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16 results for “young stars”
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>
The winds of young Solar-type stars in the Hyades - Quiet Sun model
<p>This is the quiet Sun model from my MNRAS paper "The winds of young Solar-type stars in the Hyades"(https://doi.org/10.1093/mnras/stab1696). Please see the paper for a full description.</p>
Reproduction package for the paper "Two waves of massive stars running away from the young cluster R136"
<h2>Reproduction package for the paper "Two waves of massive stars running away from the young cluster R136".</h2> <ul> <li>This reproduction package aims for open science, with the internal API designation of 'Gold'</li> <li>Authors: M. Stoop, A. de Koter, L. Kaper, S. Brands, S. Portegies Zwart, H. Sana, F. Stoppa, M. Gieles, L. Mahy, T. Shenar, D. Guo, G. Nelemans, S. Rieder</li> <li>Paper DOI: https://doi.org/10.1038/s41586-024-08013-8</li> <li>Zenodo DOI: http://doi.org/10.5281/zenodo.10058762</li> <li>Published in Nature (date of publication: 2024/10/09)</li> </ul> <h2>Hardware</h2> <ul> <li>Tested on a MacBook Pro (13-inch, 2020, Four Thunderbolt 3 ports)</li> <li>Processor: 2 GHz Quad-Core Intel Core i5</li> <li>Memory: 32 GB 3733 MHz LPDDR4X</li> <li>Graphics: Intel Iris Plus Graphics 1536 MB</li> </ul> <h2>Required non-standard hardware</h2> <ul> <li>None</li> </ul> <h2>Software dependencies</h2> <ul> <li>Jupyterlab (4.0.8)</li> <li>Notebook (7.0.6)</li> <li>Programming languages used: Python (3.11.7)</li> <li>Python packages used: numpy (1.25.2), pandas (2.1.4), matplotlib (3.8.0), os (comes with Python) scipy (1.11.4), gaiadr3-zeropoint (0.0.4) https://gitlab.com/icc-ub/public/gaiadr3_zeropoint), astroquery (0.4.6), pymc (5.6.1), corner (2.2.2), arviz (0.16.0), pytensor (2.12.3), lmfit (1.2.2), powerlaw (1.5), rpy2 (3.5.16), seaborn (0.12.2), consistencytest (0.0.2)</li> </ul> <h2>Instructions</h2> <ul> <li>The Anaconda conda environment is given should this be needed</li> <li>All Jupyter Notebooks are ready-made to produce the raw data, intermediate and end data products</li> <li>Gaia raw data is downloaded in the Jupyter Notebook "R136_runaway_candidates.ipynb"</li> <li>Data from the literature is given in the subdirectory /tables/ or /input_files/</li> <li>Input images and files are given in the subdirectory /input_files/</li> <li>Intermediate and end data products are given in /output_files/</li> <li>Figures in the paper are produced in the Jupyter Notebooks in the subdirectory /figures/ and stored in the subdirectory /figures/figures_paper/</li> </ul> <h2>Expected Output</h2> <ul> <li>Jupyter Notebooks can be executed by "Run" -> "Run All Cells"</li> <li>The Jupyter Notebook show the expected output in their respective cell</li> <li>Expected runtime are given at the top of each Jupyter Notebook</li> <li>The Jupyter Notebook which takes the longest "R136_runaway_search.ipynb" takes 7-8 hours for the entire dataset</li> <li>A small dataset has been given in this Jupyter Notebook as a proof-of-concept</li> </ul> <h2>Instructions for use</h2> <ul> <li>Jupyter Notebooks can be executed by "Run" -> "Run All Cells"</li> </ul> <h2>Figures</h2> <ul> <li>Figures can be reproduced from the /figures/ folder.</li> <li>All material and data used are available either in the Raw Data or in the Intermediate Data</li> <li>The figures shown in the paper will be saved in ./figures/figures_paper/ folder.</li> </ul> <pre> </pre>
Introducing MADYS: the Manifold Age Determination for Young Stars | Full model database
<p>Complete database of stellar and substellar evolutionary models employed in the Manifold Age Determination for Young Stars (MADYS). For a description of the tool, please refer to the main paper. For a detailed description of individual files, it is advised to use the ad-hoc functions provided within the published package.</p> <p>Bibliographic reference: arxiv:2206.02446</p> <p>GitHub repository: https://github.com/vsquicciarini/madys</p>
ariedel/young_catalog: The Catalog of Suspected Nearby Young Stars (2016.1118)
<p>This is the Catalog of Suspected Young Stars from Riedel et al. (2017) (at time of paper submission).</p> <p>The catalog is meant to contain astrometric, photometric, and basic spectroscopic information for all stars EVER reported as being young (and nearby, with a rough outer limit of 100 parsecs plus the Pleiades and stars in the Octans moving group (both extend beyond 100 parsecs) plus field stars included in papers presenting young stars, or considered and rejected in those papers. Basically, if the star's youth was ever under consideration, this catalog should have it.</p> <p>The catalog currently contains 5350 stars, in a one-line-per-star format, with 388 columns. Every quantity has an associated reference, nearly all quantities have uncertainties, and most quantities have upper limit/lower limit/joint/deblended flags. The master file is actually an OpenDocument (.ods) spreadsheet which has the following improvements over the .csv file:</p> <p>Color-coded sections In-sheet calculations for derived quantities like Mean RV, Mean Parallax, and most photometric colors. Properties of companions that were simply copied from the primary star are in bold. For instance, if all that's known is that the star is a binary, EVERYTHING should be bolded. The procedure upon discovering a companion is to copy the entire primary star's line and bold it, and then replace those values with the ones specific to the secondary. Note that the OpenDocument and Excel files have two extra header lines as compared to the CSV</p> <p>The .csv file is probably easier to read into a program. Code for using Python 2.7+ and Astropy 0.4+ to produce a Python table is below:</p> <p>from astropy.io import ascii</p> <p>catalog = ascii.read(infilename)</p> <p>Buyer beware: This is a work in progress. There is missing data (no lithium data for The Pleiades yet; I haven't added the papers; nearly no Hyades at all because I haven't added the papers yet). Multiplicity is incomplete. The Bold/Unbolded method of dealing with multiples is not consistently applied, and I intend to supplant it with flags on every data value.</p> <p>Earlier versions exist for the purposes of reproducing prior work but are far less complete and correct; versions prior to 2016.0704 have fewer objects; versions prior to 2016.0116 do not have headers that comply with AAS journal standards.</p> <p>Comments and suggestions are welcome.</p>
Reproduction package for "What happened before?. Disks around the precursors of young Herbig Ae/Be stars"
<p>This is a basic reproduction package for the paper "What happened before?. Disks around the precursors of young Herbig Ae/Be stars" by Valegard et al. (2021)(https://doi.org/10.1051/0004-6361/202039802). It aims to provide the most important data products to check and reproduce the main results of the paper.</p>
Data from "Disk Evolution Study Through Imaging of Nearby Young Stars (DESTINYS): A Panchromatic View of DO Tau's Complex Kilo-au Environment'
<p>Reduced data from Huang et al., 2022, "Disk Evolution Study Through Imaging of Nearby Young Stars (DESTINYS): A Panchromatic View of DO Tau's Complex Kilo-astronomical-unit Environment,' ApJ, 930, 171 (arXiv:2204.01758). </p> <p>See Table 1 of the article for the corresponding observing program codes and attributions for archival data (if applicable). </p> <p><strong>Images:</strong></p> <p>DOTau_12CO_automask.image.pbcor.fits: 12CO J=2-1 image cube<br> DOTau_12CO_automask.mom1.fits: 12CO J=2-1 moment 1 map<br> DOTau_12CO_automask.pbcor.2sigcut.mom0.fits: 12CO J=2-1 moment 0 map<br> DOTau_13CO_automask.image.pbcor.fits: 13CO J=2-1 image cube<br> DOTau_13CO_automask.mom1.fits: 13CO J=2-1 moment 1 map<br> DOTau_13CO_automask.pbcor.2sigcut.mom0.fits: 13CO J=2-1 moment 0 map<br> DOTau_C18O_automask.image.pbcor.fits: C18O J=2-1 image cube<br> DOTau_C18O_automask.pbcor.2sigcut.mom0.fits: C18O J=2-1 moment 0 map<br> DOTau_C18O_automask.pbcor.mom1.fits: C18O J=2-1 moment 1 map<br> DOTau_cADI_average.fits: SPHERE H-band cADI image (pixel scale: 0.01225 arcseconds)<br> DOTau_CS_automask.image.pbcor.fits: DO Tau CS J=5-4 image cube<br> DOTau_CS_automask.mom1.fits: DO Tau CS J=5-4 moment 1 map<br> DOTau_CS_automask.pbcor.2sigcut.mom0.fits: DO Tau CS J=5-4 moment 0 map<br> DOTau_DoLP.fits: DO Tau degree of linear polarization map (pixel scale: .0245 arcseconds)<br> DOTau_IDF-RDI.fits: SPHERE total intensity image produced with IDF-RDI (pixel scale: 0.01225 arcseconds)<br> DO-TAU_NICMOS_F110W_MRDILib-18_KL-2_Pixel.fits: HST NICMOS F110W image (pixel scale: 0.075 arcseconds)<br> DO-TAU_NICMOS_F160W_MRDILib-100_KL-1_Pixel.fits: HST NICMOS F160W image (pixel scale: 0.075 arcseconds)<br> DOTau_Qphi_average.fits: SPHERE H-band Qphi image (pixel scale: 0.01225 arcseconds)<br> DO_Tau_STIS_KlipWithin160pixel_counts_s_pixel.fits: HST STIS image (pixel scale: 0.0507 arcseconds)</p> <p><strong>Measurement sets:</strong></p> <p>DOTau_12CO.ms.contsub.tar: Self-calibrated, continuum-subtracted 12CO J=2-1 visibilities<br> DOTau_13CO.ms.contsub.tar: Self-calibrated, continuum-subtracted 13CO J=2-1 visibilities<br> DOTau_C18O.ms.contsub.tar: Self-calibrated, continuum-subtracted C18O J=2-1 visibilities<br> DOTau_CS.ms.contsub.tar: Self-calibrated, continuum-subtracted CS J=5-4 visibilities</p> <p><strong>Scripts:</strong></p> <p>DOTau_1.1mmreduction.py: CASA self-cal and imaging script for CS data <br> DOTau_1.3mmreduction.py: CASA self-cal and imaging script for CO data </p>
A set of synthetic spectral energy distributions for "diskless", intermediate-mass young stars
<p>These models were published in conjunction with <em>The Duration of Star Formation in Galactic Giant Molecular Clouds. I. The Great Nebula in Carina, </em>by <a href="https://arxiv.org/abs/1906.01730">Povich et al. (2019)</a>. They will also be used in subsequent papers in that series.</p> <p>The format of these models conforms with the standards of <a href="https://doi.org/10.1051/0004-6361/201425486">Robitaille (2017)</a>, so they are compatible with the <a href="http://sedfitter.readthedocs.io/en/stable/installation.html">python implementation</a> of the <a href="https://doi.org/10.1086/512039">Robitaille et al. (2007)</a> SED fitting tool. We have pre-convolved these models with a number of useful filters, including Johnson/Bessel <em>UB</em><em>VRI, </em>UKIRT <em>ZYJHK, </em>VISTA <em>ZYJHK<sub>S</sub></em>, 2MASS <em>JHK<sub>S</sub></em>, <em>Spitzer/</em>IRAC and MIPS. </p> <p>A software pipeline implementing these models to constrain the age and mass distributions of young stellar populations is also <a href="https://doi.org/10.5281/zenodo.3234101">publicly available</a>.</p> <p><strong>Limitations of these models</strong></p> <p><em>These models produce the best results for stars more massive than the Sun and older than about 0.5 Myr. </em>They employ the pre-main-sequence evolutionary tracks of <a href="https://arxiv.org/abs/astro-ph/0003477">Siess et al. (2000)</a> and <a href="https://ui.adsabs.harvard.edu/abs/1996A&A...307..829B/abstract">Bernasconi & Maeder (1996)</a>. Numerous modern tracks offer significant improvement in the treatment of subsolar-mass stars. In addition, the Kurucz stellar atmospheres used in these synthetic SEDs work best for T<sub>eff </sub>> 4,000 K; for cooler temperatures other models, for example the PHOENIX photospheres, may be more appropriate.</p> <p>Newer evolutionary tracks covering the intermediate-mass range are now available, for example the Geneva pre-MS tracks of <a href="https://doi.org/10.1051/0004-6361/201935051">Haemmerlé et al. (2019)</a>. The principal innovation of these modern models is the treatment of accretion and location of the intermediate-mass stellar birthline. The coolest, most luminous models in this set are likely <em>unphysical</em>, representing fully-convective stars of >2 solar masses and <0.5 Myr isochronal age.</p>
The Keck/NIRC2 Young M-star Survey Data Products
<p>The Keck/NIRC2 young M-star survey data products consist of complete preprocessed <em>L'</em> coronagraphic frames, associated parallactic angles, unocculted PSF frames, Super-RDI reduced images, and final optimal contrast curves for 155 targets observed in the survey. A FITS file is associated with each target in the survey. All FITS files have been compressed together into "super-rdi-mstar-survey-data-products.zip". The file naming for the FITS data product follows the convention "<target name>_<observation date>.fits", where target name corresponds to the "Name" column and observation date corresponds to the "UT Date" column in Table 1 of Sanghi et al. (2024). The Jupyter notebook "read_fits_product.ipynb" provides an example on how to access the data products. A PDF version of the notebook is also included and serves as a README.</p> <p>The observations available here are published in <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240814268S/abstract">Sanghi et al. (2024)</a>: <em>Efficiently Searching for Close-in Companions around Young M Dwarfs using a Multi-year PSF Library</em>. For research that benefits from this compilation, please cite this Zenodo post and <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240814268S/abstract">Sanghi et al. (2024)</a>.</p>
Seismic modeling of a very young SPB star – KIC 8264293
<p>An inlists for MESA v9575, used to compute a grid of evolutionary models used in the paper "Seismic modeling of a very young SPB star – KIC 8264293".</p>
Reproduction package for the paper "Disk Evolution Study Through Imaging of Nearby Young Stars (DESTINYS): The SPHERE view of the Orion star-forming region"
Open the record for dataset details and reuse information.
Properties of intermediate- to high-mass stars in the young cluster M17 Characterizing the (pre-)Zero Age Main Sequence
<p>Data and extra figures of the paper "Properties of intermediate- to high-mass stars in the young cluster M17 -- Characterizing the (pre-)Zero Age Main Sequence" by Frank Backs. Published in Astronomy and Astrophysics.</p> <p>The observed data and the fitted models are included. The fitting algorithm Kiwi-GA is available on Github: https://github.com/sarahbrands/Kiwi-GA</p> <p>Additional figures are available. These figures give an overview of the best fit models for each line like Fig. 1 in the paper. </p>
ALMA detection of CO rotational line emission in red supergiant stars of the massive young star cluster RSGC1
<p>Input files and data for the MESA simulations in the paper "ALMA detection of CO rotational line emission in red supergiant stars of the massive young star cluster RSGC1". Runs where performed with version r23.05.1 of the MESA code using the MESA SDK version x86_64-linux-22.6.1. Folder named "Decin" contains the simulation with the new mass loss rate described in the paper, while the folder named NdJ contains the input files for the simulation performed with the Nieuwenhuijzen & de Jager rates.</p>
Animation of MS evolution in young star clusters
<p>The video shows the evolution of binary and single stellar models from 1Myr to 100Myr. </p>
Effects of close binary evolution on the main-sequence morphology of young star clusters
<p>Star cluster animation to show their evolution in the Hertzsprung-Russell diagram.</p>
SACY (Search for Associations Containing Young Stars) Catalog
The SACY (Search for Associations Containing Young Stars) Catalog contains the results from a high-resolution optical spectroscopic survey aimed to search for nearby young associations and young stars among optical counterparts of ROSAT All-Sky Survey X-ray sources in the Southern Hemisphere. 1953 late-type (B-V>=0.6), potentially young, optical counterparts were selected out of a total of 9574 1RXS sources for follow-up observations. At least one high-resolution spectrum was obtained for each of 1511 targets. This paper is the first in a series presenting the results of the SACY survey in which the sample of X-ray selected stars and the supporting optical observations are described. The SACY sample is defined by Hipparcos (<a href="https://cdsarc.cds.unistra.fr/ftp/cats/I/239">CDS Cat. <I/239></a>) and Tycho-2 (<a href="https://cdsarc.cds.unistra.fr/ftp/cats/I/259">CDS Cat. <I/259></a>) stars within an error radius of 2.6 times the positional error of the ROSAT All-Sky Bright Source Catalogue (1RXS, <a href="https://cdsarc.cds.unistra.fr/ftp/cats/IX/10">CDS Cat. <IX/10></a>). The used cut-off (B-V=0.6), corresponding approximately to a G0 dwarf, is near the hottest stars where the strength of the LiI line can be used as an youth indicator. All Hipparcos stars having M_v < 2.0 have been excluded. The northern boundary limits of the survey are given in Table 1 of the reference paper. In addition to the 1511 stars observed at least once, 115 stars with data taken from the literature have been added in order to complement the sample. In addition to these 1626 stars in the SACY sample (sources with source number prefixes of 'S'), entries for 165 other observed stars (sources with source number prefixes of 'O') are also included in this table. Most of the spectroscopic observations (~70%) were performed with the FEROS spectrograph at the 1.5m/ESO telescope at La Silla between January 1999 and September 2002 (ON-ESO agreement and ESO program identification 67.C-0123). Two more runs (ESO program identifications 072.C-0393 and 077.C-0138) were carried out at the 2.2m/ESO telescope. Another set of data (~30%) was collected at the coude spectrograph attached to 1.60m telescope at the Observatorio rio do Pico dos Dias (OPD), LNA, Brazil. Some spectra are a re-analysis of the ones taken for the PDS program. A few observations were collected using the CORALIE attached to the Swiss Euler Telescope at La Silla. UBV(RI)c photometry for part of the sample was obtained using FOTRAP at the 0.60m Zeiss telescope of the OPD. When a star was not observed photometrically by the authors, they tried to obtain some useful photometric data from the Hipparcos and Tycho Catalogues or in the available literature in the SIMBAD. For multiple stars, magnitudes and colors were corrected in order to take into account the presence of the companion(s). This table was created by the HEASARC in March 2007 based on the CDS table J/A+A/460/695, files table3.dat and table4.dat This is a service provided by NASA HEASARC .
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