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29 results for “Globular cluster”
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>
Binary fractions for Galactic globular clusters
<p>Binary fractions for Galactic globular clusters</p>
Supplementary Material for "A comparative high-resolution spectroscopic analysis of in situ and accreted globular clusters"
<p>This is a file containing supplementary material for the paper <em>A comparative high-resolution spectroscopic analysis of in situ and accreted globular clusters.</em> For each star in target globular clusters, it lists crucial information on the linelist analyzed. In particular:</p> <ol> <li>Star ID.</li> <li>Chemical element.</li> <li>Wavelength.</li> <li>log <em>gf</em></li> <li>Excitation potential.</li> <li>Measured equivalent width with uncertaintiy.</li> </ol>
Reproduction package for the paper "Near-ultraviolet detections of four dwarf nova candidates in the globular cluster 47 Tucanae"
<p>This is a basic reproduction package for the paper "Near-ultraviolet detections of four dwarf nova candidates in the globular cluster 47 Tucanae" by <a href="https://www.aanda.org/articles/aa/abs/2020/02/aa37043-19/aa37043-19.html">Modiano et al. (2020)</a>. It aims to provide the most important data products to check and reproduce the main results of the paper.</p>
Multiwavelength Constraints on the Origin of a Nearby Repeating Fast Radio Burst Source in a Globular Cluster (Public Data Release)
<p>This Zenodo dataset contains the data for radio bursts B1-B9 from FRB 20200120E, as described in A. B. Pearlman et al., <em>Nature Astronomy</em> (2024) (see: https://doi.org/10.1038/s41550-024-02386-6).</p> <p>The following data products are included:</p> <ul> <li>Channelized total intensity (Stokes I) data containing radio bursts B1-B5 from FRB 20200120E, recorded using the Effelsberg radio telescope during Pinpointing Repeating CHIME Sources with the EVN (PRECISE) VLBI observations. These data have a time resolution of 8 μs and were used in Figure 1 in A. B. Pearlman et al., <em>Nature Astronomy</em> (2024). <ul> <li>frb20200120e_b1_8us_burst_data.npy</li> <li>frb20200120e_b2_8us_burst_data.npy</li> <li>frb20200120e_b3_8us_burst_data.npy</li> <li>frb20200120e_b4_8us_burst_data.npy</li> <li>frb20200120e_b5_8us_burst_data.npy</li> </ul> </li> <li>Channelized total intensity (Stokes I) data containing radio bursts B6-B9 from FRB 20200120E, recorded using the Effelsberg radio telescope. These data have a time resolution of 64 μs and were used in Figure 1 in A. B. Pearlman et al., <em>Nature Astronomy</em> (2024). <ul> <li>frb20200120e_b6_64us_burst_data.npz</li> <li>frb20200120e_b7_64us_burst_data.npz</li> <li>frb20200120e_b8_64us_burst_data.npz</li> <li>frb20200120e_b9_64us_burst_data.npz</li> </ul> </li> <li>Frequency-summed total intensity (Stokes I) burst profiles of radio burst B4. The frequency range and time resolution of the data are listed below. These data were used in Extended Data Figure 2 (panels b, c, and d) in A. B. Pearlman et al., <em>Nature Astronomy</em> (2024).<br> <ul> <li>frb20200120e_b4_8us_1254-1510mhz_burst_profile.npz; (frequency range, time resolution) = (1254-1510 MHz, 8 μs)</li> <li>frb20200120e_b4_1us_1302-1478mhz_burst_profile.npy; (frequency range, time resolution) = (1302-1478 MHz, 1 μs)</li> <li>frb20200120e_b4_31.25ns_1398-1414mhz_burst_profile.npy; (frequency range, time resolution) = (1398-1414 MHz, 31.25 ns)</li> </ul> </li> </ul> <p>We also provide the following Python code containing functions that can be used to load and plot the radio data. The plots generated by this code are similar to those shown in Figure 1 and Extended Data Figure 2 (panels b, c, and d) in A. B. Pearlman et al., <em>Nature Astronomy</em> (2024).</p> <ul> <li>plot_frb20200120e_radio_data_pearlman+2024_nature_astronomy.py</li> </ul> <p>The X-ray data (from <em>NICER</em>, <em>XMM-Newton</em>, <em>Chandra</em>, and <em>NuSTAR</em>) used in A. B. Pearlman et al., <em>Nature Astronomy</em> (2024) are publicly available and can be accessed through NASA's High Energy Astrophysics Science Archive Research Center (HEASARC) archive.</p> <p>If the data or Python code included in this Zenodo repository are used, please include the following two citations in your work:</p> <ol> <li>Pearlman, A. B., Scholz, P., Bethapudi, S. <em>et al.</em> Multiwavelength constraints on the origin of a nearby repeating fast radio burst source in a globular cluster. <em>Nature Astronomy</em> (2024). <a href="https://doi.org/10.5281/zenodo.13359005">https://doi.org/10.1038/s41550-024-02386-6</a></li> <li>Pearlman, A. B., Scholz, P., Bethapudi, S. <em>et al.</em> Multiwavelength constraints on the origin of a nearby repeating fast radio burst source in a globular cluster (public data release). <em>Zenodo</em> (2024). <a href="https://doi.org/10.5281/zenodo.13359005">https://doi.org/10.5281/zenodo.13359005</a></li> </ol> <p>If you have questions about the contents of this Zenodo repository, please contact the lead author: Dr. Aaron B. Pearlman (<a href="mailto:aaron.b.pearlman@physics.mcgill.ca">aaron.b.pearlman@physics.mcgill.ca</a>)</p>
Hierarchical binary black hole mergers in globular clusters: Mass function and evolution with redshift
<p>Database of catalogs and numerical results for the paper: Hierarchical binary black hole mergers in globular clusters: Mass function and evolution with redshift.</p> <p> </p> <p>ABSTRACT</p> <p>Hierarchical black hole (BH) mergers are one of the most straightforward mechanisms producing BHs inside and above the pair-instability mass gap. We investigated the impact of globular cluster (GC) evolution on hierarchical mergers, accounting for the uncertainties related to BH mass pairing functions on the predicted primary BH mass, mass ratio, and spin distribution. <br>We find that the evolution of the host GC quenches the hierarchical BH assembly at the third generation, mainly due to cluster expansion powered by a central BH subsystem. Hierarchical mergers match the primary BH mass distribution from GW events for $m_1 > 50 \, \msun$ regardless of the assumed BH pairing function. <br>At lower masses, however, different pairing functions lead to dramatically different predictions on the primary BH mass merger-rate density. <br>We find that the primary BH mass distribution evolves with redshift, with a larger contribution from mergers with $m_1 \geq 30 \, \msun$ for $z\geq{}2$.<br>Finally, we calculate the mixing fraction of binary black holes (BBHs) from GCs and isolated binary systems. Our predictions are very <br>sensitive to the spins, which favor a large fraction ($>0.6$) of BBHs born in GCs in order to reproduce misaligned spin observations.</p> <p> </p> <p>FILES DESCRIPTION:</p> <p>Files Catalogs.zip contain the data used in this paper. </p> <p>The directory Metallicities contains the outputs of the Fastcluster runs at Z=0.0002. For each model and for each GC evolutionary case, we report the populations of BBHs at first ("first_generation.csv") and nth ("nth_generation.csv") generation. </p> <p>The directory Merger_Rate_Density contains the catalogs from Cosmorate+Fastcluster at redshift 0 to 4 ("redshift_*.csv") and the merger rate density as a funcion of redshift ("merger_rate_density.csv"), for different GC models. Also, it contains the mixing fractions for all the models presented in this paper ("mixing_fractions.csv").</p> <p>The Jupyter notebooks generate the Figures in the main body of the paper. </p>
The data for Newly Detected Old Galactic Globular Cluster Candidates Using Gaia DR3
<pre><br><br></pre> <p>GAIA_input - Raw data downloaded by GAIA</p> <p>GAOSI - Gaussian interpolation and testing AND concer fits correlational graph values</p> <p>The result after clustering_output</p> <p>mh_gspphot - [Fe/H] ag_gspphot - AG m_M - distance modulus - This is also the header of GC01.csv and GC02.csv under .data\gaosi\GAOS, which are copied from the csv file in .data\gaosi\GAOSI\output2</p> <p>Because GAIA lacked part of the data of [Fe/H] and AG after clustering, we adopted the Gaussian RV completion method of Qin et al. (2023) doi: 10.3847/1538-4365/acadd6 to supplement the data of [Fe/H] and AG. The data in these 3 folders is the result of the process we performed. .data\gaosi\GAOSI\output and .data\gaosi\GAOSI\output1 and .data\gaosi\GAOSI\output2 </p> <p>.data\gaosi\GAOSI\output3 - Test the data after we finish the Gaussian interpolation</p> <p>.data\gaosi\GAOSI\medain.csv -The median of the data before Gaussian interpolation</p> <p>.data\gaosi\GAOSI\pyngc01_1sigma.csv and .data\gaosi\GAOSI\pyngc02_1sigma.csv -The mean, standard deviation, and error range of m_M and mh_gspphot and ag_gspphot</p> <p> </p>
Globular Cluster Abundances from High-Resolution, Integrated-Light Spectroscopy. II. Expanding the Metallicity Range for Old Clusters and Updated Analysis Techniques
<p>Data from:</p> <p> Globular Cluster Abundances from High-Resolution, Integrated-Light Spectroscopy.<br> II. Expanding the Metallicity Range for Old Clusters and Updated Analysis Techniques (Astrophysical Journal)</p> <p> J. E. Colucci, R. A. Bernstein, A. McWilliam, Observatories of the Carnegie Institution for Science</p> <p>This repository contains reduced globular cluster integrated light echelle spectra in IRAF readable format. <br> NOTE: Spectra are *not* flux calibrated or doppler corrected. Sky/Background emission and absorption lines <br> are present. See reference paper for data reduction details.</p> <p>For each globular cluster:<br> <br> 1. *Approximately* normalized spectra are found in files ending with "ils_normalized.fits." The echelle<br> blaze function normalization was performed with an order by order fit to spectra of a reference G-type star.</p> <p> 2. Unnormalized spectra are found in files ending with "ils.fits." These spectra are not flux calibrated so do not<br> use the count values in each order for science purposes. </p> <p><br> Spectra for the globular clusters NGC 104, NGC 362, NGC 2808, NGC 6093, NGC 6397, NGC 6752 were <br> taken with the DuPont telescope. A reference star spectrum associated with the DuPont data is included : hr914_std.fits</p> <p>Spectra for the globular clusters NGC 6388, NGC 6440, NGC 6441, NGC 6528, NGC 6553 were taken with the <br> MIKE spectrograph on Magellan Clay. A reference star spectrum associated with this data is included: ltt9239_std.fits</p> <p>Spectra for the globular cluster Fornax 3 was taken with the MIKE spectrograph on Magellan Clay on a different run. <br> A reference star spectrum associated with this data is included: hd033771_std.fits</p> <p>This research was supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award AST-1302710.</p>
Effects of Type Ia Supernovae in young globular clusters
<p>Talk at Elba 23, conference in honor of Mike Rich</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>
Co-added optical spectra of globular clusters around M87 in the Virgo Cluster
<p>This dataset provides the co-added optical spectra of globular clusters in the Virgo core region. The spectra were used in the stellar population analysis of the paper "The Next Generation Virgo Cluster Survey. XXXIII. Stellar Population Gradients in the Virgo Cluster Core Globular Cluster System" by Ko et al. (2022). The detailed description can be found in the README file.</p>
Formation of Black Hole X-Ray Binaries with Non-degenerate Donors in Globular Clusters
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017ApJ...843L..30I">Formation of Black Hole X-Ray Binaries with Non-degenerate Donors in Globular Clusters</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>
Data for manuscript: The orbital anisotropy profiles of nearby globular clusters from Gaia Data Release 2
<p>We upload the data used in our paper here so that our results may be reproduced. We include the dataset of stars that survive our cuts, the profiles we plot, and the manual points selected as part of our CMD cut. See the paper for details. The first version of this paper is published on the arXiv with ID: arXiv:1903.11070. </p>
Internal proper motion dispersion profiles for 37 Milky Way globular clusters extracted from Gaia EDR3
<p>Internal proper motion dispersion profiles, in the radial and tangential components, extracted from Gaia EDR3 data for 37 Milky Way globular clusters.</p> <p>Created for, and used for model fitting in, the submitted manuscript: "Multimass modelling of Milky Way globular clusters - I. Implications on their stellar initial mass function above 1 M$_{\odot}$". Details on the creation of this dataset are available within this article.</p>
A Photometric Survey of Globular Cluster Systems in Brightest Cluster Galaxies
<p>Complete photometry and reference images from HST, for globular cluster systems around 26 giant early-type galaxies.</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>
Dataset for Runaway and Hypervelocity Stars from Compact Object Encounters in Globular Clusters
<p>The dataset used for Cabrera & Rodriguez 2023. If building from the showyourwork-enabled GitHub, the file can be directly unzipped into the <code>src/data</code> folder.</p> <p>The top-level contains folders for <code>CMC</code> model- and Milky Way globular cluster-delineated data (<code>cmc</code> and <code>mwgcs</code>, respectively), and some auxiliary files, including the composite catalogs. Within the two folders are subfolders for each of the <code>CMC</code> models and MWGCs. The <code>CMC</code> model folders contain some of the output files from the <code>CMC Cluster Catalog</code> <a href="https://ui.adsabs.harvard.edu/abs/2020ApJS..247...48K">(Kremer+20</a>) (used in this project to examine GC evolution), and also two files <code>output_N-10.txt</code> (which has data for all <code>Fewbody</code> realizations for the model) and <code>output_N-10_ejections.txt</code> (which has data for all ejections from the model). The columns in the former file are regrettably not labeled, but correspond to the following parameters, many of which are direct <code>Fewbody</code> arguments:</p> <table align="center"> <thead> <tr> <th scope="col">#</th> <th scope="col">Parameter</th> <th scope="col">Description</th> <th scope="col">Units</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>time</td> <td>Physical time of encounter in <code>CMC </code>model</td> <td>Myr</td> </tr> <tr> <td>2</td> <td>b</td> <td>Impact parameter</td> <td>a1</td> </tr> <tr> <td>3</td> <td>vinf</td> <td>Velocity of single object at infinity</td> <td>v_crit</td> </tr> <tr> <td>4</td> <td>a1</td> <td>Initial semi-major axis of binary</td> <td>AU</td> </tr> <tr> <td>5</td> <td>e1</td> <td>Initial binary eccentricity</td> <td>-</td> </tr> <tr> <td>6</td> <td>vesc</td> <td>Local escape velocity in <code>CMC </code>model</td> <td>km/s</td> </tr> <tr> <td>7</td> <td>m10</td> <td>Mass of first binary component</td> <td>Msun</td> </tr> <tr> <td>8</td> <td>m11</td> <td>Mass of second binary component</td> <td>Msun</td> </tr> <tr> <td>9</td> <td>m0</td> <td>Mass of single object</td> <td>Msun</td> </tr> <tr> <td>10</td> <td>r10</td> <td>Radius of first binary component</td> <td>Rsun</td> </tr> <tr> <td>11</td> <td>r11</td> <td>Radius of second binary component</td> <td>Rsun</td> </tr> <tr> <td>12</td> <td>r0</td> <td>Radius of single object</td> <td>Rsun</td> </tr> <tr> <td>13</td> <td>k10</td> <td>BSE k-type of first binary component</td> <td>-</td> </tr> <tr> <td>14</td> <td>k11</td> <td>BSE k-type of second binary component</td> <td>-</td> </tr> <tr> <td>15</td> <td>k0</td> <td>BSE k-type of single object</td> <td>-</td> </tr> <tr> <td>16</td> <td>s</td> <td>Random seed for <code>Fewbody</code></td> <td>-</td> </tr> <tr> <td>17</td> <td>type_i</td> <td> <p>Index classifying initial system (see below)</p> </td> <td>-</td> </tr> <tr> <td>18</td> <td>type_f</td> <td>Index classifying final system (see below)</td> <td>-</td> </tr> <tr> <td>19</td> <td>v_crit</td> <td>Critical velocity of encounter (<a href="https://ui.adsabs.harvard.edu/abs/2004MNRAS.352....1F/abstract">Fregeau+04</a>)</td> <td>km/s</td> </tr> <tr> <td>20</td> <td>a_fin</td> <td>Final semi-major axis of binary (0 if no binary is present)</td> <td>AU</td> </tr> <tr> <td>21</td> <td>e_fin</td> <td>Final binary eccentricity (identically 0 if no binary is present)</td> <td>-</td> </tr> <tr> <td>22</td> <td>Lx</td> <td>x-component of the initial angular momentum of the system</td> <td>code</td> </tr> <tr> <td>23</td> <td>Ly</td> <td>y-component of the initial angular momentum of the system</td> <td>code</td> </tr> <tr> <td>24</td> <td>Lz</td> <td>z-component of the initial angular momentum of the system</td> <td>code</td> </tr> <tr> <td>25</td> <td>Lbinx</td> <td>x-component of the angular momentum of the initial binary</td> <td>code</td> </tr> <tr> <td>26</td> <td>Lbiny</td> <td>y-component of the angular momentum of the initial binary</td> <td>code</td> </tr> <tr> <td>27</td> <td>Lbinz</td> <td>z-component of the angular momentum of the initial binary</td> <td>code</td> </tr> <tr> <td>28</td> <td>Ei</td> <td>Initial energy of the encounter</td> <td>code</td> </tr> <tr> <td>29</td> <td>DeltaEfrac</td> <td>Fractional change in energy by the time of termination</td> <td>-</td> </tr> <tr> <td>30/34/38</td> <td>vfin0/1/2</td> <td>Final velocity of the final top-level object with<code> Fewbody </code>index 0/1/2 (<a href="https://ui.adsabs.harvard.edu/abs/2004MNRAS.352....1F/abstract">Fregeau+04</a>)</td> <td>v_crit</td> </tr> <tr> <td>31/35/39</td> <td>kf0/1/2</td> <td>BSE k-type of the same</td> <td>-</td> </tr> <tr> <td>32/36/40</td> <td>Rmin0/1/2</td> <td>Minimum distance between this object and any other object during the encounter</td> <td>AU</td> </tr> <tr> <td>33/37/41</td> <td>Rmin_j0/1/2</td> <td><code>Fewbody </code>index of the other object at closest passage</td> <td>AU</td> </tr> </tbody> </table> <p>The initial encounter classifying indices are as follows, where "C" denotes a compact object and "S" a star:</p> <table align="center"> <thead> <tr> <th scope="col">type_i</th> <th scope="col">Configuration</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>(C,C)+S</td> </tr> <tr> <td>2</td> <td>(C,S)+C</td> </tr> <tr> <td>3</td> <td>(C,S)+S</td> </tr> <tr> <td>4</td> <td>(S,S)+C</td> </tr> </tbody> </table> <p>The final encounter classifying indices are as follows, using the initial <code>Fewbody </code>object indices to specify if objects end up in a binary ((a,b)) or if they merge (a:b) (note that <code>Fewbody</code> initializes all binary-single encounters in the <code>type_f=3</code> configuration, i.e. the object index 0 is assigned to the single):</p> <table align="center"> <thead> <tr> <th scope="col">type_f</th> <th scope="col">Configuration</th> </tr> </thead> <tbody> <tr> <td>0</td> <td>0+1+2 (Ionization)</td> </tr> <tr> <td>1</td> <td>(0,1)+2</td> </tr> <tr> <td>2</td> <td>(0,2)+1</td> </tr> <tr> <td>3</td> <td>0+(1,2)</td> </tr> <tr> <td>4</td> <td>0:1+2</td> </tr> <tr> <td>5</td> <td>0:2+1</td> </tr> <tr> <td>6</td> <td>1:2+0</td> </tr> <tr> <td>7</td> <td>0:1:2</td> </tr> <tr> <td>-2</td> <td>binary</td> </tr> <tr> <td>-3</td> <td>hierarchical triple</td> </tr> </tbody> </table> <p>The columns in <code>output_N-10_ejections.txt</code> are labeled, and use many of the same headers in the first table; the object indices for fields 30-41 are dropped because each row in this file corresponds to an escaper. The two additions are <code>mf</code> and <code>rf</code>, which indicate the mass and radius of the ejected object.</p> <p>Each of the <code>mwgcs</code> folders contain the FITS files described in Appendix B of the text. There are also <code>output_N-10_ejections.txt</code> files similar to the ones for the <code>CMC</code> models; the MWGC versions contain the additional fields below:</p> <table align="center"> <thead> <tr> <th scope="col">Parameter</th> <th scope="col">Description</th> <th scope="col">Units</th> </tr> </thead> <tbody> <tr> <td>vout</td> <td>Velocity of object at the time of ejection from the representative model</td> <td>km/s</td> </tr> <tr> <td>X/Y/Z</td> <td>Galactocentric X/Y/Z coordinate of object at the present day</td> <td>kpc</td> </tr> <tr> <td>U/V/W</td> <td>Galactocentric U/V/W velocity of object at the present day</td> <td>km/s</td> </tr> </tbody> </table> <p> </p>
Globular Cluster Fermipy analysis output
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Data for The Absolute Age of Milky Way Globular Clusters
<p>MC isochrones used to estimate the absolute age of 8 Milky Way GCs.</p> <p>Isochrone data for each GC is stored in HDF5 format and compressed. Each file comprises 10000 sets of isochrones with information such as age, mass, magnitude, etc. The stellar evolution parameters used to construct each isochrone can also be found in the file. The HDF5 file can be accessed using tools like python.</p> <p>Detailed instruction to read MC parameters and MC isochrones can be found in the notebook: Instruction on reading isochrones.ipynb</p>
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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.
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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.