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264 results for “Stellarator”
Data and Code From Formation of Stripped Stars From Stellar Collisions in Galactic Nuclei
<p>This repository is for the paper "Formation of Stripped Stars From Stellar Collisions in Galactic Nuclei" by Charles F. A. Gibson. It is associated with manuscript number ApJ AAS55868.</p> <p>We include the MESA inlists, SPH input files, and the last SPH output file for the StarSmasher relaxations of the parent models in Table 1 and collisions from Tables 2 and 3.</p> <p>We also include the StarSmasher source code with the Stretchy HCP relaxation technique and the post processing codes used to generate MESA input from the StarSmasher output.</p> <p>Finally, we provide the MESA input files for the post-collision stellar evolution of the models shown in Figures 7 and 9.</p>
Data for the paper "Stellarator optimization for good magnetic surfaces at the same time as quasisymmetry"
<p>Input and output files for computations in the publication "Stellarator optimization for good magnetic surfaces at the same time as quasisymmetry"</p>
Variable stellar outflows as a probe to magnetic fields and other physical characteristics of hot, massive stars
<p>It is now clear that the radiatively driven outflows from hot, massive stars are far more complex than the simple homogeneous and spherically symmetric flows originally envisioned. With the advent of high resolution, high cadence observations of various types in the past decades, a myriad of phenomena have been uncovered that can help us reach a better understanding of the parameters and characteristics of the stars from which these winds originate. This in turn has important ramifications on the various phases of evolution of the star and on the way it will ultimately end its life. In this talk, I will review the many observational signatures of variable stellar outflows of massive stars and describe how they relate to physical characteristics of the underlying star, with a particular emphasis on magnetic fields.</p>
Galactic cosmic ray fluxes for a number of nearby Sun-like stellar systems
<p>This data set corresponds to the simulation data presented in the article "Charting nearby stellar systems: The intensity of Galactic cosmic rays for a sample of solar-type stars" (Rodgers-Lee, Vidotto & Mesquita, MNRAS, 2021). Details of the stellar wind and cosmic ray model used for the simulations are available in the article.</p> <p>The data consists of the differential intensity of Galactic cosmic rays as a function of cosmic ray kinetic energy at different orbital distances from the star. The data is given for a number of different stellar systems. The first line gives the column headings.</p> <p>File names are formatted as "gcr_data_XXX.dat" where "XXX" corresponds to the name of the star considered. The simulation details can be found in Tables 1 and 2 of the article.</p>
Stellar chromospheric activity database of solar-like stars based on the LAMOST Low-Resolution Spectroscopic Survey
<p>A stellar chromospheric activity database of solar-like stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains spectral bandpass fluxes and indexes of Ca II H and K lines derived from 1,330,654 high-quality LRS spectra of solar-like stars. We measure the mean fluxes at line cores of the Ca II H and K lines using a 1 Å rectangular bandpass and a 1.09 Å FWHM triangular bandpass, as well as the mean fluxes of two 20 Å wide pseudocontinuum bands on the two sides of the lines. Three activity indexes of Ca II H and K lines, <em>S</em><sub>rec</sub> based on the 1 Å rectangular bandpass and <em>S</em><sub>tri</sub> and <em>S<sub>L</sub></em> based on the 1.09 Å FWHM triangular bandpass, are evaluated from the measured fluxes to quantitatively indicate the chromospheric activity level. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H and K lines for all the spectra in the database. This database, with more than one million high-quality LAMOST LRS spectra of Ca II H and K lines and basal chromospheric activity parameters, can be further used for investigating activity characteristics of solar-like stars and solar-stellar connection.</p> <p> </p> <p>The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams of Ca II H and K lines.</p> <p>(1) Catalog of Spectral Sample and Activity Parameters<br> CaIIHK_Sindex_LAMOST_DR7_LRS.csv<br> (see Table3 in the paper 2022_ApJS_263_12 for description of the columns)</p> <p>(2) Library of Spectrum Diagrams of Ca II H and K lines<br> spectrum_diagrams_000-049.zip (46 subfolders)<br> spectrum_diagrams_050-099.zip (40 subfolders)<br> spectrum_diagrams_100-149.zip (47 subfolders)<br> spectrum_diagrams_150-174.zip (25 subfolders)<br> spectrum_diagrams_175-199.zip (24 subfolders)<br> spectrum_diagrams_200-224.zip (24 subfolders)<br> spectrum_diagrams_225-249.zip (23 subfolders)<br> spectrum_diagrams_250-259.zip (10 subfolders)<br> spectrum_diagrams_260-274.zip (12 subfolders)<br> spectrum_diagrams_275-299.zip (23 subfolders)<br> spectrum_diagrams_300-349.zip (41 subfolders)<br> spectrum_diagrams_350-374.zip (20 subfolders)<br> spectrum_diagrams_375-399.zip (19 subfolders)<br> spectrum_diagrams_400-424.zip (23 subfolders)<br> spectrum_diagrams_425-449.zip (22 subfolders)<br> spectrum_diagrams_450-499.zip (35 subfolders)<br> spectrum_diagrams_500-549.zip (27 subfolders)<br> spectrum_diagrams_550-599.zip (38 subfolders)<br> spectrum_diagrams_600-649.zip (32 subfolders)<br> spectrum_diagrams_650-699.zip (26 subfolders)<br> spectrum_diagrams_700-749.zip (28 subfolders)</p>
Data for the paper "Direct Microstability Optimization of Stellarator Devices"
<p>This archive contains data and source code used for the paper "Direct Microstability Optimization of Stellarator Devices".</p>
MESA inlists for 'Revisiting the Red Giant Branch Hosts KOI-3886 and $\iota$ Draconis. Detailed Asteroseismic Modeling and Consolidated Stellar Parameters' by Campante et al.
<p>MESA inlists used in preparation of the paper 'Revisiting the Red Giant Branch Hosts KOI-3886 and $\iota$ Draconis. Detailed Asteroseismic Modeling and Consolidated Stellar Parameters' by Campante et al. Two folders are provided in the .zip file:</p> <ul> <li>TL_Pipeline — inlists (MESA release version 12115) used to build the grid of stellar models used in Sect. 4.1 of the paper.</li> <li>JO_Pipeline — inlists (MESA release version 12778) used to build both grids of stellar models used in Sect. 4.2 of the paper.</li> </ul>
Finding Stellar Streams in the Milky Way with CWoLa
<p>These datasets are designed to accompany the paper <em>Weakly-Supervised Anomaly Detection in the Milky Way </em>by M. Pettee, S. Thanvantri, B. Nachman, D. Shih, M. R. Buckley, and J. H. Collins (<a href="https://arxiv.org/abs/2305.03761">https://arxiv.org/abs/2305.03761</a>). They illustrate how the Classification Without Labels (CWoLa) technique can be applied in the search for localized anomalies -- in this case, cold stellar streams -- in the <em>Gaia </em>DR2 dataset. We consider both simulated stellar streams and the known stream GD-1. The codebase is located at <a href="https://github.com/hep-lbdl/GaiaCWoLa">https://github.com/hep-lbdl/GaiaCWoLa</a>. </p> <p>These datasets are all formatted as Pandas DataFrames, and can be loaded using `df = pd.read_hdf(file)`. Datasets ending in `*_cwola.h5*` indicate that CWoLa has been applied to the stars in that dataset. For this analysis, we consider circular "patches" of the sky of radius 15° from the Gaia DR2 dataset. </p> <p>Columns include: </p> <ul> <li>μ_δ: Proper motion (declination)</li> <li>μ_α: Proper motion (right ascension)</li> <li>δ: Declination</li> <li>α: Right ascension</li> <li>α_wrapped: Right ascension, wrapped such that all angles are > 0 </li> <li>b-r: Color</li> <li>g: Magnitude</li> <li>ϕ: Rotated & centered right ascension </li> <li>λ: Rotated & centered declination </li> <li>μ_ϕcosλ: Rotated & centered proper motion (right ascension) </li> <li>μ_λ: Rotated & centered proper motion (declination) </li> <li>stream: Boolean label (True if part of ground truth labeling for GD-1)</li> <li>patch_id: Index of the 21 patches of the GD-1 scan</li> <li>nn_score: CWoLa classifier score (0 = more background-like; 1 = more signal=like)</li> <li>5d_distance: For the potential GD-1 member candidates, the 5D Euclidean distance to the nearest labeled star</li> </ul> <p>Files include:</p> <ul> <li>gd1_1_patch.h5 <ul> <li>Example patch of GD-1</li> </ul> </li> <li>gd1_21_patches_cwola.h5 <ul> <li>Results from applying CWoLa to the 21 patches spanning GD-1 </li> </ul> </li> <li>promising_stars.h5 <ul> <li>A list of stars identified by CWoLa that do not belong to the labeled GD-1 stream catalogue, but are close in 5D Euclidean space to labeled stars. Ordered in descending order by CWoLa classifier score. </li> </ul> </li> <li>scan_bump_cwola.h5 <ul> <li>An example of how to apply CWoLa in a scan where the stream location is unknown</li> </ul> </li> <li>scan_no_bump_cwola.h5 <ul> <li>An example of how to apply CWoLa in a scan where the stream location is unknown</li> </ul> </li> <li>simulated_100_patches.h5 <ul> <li>Results from applying CWoLa to 100 simulated streams </li> </ul> </li> <li>simulated_patch.h5 <ul> <li>A full simulated stream </li> </ul> </li> <li>simulated_patch_cwola.h5 <ul> <li>Results from applying CWoLa to the example simulated stream</li> </ul> </li> </ul> <p>To recreate the full scan across GD-1, one would need to use the original 21 patches of Gaia DR2 located at <a href="https://doi.org/10.5281/zenodo.7897935">10.5281/zenodo.7897935</a> that were constructed for <a href="https://arxiv.org/abs/2104.12789">arXiv:2104.12789</a> [astro-ph.GA). GD-1 labels were derived from <a href="https://doi.org/10.5281/zenodo.1295543">10.5281/zenodo.1295543</a>. </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>
MCMC chains representing stellar halo fits for Lane et al. (2023) paper published in MNRAS
<p>Results for the paper entitled "The stellar mass of the Gaia-Sausage/Enceladus accretion remnant" published in MNRAS by Lane, Bovy, & Mackereth. The results are in the form of MCMC posterior chains, which are used to generate the results recorded in Table 1 of the manuscript. The process used to generate these data is outlined in section 2 (data & sample preparation), section 3 (Density modelling framework), and section 4 (Presentation of results) of the manuscript.</p> <p>The data are contained within a single gzipped .tar file, organized in two directories: gse/ containing the results for fits to the GS/E kinematic samples, and all/ containing the results for the fits to the whole halo sample. In the gse/ directory, there are three directories: eLz/, AD/, and JRLz/, containing the results for the fits to each of the respective kinematically defined subsamples. Within these directories, as well as within all/, are a final set of directories for each of the eight density profiles considered in the work.</p> <p>Within each of these directories are a single file named "samples.npy" which is a binary file (see <a href="https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format">this link</a> for format information) containing a numpy array of shape (# of parameters, # of posterior samples). The number of posterior samples is the number of walkers (100) times the number of samples per walker (10,000), minus the number of burn-in steps per walker (1,000) = 900,000. The number of parameters can be inferred from the density profiles definitions in section 3 of the manuscript, and the ordering of the parameters is the same as in Table 1. The units of the parameters are as in Table 1, except for the parameters theta and phi which are scaled such that they are defined on the interval (0,1), representing the intervals (0,2pi) and (0,pi) respectively.</p>
Fortuitous Observations of Potential Stellar Relay Probe Positions with GBT - Results Data Table
<p>This record contains the data table produced as part of "Fortuitous Observations of Potential Stellar Relay Probe Positions with GBT" by Palumbo et al. </p>
Ages and metallicities of stellar clusters using S-PLUS narrow-band integrated photometry: the Small Magellanic Cloud
<p>These are the final photometric quantities measured in the work "Ages and metallicities of stellar clusters using S-PLUS narrow-band integrated photometry: the Small Magellanic Cloud". The raw S-PLUS images are available upon request to the corresponding author. Nevertheless, the complete S-PLUS data will become publicly available alongside the next data release, scheduled for 2023.</p>
A Study of Sotatercept for the Treatment of Pulmonary Arterial Hypertension (MK-7962-003/A011-11)(STELLAR)
ClinicalTrials.gov study NCT04576988. IPD Sharing: YES. Countries: 21. Publications: 4.
Scalable TELeheaLth Cancer CARe: The STELLAR Program to Treat Cancer Risk Behaviors
ClinicalTrials.gov study NCT05687604. IPD Sharing: YES. Countries: 1. Publications: 2.
Numerical code and data for the stellar structure and dynamical instability analysis of generalised uncertainty white dwarfs
Open the record for dataset details and reuse information.
Eclipses of continuous gravitational waves as a probe of stellar structure
<p>Jupyter notebooks to reproduce the results and figures of the paper "Eclipses of continuous gravitational waves as a probe of stellar structure". Input files and data produced from the MESA simulations in the paper is also included. MESA version used is 10398.</p> <p>The jupyter notebooks included are:</p> <p>- Notebook.ipynb: Containing all calculations and plots except for the pop-synth section.</p> <p>- accreting_NS.ipynb: Containing the calculations and plots for the pop-synth section.</p> <p>Further details can be found inside these notebooks.</p> <p> </p> <p>The mesa input files are contained in</p> <p>- mesa_models/sun: For the solar model used.</p> <p>- mesa_models/LMXB: For the low mass X-ray binary model used.</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>
Data for "Calculation of permanent magnet arrangements for stellarators: A linear least-squares method"
<p>Data associated with the paper "Calculation of permanent magnet arrangements for stellarators: A linear least-squares method"</p>
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>
Files for reproducing results in Octo-Tiger: a new, 3D hydrodynamic code for stellar mergers that uses HPX parallelisation
<p>This archive contains config files for reproducing results in the paper "Octo-Tiger: a new, 3D hydrodynamic code for stellar mergers that uses HPX parallelisation"</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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