.</p> <p>(1)The first directory "all_clusters" gives the basic information and the observed CMD data of 3597 clusters in the work of Li et al.(2021). These clusters are all searched clusters by FOF and compared with previous catalogs. It has two subfolders and two files with '.dat' suffix.</p> <p>The first subfolder "new_candidates" contains observed CMD data of 868 clusters. These clusters are the different clusters in the previous catalogues, i.e., Liu & Pang(2019), Kharchenko et al.(2013), Cantat-Gaudin et al.(2018), Cantat-Gaudin et al.(2019), Bica et al.(2019), Castro-Ginard et al.(2019), Castro-Ginard et al.(2020), and Casado(2021) ,and the catalogue proposed in this work. Each file is named "obcmd_LISC****. dat".There are 10 columns in each file. The colums are for V, V-I, BP, BP-RP, ra, dec, parallax, rv, e_ra, e_dec respectively. The first and second columns are for V magnitude and V-I color which are transformed from the Gaia EDR3 magnitudes using some fitting correlations, and the other columns are the information of single star from Gaia EDR3.</p> <p>The second subfolder "matched_clusters" contains observed CMD data of 2729 clusters. These clusters are the same cluster in the previous catalogues, i.e., Liu & Pang(2019), Kharchenko et al.(2013), Cantat-Gaudin et al.(2018), Cantat-Gaudin et al.(2019), Bica et al.(2019), Castro-Ginard et al.(2019), Castro-Ginard et al.(2020), and Casado(2021), and the catalogue proposed in this work. The name and content of each file are the same as the file in the first subfolders.</p> <p>The first file "new_candidates" gives basic information of 868 candidates which corresponds to the candidates in the first subfolder.</p> <p>The second file "match_clusters.dat" gives basic information of 2729 clusters which corresponds to the clusters in the second subfolder of this directory.</p> <p>(2)The second directory "new_clusters" gives observed CMD data, best-fitted CMD data and best-fit parameters of 61 unknown clusters before. These clusters come from 868 star clusters that have not been matched by other catalogues. They were identified as potential new clusters in Li et al.(2021). These clusters are fitted via ASPS model and Powerful CMD code. Three parts of this directory are as follows.</p> <p>The first subfolder "obcmd" contains observed CMDs of 61 newly found clusters. The name and content of each file are the same as the file in the first subfolders of the first directory.</p> <p>The second subfolder "fitcmd" contains best-fitted CMDs of 61 new found clusters. These clusters are fitted by the ASPS model and Powerful CMD code. Each file is named "fitcmd_LISC****. dat". The first two lines give the best fitting parameters of the cluster. Note that "age0" is the age of the youngest star in the cluster if the stellar population type of cluster is composite stellar population(CSP). The first and second columns from the fourth row are for (V-I) color and V magnitude.</p> <p>The file "fit_parameter.dat" contains best-fit parameters of 61 new found clusters. There are 16 columns in this file. The colums are for id, ra, dec, plx,sig_plx, μαcosδ,sig_μαcosδ, μδ,sig_μδ, rsc, m-M, E(V-I), Z, t/t_range, f_bin and f_rot respectively. These parameters are the best-fit parameters by the ASPS model and Powerful CMD code. They correspond to the contents of a manuscript that was submitted to ApJS.</p> <p>(3)The third directory "known_clusters" gives observed CMD data, best-fitted CMD data and best-fit parameters of 594 known clusters. These clusters come from 2729 star clusters that have been matched by other catalogues. They have relatively clear CMDs structure and be fitted via ASPS model and Powerful CMD code. This directory have two subfolders.</p> <p>The first subfolder "good_fit" have the same structure with the second directory "new_clusters" but for 309 known clusters that have high quality CMDs and are fitted well. </p> <p>The second subfolder "other" have the same structure with the second directory "new_clusters" but for 285 known clusters that did not have high quality CMDs or are not well fitted.</p> <p>If you have any problems when using these data, send an email to Prof. Dr. Zhongmu LI, at email: zhongmuli@126.com.</p>
Cataloging Distant Galactic Open Clusters: Identification of 739 New Star Clusters Beyond 5 kpc Utilizing GAIA DR3 Data
<p><span>The figures of the 739 open clusters that report in our paper (Cataloging Distant Galactic Open Clusters: Identification of 739 New Star Clusters Beyond 5 kpc Utilizing GAIA DR3 Data)</span></p> <p><span> complete King's model<span> </span>profile fitting, sky charts and 5-panels ( spatial distribution, proper-motion distribution,</span></p> <p><span><span>parallax statistics, parallax distribution, and CMD)</span> .</span></p>
Data file needed for star cluster setup in Phantom smoothed particle hydrodynamics and magnetohydrodynamics code
<p>** this file is automatically downloaded by Phantom when running the starcluster setup **</p> <p>This is a small ascii file containing positions and velocities of stars utilised in the "starcluster" configuration in the Phantom smoothed particle hydrodynamics and magnetohydrodynamics code (<a href="http://adsabs.harvard.edu/abs/2018PASA...35...31P">Price et al. 2018</a>). It is used to set up a collection of N-body particles.</p> <p>The star cluster setup (and the data file) were written by Yann Bernard as part of his PhD thesis at<strong> </strong>Université Grenoble Alpes. The datafile is published here so it can be used in the automated code testing via github actions. </p> <p>The columns are mass, position (x,y,z) and velocity (vx,vy,vz) for all of the stars in the simulation</p>
On the Observability of Individual Population III Stars and Their Stellar-mass Black Hole Accretion Disks through Cluster Caustic Transits
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018ApJS..234...41W/abstract">On the Observability of Individual Population III Stars and Their Stellar-mass Black Hole Accretion Disks through Cluster Caustic Transits</a></p>
A possible formation channel for blue hook stars in globular cluster - II. Effects of metallicity, mass ratio, tidal enhancement efficiency and helium abundance
<p>MESA inlists and run_star_extras associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2016MNRAS.463.3449L">Lei et al. (2016)</a>. MESA version 7211.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/stw2242">10.1093/mnras/stw2242</a></p>
A catalogue of Galactic GEMS: Globular cluster Extra-tidal Mock Stars
<p>The Globular cluster Extra-tidal Mock Star (GEMS) catalogue contains data for simulated extra-tidal stars and binaries created via three-body dynamical encounters in globular cluster cores. Using the particle-spray code Corespray (presented in Grondin et al. 2023a), we provide data for extra-tidal single stars and escaped recoil binaries for 159 globular clusters in the Milky Way. Sky positions, kinematics, stellar properties and escape information are provided for all simulated stars. This online catalogue is associated with Grondin et al. (2023b), which has been submitted to MNRAS and is available on arXiv. A README.txt file contains information on how to access the catalogue and describes the parameters within. If you use the GEMS catalogue, please cite Grondin et al. (2023b).</p>
Strong chemical tagging with APOGEE: 21 candidate star clusters that have dissolved across the Milky Way disc
<p>Two files containing the chemically tagged abundances derived by astroNN from the Apache Point Observatory Galactic Evolution Experiment. The chemical tagging procedure is described in <a href="https://arxiv.org/abs/2004.04263">https://arxiv.org/abs/2004.04263</a>. DBSCAN_labels_APOGEE_DR16.npy contains only members of groups with more than 15 members and silhouette coefficients greater than 0. DBSCAN_labels_APOGEE_DR16_all.npy contains labels for all stars in the quality controlled data set. The data are packaged as a numpy structured array. Most of the columns are described at <a href="https://data.sdss.org/datamodel/files/APOGEE_ASTRONN/apogee_astronn.html">https://data.sdss.org/datamodel/files/APOGEE_ASTRONN/apogee_astronn.html</a>. There are two additional columns: CLUSTER_ID, and SILHOUETTE_COEFF, which are respectively the label and silhouette coefficient for each star.</p>
FIGURE. Scatter plots (N=200) and linear regression lines of the length and diameter of termite coprolites from the Lower Cretaceous Huolinhe Formation in eastern Inner Mongolia, China. The grey shading represents the 95% confidence interval of linear relationship. Note scatter plots depicting a k-means clustering analysis reveals three groups, indicated by circles of different colours; stars of different colour mean the clusters centroids which are the average length and diameter. in Termite coprolites (Blattodea: Isoptera) from the Early Cretaceous of eastern Inner Mongolia, Northeast China
FIGURE. Scatter plots (N=200) and linear regression lines of the length and diameter of termite coprolites from the Lower Cretaceous Huolinhe Formation in eastern Inner Mongolia, China. The grey shading represents the 95% confidence interval of linear relationship. Note scatter plots depicting a k-means clustering analysis reveals three groups, indicated by circles of different colours; stars of different colour mean the clusters centroids which are the average length and diameter.
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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.