Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
13
datasets available to search
ShareScore release 0.7.1
Dataset results
13 results for “Asteroseismology”
The APO-K2 Catalog. I. ~7,500 Red Giants with Fundamental Stellar Parameters from APOGEE DR17 Spectroscopy and K2-GAP Asteroseismology
<p><strong>Abstract: </strong>We present a catalog of fundamental stellar properties for ~7,500 evolved stars, including stellar radii and masses, determined from the combination of spectroscopic observations from the Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the Sloan Digital Sky Survey IV (SDSS), and asteroseismology from K2. The resulting APO-K2 catalog provides spectroscopically derived temperatures and metallicities, asteroseismic global parameters, evolutionary states, and asteroseismically-derived masses and radii. Additionally, we include kinematic information from <em>Gaia</em>. We investigate the multi-dimensional space of abundance, stellar mass, and velocity with an eye toward applications in Galactic archaeology. The APO-K2 sample has a large population of low metallicity stars (~288 at [M/H] ≤ -1), and their asteroseismic masses are larger than astrophysical estimates. We argue that this may reflect offsets in the adopted fundamental temperature scale for metal-poor stars rather than metallicity-dependent issues with interpreting asteroseismic data. We characterize the kinematic properties of the population as a function of α-enhancement and position in the disk and identify those stars in the sample that are candidate components of the <em>Gaia-Enceladus</em> merger. Importantly, we characterize the selection function for the APO-K2 sample as a function of metallicity, radius, mass, νmax, color, and magnitude referencing Galactic simulations and target selection criteria to enable robust statistical inferences with the catalog.</p> <p><strong>Included Files:</strong></p> <ul> <li>The publicly available APO-K2 catalog, the is provided in the publication.</li> <li>The APO-K2 catalog without truncation to any numbers. </li> <li>The selection function relative density tables for the mass-radius parameter space. </li> <li>The selection function relative density tables for the metallicity-mass parameter space. </li> <li>The selection function relative density tables for the magnitude-color parameter space. </li> <li>The selection function relative density tables for the ν<sub>max</sub>-mag parameter space. </li> </ul>
Asteroseismology of the young open cluster NGC 2516 I: Photometric and spectroscopic observations
<p>A column-to-column explaination is here:</p> <p>gaia_dr3_source_id: Gaia DR3 source ID</p> <p>TIC: TIC number</p> <p>gaia_RA: RA by Gaia</p> <p>gaia_DEC: DEC by Gaia</p> <p>gaia_G_apparent_mag: Gaia G band magnitude</p> <p>gaia_G_apparent_mag_err: Gaia G band magnitude uncertainty</p> <p>gaia_G_absolute_mag: Gaia G band absolute magnitude, without the correction of extinction</p> <p>gaia_G_absolute_mag_err: uncertainty of gaia_G_absolute_mag</p> <p>log_Luminosity: log of luminosity, calculated by Gaia effective temperature, with the bolometric correction and extinction correction. Use with caution.</p> <p>log_Luminosity_err: uncertainty of log_Luminosity</p> <p>Gaia_Teff: effective temperature provided by Gaia. Use with caution.</p> <p>Gaia_Teff_err: uncertainty of Gaia_Teff. Use with caution. A uncertainty value of '100' means the temperature is absent by Gaia, so we use the temperature from the TIC input catalog.</p> <p>BP-RP: Gaia colour index.</p> <p>BP-RP_err: uncertainty of BP-RP</p> <p>Teff_by_spectra: effective temperature by FEROS spectra, better than Gaia_Teff, only available for nine stars. "9999" means no data available.</p> <p>Teff_by_spectra_err: uncertainty of Teff_by_spectra. "9999" means no data available.</p> <p>log_L_by_Teff_spectra: log of luminosity calculated by Teff_by_spectra, with the bolometric correction and extinction correction, better than log_Luminosity.</p> <p>log_L_by_Teff_spectra_err: uncertainty of log_L_by_Teff_spectra</p> <p>spectra_logg: log g by FEROS spectra, only available for nine stars. "9999" means no data available.</p> <p>spectra_logg_err: uncertainty of spectra_logg</p> <p>spectra_vsini: projected equatorial velocity by FEROS spectra, only available for nine stars. "9999" means no data available.</p> <p>spectra_vsini_err: uncertainty of spectra_vsini</p> <p>spectra_matellicity: matellicity by FEROS spectra, only available for nine stars. "9999" means no data available.</p> <p>spectra_matellicity_err: uncertainty of spectra_matellicity</p> <p>spectra_radial_velocity: radial velocity by FEROS spectra, only available for nine stars. "9999" means no data available.</p> <p>spectra_radial_velocity_err: uncertainty of spectra_radial_velocity</p> <p>spectra_microturbulent: microturbulent velocity by FEROS spectra, only available for nine stars. "9999" means no data available.</p> <p>spectra_microturbulent_err: uncertainty of spectra_microturbulent</p> <p>spectra_SNR: signal-to-noise ratio of the FEROS spectra</p> <p>Pi0: asymptotic spacing of g modes, measured by g modes, only available for 11 stars. '9999' means no data available.</p> <p>Pi0_err: uncertainty of Pi0</p> <p>core_rotation_g_mode: near-core rotation rate in unit of days^{-1}, measured by g modes, only available for 11 stars. '9999' means no data available.</p> <p>surface_modulation_period: surface rotation period measured by surface modulations. '9999' means no data available.</p> <p>surface_modulation_period_err: uncertainty of surface_modulation_period</p> <p> </p>
Asteroseismology and Interferometry: a powerful combination to understand Ap stars
<p>Ultra-precise, 2-min cadence, photometric data is now available on over one thousand Ap stars, thanks to the NASA Transiting Exoplanet Survey Satellite (TESS) mission. These data is enabling the first unbiased search for pulsations among Ap stars, which, in turn, will impose stringent tests on current theoretical models for the driving of pulsations in these stars. To be successful, these tests require also that the global parameters of the stars are determined with great accuracy. In this talk we will present recent results from an ongoing interferometric programme on Ap stars aimed at establishing their radii and effective temperatures in a quasi model-independent way. We will then show how these accurate parameter determinations are enabling us to test the driving of pulsations in Ap stars, in combination with the asteroseismic data. Finally, we will show how the small cohort of stars in reach of interferometry is being used to test other methods for the computation of stellar parameters that are applicable to a vaster number of Ap stars and how this may, in turn, allow us to check the evolution of their magnetic properties.</p>
Merger seismology: distinguishing massive merger products from genuine single stars using asteroseismology (online data)
<h1><strong>Input and output files for "Merger seismology: distinguishing massive merger products from genuine single stars using asteroseismology" (Henneco et al. 2024b)</strong></h1> <p>This repository contains the MESA and GYRE input files required to reproduce the models used in Henneco et al. (2024b), as well as some of the output files.</p> <p><strong>[MESA version]</strong><br>MESA r12778<br>MESA SDK 20.3.2</p> <p><strong>[GYRE version]</strong><br>GYRE 7.0<br>MESA SDK 22.6.1</p> <p> </p> <h2><strong>input_files</strong></h2> <p>This directory contains the template input files for the MESA and GYRE models.</p> <h3><strong>gyre</strong></h3> <p>- gyre_nonrot_template.in: GYRE inlist for computations without rotation<br>- gyre_rot_template.in: GYRE inlist for computations, including rotation using the TAR<br>- gyre_rot_pert_template: GYRE inlist for computations including rotation using the perturbative approach</p> <h3><strong>mesa</strong></h3> <p>- <strong>genuine_single</strong>: MESA work directory for genuine single stars<br>- <strong>merger_product</strong>: MESA work directory for merger products via the fast accretion method<br>- <strong>zams_z0142_y2703.data</strong>: ZAMS models used to start all MESA computations from</p> <h2> </h2> <h2><strong>output</strong></h2> <h3><strong>mesa</strong></h3> <p>In this directory, we provide the MESA history and profile (GYRE format only) output for the MESA models used in our work.<br>The more detailed regular profile files are left out because of storage constraints, but these can be transferred upon reasonable request.</p> <p>- mXX_plus_mYY_at_rZZ: XX + YY Msol merger product model where the fast accretion method was invoked when the HG star had a radius of ZZ Rsol<br>- mXX: genuine single-star model of XX Msol</p> <h3><strong>gyre</strong></h3> <p>This directory contains the GYRE summary files and input files (with the frequency ranges specific to these models). The detail files are left out because of storage constraints, but these can be transferred upon reasonable request. </p> <p><strong>[suffixes]</strong><br>NAD: nonadiabatic computations<br>pmodes: computations in frequency ranges appropriate for pressure modes<br>Om20_PERT: computations including rotation (20% of critical) using the perturbative approach<br>Om20_TAR: computations including rotation (20% of critical) using the TAR</p> <p>Except for the computations in `m6.0_plus_m2.4_at_r9.0`, the GYRE computations have been made only for a specific MESA profile (the profile at the time when the models were seismically compared).<br>These are:</p> <p>-<strong> m6.0_plus_m2.4_at_r9.0</strong>: profile 38<br>- <strong>m7.8</strong>: profile 14<br>- <strong>m9.0_plus_m6.3_at_r10.4</strong>: profile 62<br>- <strong>m13.6</strong>: profile 16</p> <p>For the `m6.0_plus_m2.4_at_r9.0` model, GYRE computations have been made for profiles 27 -- 52 (see Section 4.2).</p>
Exploring the Helium Core of the δ Scuti Star CoRoT 102749568 with Asteroseismology
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2017ApJ...834..146C/abstract">Chen et al. (2017)</a>. MESA version 7624.</p> <p>Publication DOI: <a href="https://doi.org/10.3847/1538-4357/834/2/146">10.3847/1538-4357/834/2/146</a></p>
Asteroseismology of the nearby SN II Progenitor Rigel. II. epsilon-mechanism Triggering Gravity-mode Pulsations?
<p>MESA inlist associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2012ApJ...749...74M">Moravveji et al. (2012)</a>. MESA version 3723.</p> <p>Publication DOI: <a href="https://doi.org/10.1088/0004-637X/749/1/74">10.1088/0004-637X/749/1/74</a></p>
The Betelgeuse Project II: asteroseismology
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.tmp.1377N/abstract">Nance et al. (2018)</a>. MESA version 6208 and 7624.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/sty1418">10.1093/mnras/sty1418</a></p>
Asteroseismology of KIC 7107778: a binary comprising almost identical subgiants
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.476..470L/abstract">Li et al. (2018)</a>. MESA version 8845.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/sty222">10.1093/mnras/sty222</a></p>
Modelling Kepler red giants in eclipsing binaries: calibrating the mixing-length parameter with asteroseismology
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.475..981L/abstract">Li et al. (2018)</a>. MESA version 8118.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/stx3079">10.1093/mnras/stx3079</a></p>
Calibrating angular momentum transport in intermediate-mass stars from gravity-mode asteroseismology
<p>Best-matching MESA stellar evolution models and GYRE stellar pulsation models of the seven stars presented in Mombarg (2023).</p> <p>'MESA_inlist_template_for_GYRE' is the inlist for MESA to compute the models used for the asteroseismic modelling, 'GYRE_inlist_template.in' is the inlist for GYRE to compute the eigenmodes. </p> <p>'MESA_inlist_template_AM_transport' is the inlist for MESA to compute rotating models with angular momentum transport that were used to predict the near-core and surface rotation frequencies.</p>
Inlist and Data Files for "Mixed Mode Asteroseismology of Red Giant Stars Through the Luminosity Bump"
<p>MESA (r12778) and GYRE (version 6.0) inlist files used in the work described in "Mixed Mode Asteroseismology of Red Giant Stars Through the Luminosity Bump". Published in The Astrophysical Journal, Volume 931, Issue 2, id.116 </p> <p>Two subdirectories are provided in the archive:</p> <p>1) The directory called "inlists_and_src" contains different MESA inlist files for different evolutionary period (inlist_pms=pre main sequence to beginning of the red giant phase and inlist_rgb=red giant branch through the RGB luminosity bump) of the stellar model. The four subdirectories refer to the four overshooting prescriptions described in the paper. The different inlist files for the different evolutionary states are called by putting their names in the "inlist" file. Two example gyre (version 6.0) inlists are also included in the "inlists" subdirectory. The inlist titled gyre_pi.in calculates the radial, dipole, and quadrupole pi mode frequencies, while the inlist titled gyre.in calculates the non-pi mode frequencies. </p> <p>A custom diffusion cutoff (see Viani et al. 2018, ApJ, 858, 28) are included in the run_star_extras.f file in the "src" subdirectories. There is also a custom subroutine called "other_adjust_mlt_gradT_fraction_overshoot" which is used to change the temperature gradient within the overshooting region for models incorporating full/penetrative overshoot. The subroutine is activated by setting "x_logical_ctrl(1)" to .true. in the MESA inlists. The amplitude of the full overshooting region is controlled with "x_ctrl(1)"</p> <p>2) The subdirectory named "example_data" include the MESA modelling results used in the paper to produce figure 16, showing the evolution of the gravity mode phase offset through the red giant branch luminosity bump. The GYRE-calculated frequencies are included in the GYRE_OUTPUTS subdirectories. In these models, overshooting from the red giant convective envelope was turned off. </p>
A calibration point for stellar evolution from massive star asteroseismology: supplementary dataset
<p>Dataset related to the article "A calibration point for stellar evolution from massive star asteroseismology" by Burssens et al. 2022 published in Nature Astronomy on the 22nd of June 2023. </p> <p>This dataset contains:</p> <p>1) The frequency list derived from the cycle 2 TESS data set of HD192575 in machine-readable format. Units are provided in the article. </p> <p>2) The MESA/GYRE inlists needed to reproduce models and figures. </p> <p>See the article for more detailed information.</p> <p> </p> <p> </p> <p> </p> <div> </div>
The Asteroseismological Richness of RCB and dLHdC Stars
<p>MESA and GYRE inlists and output files for the paper "The Asteroseismological Richness of RCB and dLHdC Stars" . Uses MESA version 22.11.1, GYRE version 6.0, and MESA SDK version x86_64-linux-21.4.1. See README for details.</p>
ScienceDex guides
Understand access before you commit
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.