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Dataset results
264 results for “Stellarator”
Chemical species in Titan's upper atmosphere observed by Cassini/UVIS stellar occultations
<p>The archive files contain the line-of-sight abundances and local densities of CH<sub>4</sub>, C<sub>2</sub>H<sub>2</sub>, C<sub>2</sub>H<sub>4</sub>, C<sub>2</sub>H<sub>6</sub>, C<sub>4</sub>H<sub>2</sub>, C<sub>6</sub>H<sub>6</sub>, HCN, HC<sub>3</sub>N, and haze particles in Titan's upper atmosphere retrieved using Cassini/UVIS stellar occultation observations during 18 Titan flybys. These results are shown in Figures 5-10 of the manuscript listed below.</p> <p>Fan, S., Zhao, D., Li, C., Shemansky, D. E., Liang, M. -C., and Yung, Y. L. (2022) Seasonal Variations of Chemical Species in Titan’s Upper Atmosphere. <em>The Planetary Science Journal.</em></p>
Multi-dimensional hydrodynamic simulations of stellar objects
<p>Supplementary material for the ArbeitsgruppenInspirationsMesse event</p>
Explaining the luminosity spread in young clusters: proto and pre-main sequence stellar evolution in a molecular cloud environment
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2018MNRAS.474.1176J">Jensen & Haugbølle (2018)</a>. MESA version 8845.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/stx2844">10.1093/mnras/stx2844</a></p>
Stellar models with calibrated convection and temperature stratification from 3D hydrodynamics simulations
<p>MESA T-tau data file associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.478.5650M/abstract">Stellar models with calibrated convection and temperature stratification from 3D hydrodynamics simulations</a></p>
Integrating Novel Stellarator Single-Stage Optimization Algorithms to Design the Columbia Stellarator Experiment - Dataset
<p>Data related to the publication by A. Baillod <em>et.al., </em>Integrating Novel Stellarator Single-Stage Optimization Algorithms to Design the Columbia Stellarator Experiment, https://arxiv.org/abs/2409.05261</p>
Stellar Stream Models in the presence of the Milky Way and LMC
<p>These files include simulated stream models from Shipp et al. 2021 (https://ui.adsabs.harvard.edu/abs/2021arXiv210713004S/abstract).</p> <p>These streams are simulated using a modified Lagrange Cloud Stripping technique developed in Gibbons 2014, in a McMillan 2017 Milky Way potential, and with an LMC modeled as a Hernquist profile, with details described in Shipp et al. 2021. These are best-fit models resulting from fits to data from the Southern Stellar Stream Spectroscopic Survey (S5), Gaia, and the Dark Energy Survey (DES).</p> <p>The columns, as listed in the file headers, are ra and dec (deg), stream coordinates phi1 and phi2 (deg), proper motion in ra and dec (mas/yr, without reflex correction), radial velocity (km/s), Heliocentric distance (kpc), and stream positions and velocities in standard Galactocentric cartesian coordinates, x, y, z (kpc), vx, vy, vz (km/s).</p> <p>Please cite <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv210713004S/abstract">Shipp et al. 2021</a> if you make use of this data.</p>
SolSysELTs2022 Part II: Unveiling the trans-Neptunian belt through stellar occultations in the ELTs era
<p>Invited talk: presentation and video recording</p>
Low-mass stellar models (MESA v15140 inlists)
<p>Low-mass stellar models (MESA v15140 inlists)</p>
Stellar properties of observed stars stripped in binaries in the Magellanic Clouds - Spectral Models
<p>This Zenodo repository is one of three Zenodo repositories related to the article "Stellar properties of observed stars stripped in binaries in the Magellanic Clouds" by Y. Götberg, M.R. Drout, A.P. Ji, J.H. Groh, B.A. Ludwig, P.A. Crowther, N. Smith, A. de Koter, and S.E. de Mink. In the article, we analyze the optical spectra of ten stars and measure their stellar properties using spectral fitting. This repository contains the full spectral model grid computed using the 1D non-LTE radiative transfer code CMFGEN (see Hillier & Miller 1998 and http://kookaburra.phyast.pitt.edu/hillier/web/CMFGEN.htm). The grid spans three parameters: temperature, surface gravity, and surface hydrogen mass fraction (which also sets the surface helium mass fraction; Y = 1 - X - Z). See Section 4.1 for more details. Below, we describe the content presented here in more detail:</p> <ul> <li><strong>0_ReadMe.txt</strong>: A text file where we describe some more details regarding the content.</li> <li><strong>S41_spectral_model_grid_parameters.txt (95 KB):</strong> A table containing relevant parameter information for each model in the spectral model grid presented in Section 4.1.</li> <li><strong>S41_spectra_spectral_model_grid.tar.gz (479MB)</strong>: A .tar.gz containing the spectral energy distributions and normalized spectra in a text file for each model. The full CMFGEN models are provided as well (see below). This .tar.gz becomes 3.2 GB when inflated.</li> <li>Complete CMFGEN models for the full spectral model grid. Because of the size of these models, we group them into tarballs with one surface hydrogen mass fraction and one effective temperature, labeled for example <strong>XHs0.01_T40000.tar.gz</strong> (that is, this tarball contains a set of models with different surface gravity). Each of these have a size of ~1-3GB and when inflated the total content is ~5GB, and each model has about 500MB.</li> </ul>
Simulated stellar halo in the presence of the LMC
<p>This file contains a simulated Milky Way stellar halo from Erkal et al. 2020 (<a href="https://ui.adsabs.harvard.edu/abs/2020arXiv200111030E/abstract">https://ui.adsabs.harvard.edu/abs/2020arXiv200111030E/abstract</a>) which has been evolved in the presence of a 1.5e11 Msun LMC. This stellar halo has a nearly constant anisotropy of 0.5. As described in the header, the first 6 columns give the Galactocentric position and velocity of each particle in cartesian coordinates and the next 6 columns give the observables from the Sun's location (l,b,dist,mu_l*,mu_b,v_gsr). The Sun is taken to be at a distance of 8.122 kpc in the -x direction. Note that the proper motions are reflex corrected.</p> <p>Please cite <a href="https://ui.adsabs.harvard.edu/abs/2020arXiv200111030E/abstract">Erkal et al. 2020</a> if you make use of this simulation.</p>
Stellar Tracks (i.e., MESA history files) used in the article "On Stellar Evolution In A Neutrino Hertzsprung-Russell Diagram"
<p>MESA history files (i.e. stellar tracks) for all masses in the article "On Stellar Evolution In A Neutrino Hertzsprung-Russell Diagram". Files have been compressed with xz. To decompress, xv --decompress filename.</p>
The Influence of Stellar Contamination on the Interpretation of Near-Infrared Transmission Spectra of Sub-Neptune Worlds around M-Dwarfs
<p>Supplementary Figures displaying posterior probability distributions of all simulation scenarios discussed in <em><strong>The Influence of Stellar Contamination on the Interpretation of Near-Infrared Transmission Spectra of Sub-Neptune Worlds around M-dwarfs. </strong></em></p> <p>Arxiv link to the paper: https://arxiv.org/abs/1912.04389</p> <p>The directory structure is as follows: </p> <p>1) 30ppm_JWST_NIRISS_BIAS: Cases with varying levels of stellar contamination and varying planetary atmospheric scenarios (clear/cloudy/high-metallicity) over the JWST NIRISS-like bandpass with 30ppm spectro-photometric precision. Here we show that there is a bias incurred in the retrieval results when fitting with a model not accounting for the stellar contamination correction.</p> <p>2) 30ppm_JWST_NIRCAM_BIAS: Case of 14% spot and 63% faculae over the JWST-NIRCam like bandpass with 30ppm precision for a cloudy atmosphere planet.</p> <p>3) JWST_NIRISS_VARY_PRECISION: Cases with varying levels of stellar contamination for a high-metallicity+cloudy planetary atmosphere exploring different JWST precisions from 15-120ppm. Here we show that the bias incurred when retrieving with the uncorrected atmosphere model persists over our grid of JWST sensitivities with increasing levels of stellar contamination. However, this bias is not noteworthy for spot-covering fractions below 1%. </p> <p>4) 30ppm_JWST_NIRISS_NO_IMPROVEMENT_WITH_JOINT_RETRIEVAL_OF_STELLAR_SPECTRUM: Case of 12% spot covering fraction with a high-metallicity+cloudy planetary atmosphere (with 30ppm precision over NIRISS-like bandpass) shows no improvement in the precision of planetary temperature, metallicity, and carbon-to-oxygen ratio despite acquiring improved constraints on the stellar contamination parameters directly from the disk-integrated spectrum of the star. </p> <p>5) 30ppm_JWST_NIRISS_STELLAR_MODEL_DIFF_BIAS: Case of 12% spot covering fraction with a high-metallicity+cloudy planetary atmosphere (with 30ppm precision on the NIRISS-like bandpass range) incorporating "realistic" stellar contamination with a different stellar model. Here we show that there is a bias that arises in the retrievals due to generational stellar model differences (also mimicking stellar model-data differences in our example case) despite including the correction for stellar contamination. Our work suggests that planetary parameter retrievals, despite correcting for stellar contamination are heavily dependent on an accurate characterization of the stellar photosphere. </p> <p>*** In addition to the supplementary figures in the above mentioned directories, you can also access a high-resolution version of Figure 10 from the paper, accompanied by the full retrieval corner plot illustrating bias induced due to stellar model differences. </p> <p>*These figures have made use of the pygtc plotting routine for displaying posterior probability distribution corner plots (Bocquet et al, (2016), pygtc: beautiful parameter covariance plots (aka. Giant Triangle Confusograms), Journal of Open Source Software, 1(6), 46, doi:10.21105/joss.00046)</p>
Dataset for Wistell-A stellarator
<p>The dataset includes three VMEC input files, one for a midscale device and one for a reactor scale device and one for the turbulence reduced configuration. These configurations were featured in the publication in the Journal of Plasma Physics: "Advancing the Physics Basis for Quasihelically Symmetric Stellarators" <br> </p> <p>Also included are coils for a reactor scale device. </p>
INCLINATION EXCITATION OF SOLAR SYSTEM DEBRIS DISK DUE TO STELLAR FLYBYS (Dataset)
<p>This upload contains the output files for simulations which recreate flyby stellar encounters upon an idealized thin disk of test particles (Moore, Li, & Adams submitted; <a href="https://arxiv.org/abs/2007.15666">https://arxiv.org/abs/2007.15666</a>). Each folder has a readme to assist in navigating the data.</p> <p>These simulations were conducted using the Mercury Integrator (Chambers, J. E. 1999, MNRAS, 304, 793) and the output files are modified "element.out" equivalents. Each row of output file corresponds to an object in the simulation. The first column contains the final semi-major axis of the corresponding object. The second column contains the final eccentricity of the corresponding object. The third column contains the final inclination of the corresponding object.</p>
Stellar specific intensity models used in "Hiding in plain sight: observing planet-starspot crossings with the James Webb Space Telescope"
<p>These stellar specific intensity models were used in the paper "Hiding in plain sight: observing planet-starspot crossings with the James Webb Space Telescope" to simulate starspot contrast spectra. See more details in the README file contained in the folder.</p>
On the detection of stellar wakes in the Milky Way: a deep learning approach
<p>The machine learning dataset used in the work of "On the detection of stellar wakes in the Milky Way: a deep learning approach". The .tar contains .h5 files for four different subhalo target masses such that each file is generated from a unique simulation seed. Each file contains data from a single simulation run and is comprised of 100 samples which are generated by sampling 1% of all star particles from a particular simulation snapshot. Prior to sampling particles, we split the simulation box into three equal slices in the Z-coordinate and bin the data onto the X-Y plane with 32 bins on each axis. Each sample is then characterised by a 2D histogram of shape (32, 32, 12) with the last dimension containing the training features which are the overdensity, mean X-Y velocity, X-Y velocity dispersion and divergence in X-Y for the three Z-slices.</p>
Results of Modeling Kepler Eclipsing Binaries: Homogeneous Inference of Orbital & Stellar Properties
<p>These are the parameter estimation results (thinned versions of the full MCMC analysis) from the paper "Modeling Kepler Eclipsing Binaries: Homogeneous Inference of Orbital & Stellar Properties" by Windemuth et al. (2019). </p>
Inlists for paper: Simulating a stellar contact binary merger – I. Stellar models
<p>We study the initial conditions of a common envelope (CE) event resulting in a stellar merger. A merger’s dynamics could be understood through its light curve, but no synthetic light curve has yet been created for the full evolution. Using the smoothed particle hydrodynamics (SPH) code StarSmasher, we have created three-dimensional (3D) models of a 1.52 M<sub>⊙</sub> star that is a plausible donor in the V1309 Sco progenitor. The integrated total energy profiles of our 3D models match their initial one-dimensional (1D) models to within a 0.1 per cent difference in the top 0.1 M<sub>⊙</sub> of their envelopes. We have introduced a new method for obtaining radiative flux by linking intrinsically optically thick SPH particles to a single stellar envelope solution from a set of unique solutions. For the first time, we calculated our 3D models’ effective temperatures to within a few per cent of the initial 1D models, and found a corresponding improvement in luminosity by a factor of ≳10<sup>6</sup> compared to ray tracing. We let our highest resolution 3D model undergo Roche lobe overflow with a 0.16 M<sub>⊙</sub> point-mass accretor (<em>P</em> ≃ 1.6 d) and found a bolometric magnitude variability amplitude of ∼0.3 – comparable to that of the V1309 Sco progenitor. Our 3D models are, in the top 0.1 M<sub>⊙</sub> of the envelope and in terms of total energy, the most accurate models so far of the V1309 Sco donor star. A dynamical simulation that uses the initial conditions we presented in this paper can be used to create the first ever synthetic CE evolution light curve.</p>
From solar to stellar flare characteristics. On a new peak size distribution for G-, K-, and M-dwarf star flares
<p>This dataset contains additional material for the research paper "From solar to stellar flare characteristics. On a new peak size distribution for G-, K-, and M-dwarf star flares", Astron. Astrophys., 2018.</p> <p>Based on the flare list available at http://156.17.94.1/sphinx_l1_catalogue/SphinX_cat_main.html, here peak X-ray flare intensities of Q- to C-class flares measured by the SphinX instrument (see, e.g., Kotov, 2011; Sylvester et al., 2011, 2012; Gburek et al., 2011a,b, 2013; Gryciuk et al., 2017) during the solar minimum of <strong>2009</strong> and their corresponding GOES E > 10 MeV peak proton fluxes are given.</p> <p><br> Column 1: Month<br> Column 2: Day<br> Column 3: X-ray flux peak hour<br> Column 4: X-ray flux peak minute<br> Column 5: X-ray flare peak intensity (W/m<sup>2</sup>)<br> Column 5: GOES E > 10 MeV peak proton flux (pfu)<br> Column 6: Flare location (according to the SphinX-database)</p>
The catalogue of "MaNGA DynPop - II. Global stellar population, gradients, and star-formation histories from integral-field spectroscopy of 10K galaxies: link with galaxy rotation, shape, and total-density gradients"
<p><strong>NOTE: Three parameters related to dust extinction ("delta_Map", "Fred_tot_Map", "Fred_gal_Map") in v1 catalogue are incorrectly saved, we have updated the catalogue in <a href="https://zenodo.org/records/15742825">https://zenodo.org/records/15742825</a> .</strong></p> <p> </p> <p>This catalogue is related to the paper "<strong>MaNGA DynPop - II. Global stellar population, gradients, and star-formation histories from integral-field spectroscopy of 10K galaxies: link with galaxy rotation, shape, and total-density gradients</strong>" by <strong>Lu et al. </strong><a href="https://ui.adsabs.harvard.edu/abs/2023MNRAS.tmp.2611L/abstract">https://ui.adsabs.harvard.edu/abs/2023MNRAS.tmp.2611L/abstract</a>. In this paper, we analyze the stellar population properties and star formation histories for over 10,000 MaNGA galaxies.</p> <p>Below are the descriptions of the files: </p> <ul> <li><strong>DynPop2_SPSFH_v1.hdf5 </strong>A HDF5 file containing the catalogue.</li> <li><strong>HDF5_reading_script.py</strong> A Python script to read the catalogue from the HDF5 file.</li> <li><strong>SP_catalog_explanation.pdf</strong> The data explanations for the catalogue, also see Table B1 in the paper. </li> </ul>
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