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19 results for “Stellar Mass”
BASE-9 binarity and stellar masses from Gaia DR3, 2MASS, and Pan-STARRS data for six open clusters: NGC 2168, NGC 7789, NGC 6819, NGC 2682, NGC 188, NGC 6791
<h2>Data sets as described in "Goodbye to Chi-by-Eye: A Bayesian Analysis of Photometric Binaries in Six Open Clusters", Childs et al. 2023 <a href="https://ui.adsabs.harvard.edu/abs/2023arXiv230816282C/abstract">https://ui.adsabs.harvard.edu/abs/2023arXiv230816282C/abstract</a></h2>
X-rays across the galaxy population: The distribution of AGN accretion rates as a function of stellar mass and redshift
<p>We provide measurements of the probability distribution function of specific black hole accretion rates within a sample of galaxies of a given stellar mass and redshift, <span class="math-tex">\(p(\log \lambda_{sBHAR} | M_*,z)\)</span>. Measurements are provided for all galaxies, star-forming galaxies and quiescent galaxies. We also provide estimates of the AGN duty cycle, <span class="math-tex">\(f(\lambda_{sBHAR} >0.01)\)</span> i.e. the fraction of galaxies with an AGN above a given limit in specific accretion rate, based on the probability distribution functions. Full details are provided in Aird et al. (2018, MNRAS, 474, 1225); please cite this publication if you use these measurements. </p>
The Outer Stellar Mass of Massive Galaxies: A SimpleTracer of Halo Mass with Scatter Comparable to Richness and Reduced Projection Effects
<p>These are the data for reproducing the results of the publication titled "The Outer Stellar Mass of Massive Galaxies: A Simple Tracer of Halo Mass with Scatter Comparable to Richness and Reduced Projection Effects" by Song Huang et al.</p> <p>Please see the Python scripts and Jupyter notebooks provided in the <a href="https://github.com/dr-guangtou/jianbing">jianbing</a> repo for examples about how to use these data files. And please contact dr.guangtou@gmail.com if you have any questions about these data.</p> <p>-------------------------------------------------------------------------------------------------</p> <p>Here is a brief description of all the files:</p> <p><strong>Data from N-body simulation:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/mdpl2_halos_0.7333_reduced_logmvir_13.npy?versionId=1648006b-a91a-4300-aadf-c4746d6f3ef2">mdpl2_halos_0.7333_reduced_logmvir_13.npy</a> <ul> <li>Basic information about the dark matter halos from MDPL2 simulation</li> <li>For scale factor = 0.7333 (or z~0.4).</li> <li>Only for halos with logMvir > 13.0.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/mdpl2_particles_0.7333_72m.npy?versionId=ff7d5847-df44-46f5-9bcc-d8a7f3cc040d">mdpl2_particles_0.7333_72m.npy</a> <ul> <li>Particle catalog of the a=0.7333 snapshot from MDPL2</li> <li>This is a down-sampled version with 72 million particles.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/topn_theory_demo.pkl?versionId=7ed87c28-7adc-4987-9e00-b6223c744d42">topn_theory_demo.pkl</a> <ul> <li>These are the data used to create the theoretical demo of the TopN test.</li> <li>It is used for making the figures in <a href="https://github.com/dr-guangtou/jianbing/blob/master/notebooks/figure/fig1.ipynb">this notebook</a>.</li> </ul> </li> </ul> <p><strong>Catalogs of Galaxies or Galaxy Clusters:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/camira_s16a_cluster_use_bsm.fits?versionId=ca274c83-4025-41c4-b993-3cc9074f08b2">camira_s16a_cluster_use_bsm.fits</a> <ul> <li>The HSC S16A CAMIRA cluster catalog.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/redmapper_hsc_s16a_cluster_bsm.fits?versionId=11608e41-2427-4808-9060-a06139de165c">redmapper_hsc_s16a_cluster_bsm.fits</a> <ul> <li>The HSC S16A redMaPPer cluster catalog.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/redmapper_sdss_cluster_bsm.fits?versionId=b977c4ed-11c9-4751-b32f-60883d2e81b0">redmapper_sdss_cluster_bsm.fits</a> <ul> <li>The SDSS DR8 redMaPPer clusters in the HSC S16A footprint.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/s16a_massive_logm_11.2.fits?versionId=603cb17c-bb64-4aa7-ae05-5ec61c7ee861">s16a_massive_logm_11.2.fits</a> <ul> <li>0.2 <z < 0.5 massive galaxies in the HSC S16A footprint.</li> </ul> </li> </ul> <p><strong>Galaxy-Galaxy Lensing Data:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/s16a_weak_lensing_medium.hdf5?versionId=593c4ba0-6d7d-4b83-b8d9-01740a351fcd">s16a_weak_lensing_medium.hdf5</a> <ul> <li>A compilation of the weak lensing data to calculate the DeltaSigma profiles.</li> <li>This includes the weak lensing source catalog, photometric redshift calibration file, and the random catalog.</li> <li>"medium" here means we applied the medium criteria for selecting source galaxies. Please refer to <a href="https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.5658S/abstract">Speagle et al. (2019)</a> for the exact meaning of these criteria.</li> <li>We also have a "basic" and "strict" version. Please send your request if you need them.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/topn_public_s16a_medium_precompute.hdf5?versionId=2216ecf9-b836-4dd5-a9dd-7e070e4977bf">topn_public_s16a_medium_precompute.hdf5</a> <ul> <li>A compilation of pre-computed lensing profiles for each individual object in a different galaxy or cluster samples for the TopN test.</li> <li>These are the data used to create the stacked DeltaSigma profiles.</li> <li>We also provide the "strict" and the "basic" versions if you want to test the robustness of the TopN tests against the different selections of source galaxies in weak lensing measurements. You just need these files to generate the stacked DeltaSigma profiles.</li> </ul> </li> </ul>
MESA model files and data for: 'Stellar Neutrino Emission Across The Mass-Metallicity Plane'
<p>Example MESA model files and stellar evolution tracks for download from "Stellar Neutrino Emission Across The Mass-Metallicity Plane".</p>
Stellar Mass Black Hole Formation and Multimessenger Signals from Three-dimensional Rotating Core-collapse Supernova Simulations
<p>Gravitational waveforms from <a href="https://ui.adsabs.harvard.edu/abs/2021ApJ...914..140P/abstract">Pan et al. (2021) .</a></p> <p>They are the 40 solar mass model from Woosley & Heger 2007 with different<br>initial rotational speeds:</p> <p>Model NR: Omega_0 = 0.0 rad/sec<br>Model SR: Omega_0 = 0.5 rad/sec<br>Model FR: Omega_0 = 1.0 rad/sec</p> <p>/* File content */</p> <p>They are 5 files for each simulation.</p> <p>Files "data_s40_[model]_d3_[Cross/Plus][Equator/Pole].d" are GW strains for different<br>mode of polarization [h_plus or h_cross] and viewing angles [equator or pole].</p> <p>1st column is time [s] in postbounce. <br>2nd column s the GW strain, assuming d=10 kpc.<br> <br>Files "data_s40_[model]_d3_Idotdot.d" are the second time derivative of the<br>quadruple moments.</p> <p>1st: postbounce time [s] <br>2nd: Idd_xx [cgs]<br>3rd: Idd_xy = Idd_yx [cgs]<br>4th: Idd_yy = Idd_yy [cgs]<br>5th: Idd_zx = Idd_zx [cgs]<br>6th: Idd_zy = Idd_zy [cgs]<br>7th: Idd_zz = Idd_zz [cgs]</p> <p> </p>
The COSMOS2020 Galaxy Stellar Mass Function -- Key Measurements
<p>Here we describe the release of the measurements of the galaxy Stellar Mass Function and quiescent mass fractions based on the COSMOS2020 Farmer Catalogue and LePhare estimates of redshifts, masses, and rest-frame colours as described in Weaver et al. 2023 (ApJS, in press).</p> <p>Measurements can be found in "SMF_Farmer_Weaver+23.tar.gz"<br> Markov chains are contained in the remaining '.dat.gz' files</p> <p>When using these data products please cite both this SMF paper (Weaver et al. 2023) and the COSMOS2020 Catalogue (Weaver et al. 2022). Links to ADS export citations:</p> <p> SMF | https://ui.adsabs.harvard.edu/abs/2022arXiv221202512W<br> COSMOS2020 | https://ui.adsabs.harvard.edu/abs/2022ApJS..258...11W</p> <p>Please reach out if you have any questions or concerns.</p>
Stellar mass function for galaxies in A133
<p>This table provides the stellar mass functions (dN/dlg(M*)) of A133,<br> as shown in Fig 10 of Starikova et al. 2020, normalized to 1 square<br> degree on the sky.</p> <p> </p>
Stellar mass and star formation rate within a billion light-years
<p>Tables 1-5 of the paper entitled "Stellar Mass and Star Formation Rate within a Billion Light-Years" are available in machine readable format, together with a ReadMe file in CDS format. The python script loads Table 5 and displays the stellar mass density inferred in a volume of 200 Mpc size. Interactive versions of the six figures shown in Appendix C of the above mentioned article are also available in html format, as generated from a similar script.</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>
Dust formation and mass loss around intermediate-mass AGB stars with initial metallicity Zini ≤ 10-4 in the early Universe - I. Effect of surface opacity on stellar evolution and the dust-driven wind
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017MNRAS.466.1709T">Dust formation and mass loss around intermediate-mass AGB stars with initial metallicity Zini ≤ 10-4 in the early Universe - I. Effect of surface opacity on stellar evolution and the dust-driven wind</a></p>
Mass ejection in failed supernovae: variation with stellar progenitor
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.476.2366F/abstract">Fernández et al. (2018)</a>. MESA version 6974.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/sty306">10.1093/mnras/sty306</a></p>
The impact of stellar rotation on the black hole mass-gap from pair-instability supernovae
<p>Necessary files to reproduce the simulations of the paper "The impact of stellar rotation on the black hole mass-gap from pair-instability supernovae", as well as simulation output.</p> <p>These simulations were performed using MESA version 13311, with a small bugfix that can be applied with the provided <a href="https://zenodo.org/api/files/b21500e4-6cb5-4e3e-b8c5-83d769b24161/hydro_riemann.f90?versionId=36bcfc7a-4535-4494-ba2b-c7ea69b9b362">hydro_riemann.f90</a> file.</p> <p>A description of the included files is as follows:</p> <ul> <li><a href="https://zenodo.org/api/files/b21500e4-6cb5-4e3e-b8c5-83d769b24161/final_profiles.tar.gz?versionId=b85755ce-cd64-4e6b-ac14-d9e5364ee86b">final_profiles.tar.gz</a>: Individual profiles for all models at iron-core collapse (or last profile for PISN models). Files are separated into three folders, 'non_rot', 'rot_ST', 'rot_no_ST' corresponding to non-rotating models, rotating models with ST and rotating models without ST. Names of individual files contain the initial mass and the initial ratio between surface omega and its critical value. So for example, a file named "50.00_0.90_profile.data" represents an initial mass of 50 Msun and an initial rotation rate of 0.9 times critical. This work only contains non-rotating models and models at 0.9 critical though.</li> <li><a href="https://zenodo.org/api/files/b21500e4-6cb5-4e3e-b8c5-83d769b24161/histories.tar.gz?versionId=d3876d5e-c95e-4945-8715-9da428837afa">histories.tar.gz</a>: MESA history files containing various stellar properties describable by a single number at each timestep of the simulation (for instance, mass, effective temperature, etc...). Files follow the same naming scheme as those in final_profiles.tar.gz. For each simulation there is an additional file with a name ending in "pulse_indexes" that contains various lines with two integers per line. These specify for PPISN models the simulation step (or model_number in MESA-speak) at which a pulsation begins, and the step at which it ends.</li> <li><a href="https://zenodo.org/api/files/b21500e4-6cb5-4e3e-b8c5-83d769b24161/tables.tar.gz?versionId=69974ece-20e5-4509-a1a4-7dad7a92f4b6">tables.tar.gz</a>: Machine readable tables summarizing our simulations, these correspond to the data shown in the tables in the paper. The names of the tables "non_rot.txt", "rot_ST.txt" and "rot_no_ST.txt" correspond to non-rotating models, rotating models with ST and rotation models without ST respectively. The meaning of each column is: <ul> <li>M_i[Msun]: Initial mass of the helium star</li> <li>(om/omc)_i: Ratio between omega and its critical value at the star of core helium burning.</li> <li>M_Hedep[Msun]: Mass of the star at core helium depletion</li> <li>M_CO[Msun]: Carbon oxygen core mass at core helium depletion. Defined as the innermost mass coordinate at which Y<0.01.</li> <li>M_preSN[Msun]: Mass at the onset of PPISN/PISN. For models that do not undergo pair-instability, it corresponds to the mass at iron-core collapse.</li> <li>M_He,preSN[Msun]: Total mass in helium of the star at the onset of PPISN/PISN, or at iron-core collapse for non pair-unstable models. This does not represent the mass of the helium-rich envelope, but the total baryonic mass in helium of the star.</li> <li>M_ejecta[Msun]: Mass ejected by pulsations.</li> <li>M_final[Msun]: Final mass of the star at iron-core collapse.</li> <li>number_of_pulses: Number of pulsations.</li> <li>time_to_coll[yrs]: Time between the first pulse and iron-core collapse.</li> <li>max_KE[foe]: Maximum kinetic energy achieved by any pulse, measured in 10^51 erg/s=1 foe.</li> <li>a_i: Dimensionless spin of the star (a=jc/Gm) at the beginning of core helium burning.</li> <li>a_he_dep: Dimensionless spin at core helium depletion</li> <li>a_preSN: Dimensionless spin at the onset of PPISN/PISN.</li> <li>a_f: Final dimensionless spin from our simulations at iron-core collapse.</li> <li>BH_mass[Msun]: Final BH mass predicted from the properties of our model at iron-core collapse following Batta & Ramirez-Ruiz (2019).</li> <li>BH_spin: Final BH spin predicted from the properties of our model at iron-core collapse following Batta & Ramirez-Ruiz (2019).</li> </ul> </li> <li><a href="https://zenodo.org/api/files/b21500e4-6cb5-4e3e-b8c5-83d769b24161/pulses.tar.gz?versionId=5afe548e-3f3f-429a-98f6-b3cb14c77cc6">pulses.tar.gz</a>: Information on individual pulses for each PPISN simulation in our grid. Files are contained in three separate folders "non_rot", "rot_ST" and "rot_no_ST" for models that are non-rotating, rotating with ST and rotating without ST respectively. Naming of individual files is the same as those in final_profiles.tar.gz. Information contained in these tables is: <ul> <li>pulse_num: Integer identifying the pulse.</li> <li>ejecta[Msun]: Total mass ejected by the pulse.</li> <li>time_to_coll[yrs]: Time between the onset of this pulse and iron-core collapse.</li> <li>KE[foe]: Maximum kinetic energy reached during the pulse.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/b21500e4-6cb5-4e3e-b8c5-83d769b24161/template_ST.tar.gz?versionId=ac1563c9-5b0c-422a-8739-2fbc82ff5788">template_ST.tar.gz</a>: Template used for simulations. This template is setup for the simulations that include the ST dynamo and have an initial rotation rate of 90% critical. To modify the rotation rate and the initial mass, modify new_omega_div_omega_crit and initial_mass in the inlist_extra file. To turn of ST, set am_nu_ST_factor=0 in inlist_ppisn. Only one model required additional tuning to comple, the 60 Msun rotating model with ST. For this one, the model was restarted at step 98000 with the value of the option x_ctrl(18) switched from 0.025d0 to 0.25d0. This particular simulation did not reach the automated terminating condition and was stopped manually, but at the end it does have a collapsing iron-core with an infall velocity ~5000 km/s.</li> <li><a href="https://zenodo.org/api/files/b21500e4-6cb5-4e3e-b8c5-83d769b24161/notebook.tar.gz?versionId=d59d2404-1517-4c0a-910e-4adbc14511f8">notebook.tar.gz</a>: jupyter notebook used to process the data from our simulations and produce tables and figures (except for the information on the spin of the primary BH of GW170729).</li> <li><a href="https://zenodo.org/api/files/b21500e4-6cb5-4e3e-b8c5-83d769b24161/GW170729_spin.tar.gz?versionId=47f46740-3c0d-4355-b2a2-9d7a454f388b">GW170729_spin.tar.gz</a>: jupyter notebook used to compute the spin posterior of GW170729 using the data from the first catalogue of gravitational wave transients.</li> </ul>
Stellar evolution tracks comparing turbulent pressure driven mass loss and the de Jager mass-loss rates
<p>The uploaded files provide a series of stellar evolution tracks with initial masses from 16 to 20 <span class="math-tex">\(M_\odot\)</span>. The two sets of tracks compare the evolution of stars evolved on the red supergiant branch with the Kee et al. turbulent pressure driven mass-loss rates to stars that instead use the de Jager mass-loss rates.</p>
Measuring the conditional luminosity and stellar mass functions of galaxies by combining the DESI LS DR9, SV3 and Y1 data
Open the record for dataset details and reuse information.
The Data For Spatial Variations of Stellar Elemental Abundances in FIRE Simulations of Milky Way-Mass Galaxies: Patterns Today Mostly Reflect Those at Formation
<p>Spatial patterns of stellar elemental abundances encode rich information about a galaxy’s formation<br>history. We analyze the radial, vertical, and azimuthal variations of metals in stars, both today and at<br>formation, in the FIRE-2 cosmological simulations of Milky Way-mass galaxies, and we compare<br>with the Milky Way. Overall, spatial variations of stellar metallicities show only modest differences between formation and today; spatial variations today primarily reflect the conditions of stars at birth, with spatial redistribution of stars after birth contributing secondarily. </p> <p> </p> <p>This data abides by CC-BY.</p>
The mass fallback rate in relativistic stellar tidal disruption events
<p>MESA inlist files for the paper "The mass fallback rate in relativistic stellar tidal disruption events". Versions 15140 of MESA and MESA SDK 20.3.1 were used for the simulations. More details are in the README.txt file and in the paper.</p>
MRExo 4D Fit: Mass-Radius-Stellar-Mass-Insolation Small Planet
<p>A sample of 182 planets from the NASA Exoplanet Archive queried on 2023 March 6 for planets with masses and radii $> 3\sigma$ precision, planetary radii $<$ 4 \earthradius~ and stellar masses $<$ 1.5 \solmass described in Section 2 of Kanodia et al. 2023.</p> <p>We then perform a 4-D fit to the dataset described above, across planetary masses, radii, insolation fluxes, and stellar masses. We use 40 degrees across all four dimensions, and perform 100 trials for Monte-Carlo and Bootstrap simulations each. This is described in Section 3.1 of Kanodia et al. 2023.</p> <p>For ease of download, we have broken up the fit into three separate .zip files -</p> <p>1. Without the bootstrap or Monte-Carlo results (AllPlanet_RpLt4_StMlt1.5_MRSStM_d40_0MC_0BS.zip)</p> <p>2. With the bootstrap but not Monte-Carlo results (AllPlanet_RpLt4_StMlt1.5_MRSStM_d40_0MC_100BS.zip)</p> <p>3. Without the bootstrap but with the Monte-Carlo results (AllPlanet_RpLt4_StMlt1.5_MRSStM_d40_100MC_0BS.zip)</p> <p><em>Beyond 2-D Mass-Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions: Kanodia et al. 2023</em></p> <p> </p>
Pulsation-driven Mass Loss from Massive Stars behind Stellar Mergers in Metal-poor Dense Clusters
<p>MESA inlists, run_star_extras, and data associated with Nakauchi, Inayoshi, Omukai 2020. MESA version</p> <p>12115.</p>
Low-mass stellar models (MESA v15140 inlists)
<p>Low-mass stellar models (MESA v15140 inlists)</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
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Annotated Behaviour and Observability Dataset (ABODe)
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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.