Find research datasets worth reusing

opencc-by-4.0May 2020View details →

Data from: "Deep Generative Modeling of Periodic Variable Stars Using Physical Parameters"

This dataset was used for the training of a conditioned Variational Autoencoder that generates physically informed light curves of periodic variable stars. The light curves correspond to data obtained from The Optical Gravitational Lensing Experiment (<a href="https://ui.adsabs.harvard.edu/abs/1992AcA....42..253U/abstract">OGLE</a>), while ancillary information was obtained from the Gaia Data Release 2 (<a href="https://ui.adsabs.harvard.edu/link_gateway/2016A&A...595A...1G/doi:10.1051/0004-6361/201629272">GAIA DR2</a>). This repository contains the preprocessed OGLE light curves and the GAIA measurements corresponding to each cross-matched source. We also provided a subsample of cross-matched sources that were carefully validated following several steps described in the companion article (paper reference). This dataset is realized in tandem with the corresponding <a href="https://github.com/jorgemarpa/PELS-VAE">GitHub</a> and <a href="https://arxiv.org/abs/2005.07773">article</a>.

opencc-by-4.0Aug 2021View details →

SuperWASP Variable Star Photometry Archive (VeSPA)

This data set contains the metadata for periodic variable stars that have been classified by Citizen Scientists using the <a href="https://www.zooniverse.org/projects/ajnorton/superwasp-variable-stars">SuperWASP Variable Stars Zooniverse project</a>. The data set is in the same format as custom data exports generated via the <a href="https://www.superwasp.org/vespa/">superwasp.org</a> website. It consists of three files: <ul> <li>export.csv: The main data export in CSV format, containing one row per folded light curve (i.e. multiple rows per source object).</li> <li>fields.yaml: A YAML-format list of the columns included in the CSV export with an English description of each one.</li> <li>params.yaml: A YAML-format copy of the search and filtering parameters which were used to generate the export (in this case this is the full data set with no filtering applied). Also includes a data version number which will be incremented with future data releases or changes to the export format.</li> </ul> Photometry data is also available for download in FITS and JSON format, but this is not included here. URLs for the photometry files are included in export.csv for ease of downloading. Acknowledgements The SuperWASP project is currently funded and operated by Warwick University and Keele University, and was originally set up by Queen’s University Belfast, the Universities of Keele, St. Andrews and Leicester, the Open University, the Isaac Newton Group, the Instituto de Astrofisica de Canarias, the South African Astronomical Observatory and by STFC. The Zooniverse project on SuperWASP Variable Stars is led by Andrew Norton (The Open University) and builds on work he has done with his former postgraduate students Les Thomas, Stan Payne, Marcus Lohr, Paul Greer, and Heidi Thiemann, and current postgraduate student Adam McMaster. The Zooniverse project on SuperWASP Variable Stars was developed with the help of the ASTERICS Horizon2020 project. ASTERICS is supported by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement n.653477 VeSPA was designed and developed by Adam McMaster as part of his postgraduate work. This work is funded by STFC, DISCnet, and the Open University Space SRA. Server infrastructure was funded by the Open University Space SRA.

opencc-by-4.0Dec 2022View details →

A three-dimensional map of the Milky Way using 66,000 Mira variable stars

We provide here full Table 1 from Iwanek, P., et al., 2023, "A three-dimensional map of the Milky Way using 66,000 Mira variable stars", ApJS (accepted for publication, DOI: 10.3847/1538-4365/acad7a), which contains mean magnitudes, distances, extinction values, and photometric chemical types for 65,981 Galactic Miras (Iwanek2023_Table1_GalMirasDist.txt file). The corner plot, i.e., the two-dimensional projections of the multi-dimensional posterior parameter spaces fitted to the Galactic Miras distribution is presented in Figure Iwanek2023_corner_plot.png.   Patryk Iwanek is partially supported by Kartezjusz program No. POWR.03.02.00-00-I001/16-00, founded by the National Centre for Research and Development, Poland. Szymon Kozłowski acknowledges the support from the National Science Centre, Poland, via grant OPUS 2018/31/B/ST9/00334.  This publication makes use of data products from WISE, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration (NASA). This work is based in part on archival data obtained with the Spitzer Space Telescope, which was operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA.

opencc-by-4.0Oct 2023View details →

TESS Confirmed and First Identified SuperWASP Variable Stars

This catalog consists of the TESS-confirmed and First Identified SuperWASP Variable Stars of types $\delta$ Scuti, $\gamma$ Doradus, RR Lyrae, eclipsing binary systems with pulsating components, rotating variables, and others.  This dataset is part of a short summary submitted to RNAAS entitled "Identifying SuperWASP Detected Candidate Variables with TESS" (Zhou, A.-Y., 2023 Research Notes of the AAS, vol.7).

zenodo44/100

SuperWASP Variable Stars: Classifying Light Curves Using Citizen Science

Table of 301 previously unidentified SuperWASP stellar variables and related characteristics, not including rotators and unknown variables. The variable type has been decided by citizen scientists through the SuperWASP Variable Stars Zooniverse project. The types and periods of each object have been assessed by the authors to correct for mis-classifications; whilst they have been corrected as much as possible, some types periods remain best guesses. All periods have an uncertainty of 0.1%.

opencc-by-4.0Jan 2021View details →

zenodo44/100

Bright Southern Variable Stars in the bRing Survey

The corresponding data and plots for the 353 variables in the comprehensive survey of bright stars from the bRing telescopes. The paper has been accepted to the Astrophysical Journal Supplemental Series (July 27, 2019). An arXiv pre-print article is now available. If these data are to be used in future works, we ask that a short list of the bRing team be included as co-authors. Please contact Samuel Mellon (smellon@ur.rochester.edu) or Matthew Kenworthy (kenworthy@strw.leidenuniv.nl) for details. Paper Abstract: Besides monitoring the bright star β Pic during the near transit event for its giant exoplanet, the β Pictoris b Ring (bRing) observatories at Siding Springs Observatory, Australia and Sutherland, South Africa have monitored the brightnesses of bright stars (V ≃ 4--8 mag) centered on the south celestial pole (δ ≤ -30∘) for approximately two years. Here we present a comprehensive study of the bRing time series photometry for bright southern stars monitored between 2017 June and 2019 January. Of the 16762 stars monitored by bRing, 353 of them were found to be variable. Of the variable stars, 80% had previously known variability and 20% were new variables. Each of the new variables was classified, including 3 new eclipsing binaries (HD 77669, HD 142049, HD 155781), 26 δ Scutis, 4 slowly pulsating B stars, and others. This survey also reclassified four stars based on their period of pulsation, light curve, spectral classification, and color-magnitude information. The survey data were searched for new examples of transiting circumsecondary disk systems, but no candidates were found.

opencc-by-4.0Jul 2019View details →

zenodo44/100

Photometric detection of internal gravity waves in upper main-sequence stars. IV. Comparable stochastic low-frequency variability in SMC, LMC, and Galactic massive stars

Supporting data for peer-reviewed publication entitled: 'Photometric detection of internal gravity waves in upper main-sequence stars. IV. Comparable stochastic low-frequency variability in SMC, LMC, and Galactic massive stars', published in A&A. For the purpose of open access, the authors have applied a CC BY licence to the author accepted manuscript version and made it publicly available: <a href="https://arxiv.org/abs/2410.12726">https://arxiv.org/abs/2410.12726</a> Evolutionary models and stability window calculations courtesy of Jermyn et al. 2022 (DOI: <a href="https://iopscience.iop.org/article/10.3847/1538-4357/ac4e89">10.3847/1538-4357/ac4e89</a>) are publicly available via: <a href="https://github.com/adamjermyn/conv_trends">https://github.com/adamjermyn/conv_trends</a> TESS full-frame image data are publicly available from the Mikulski Archive for Space Telescopes (MAST) at the Space Telescope Science Institute (STScI): <a href="https://archive.stsci.edu/missions-and-data/tess">https://archive.stsci.edu/missions-and-data/tess</a> TESS light curves (provided in this repository) were extracted using the publicly available tglc (Han & Brandt 2023; DOI: <a href="https://iopscience.iop.org/article/10.3847/1538-3881/acaaa7">10.3847/1538-3881/acaaa7</a>) software package: <a href="https://github.com/TeHanHunter/TESS_Gaia_Light_Curve">https://github.com/TeHanHunter/TESS_Gaia_Light_Curve </a> SLF variability parameters (provided in this repository; cf. Tables 1 and 2 of the paper) were obtained using GP regression with the publicly available celerite2 (Foreman-Mackey et al. 2017; DOI: <a href="https://iopscience.iop.org/article/10.3847/1538-3881/aa9332">10.3847/1538-3881/aa9332</a>) software package: <a href="https://celerite2.readthedocs.io/en/latest/">https://celerite2.readthedocs.io/en/latest/</a>  and confidence intervals were obtained using the publicly available pymc3 (Salvatier et al. 2016; <a href="https://doi.org/10.7717/peerj-cs.55">https://doi.org/10.7717/peerj-cs.55</a>) software package: <a href="https://github.com/pymc-devs/pymc">https://github.com/pymc-devs/pymc</a> This research was supported in part by the National Science Foundation (NSF) under Grant Number NSF PHY-1748958; the Research Foundation Flanders (FWO) with grant agreement numbers 1286521N, 11F7120N, and V411621N; UK Research and Innovation (UKRI) in the form of a Frontier Research grant under the UK government's ERC Horizon Europe funding guarantee (SYMPHONY; grant number: EP/Y031059/1); a Royal Society University Research Fellowship (URF; grant number: URF\R1\231631); and the KU Leuven Research Council (grant number C16/18/005: PARADISE).

opencc-by-4.0Oct 2024View details →

opencc-by-4.0May 2020View details →

Variability of OB stars from TESS southern Sectors 1-13 and high-resolution IACOB and OWN spectroscopy

Typical MESA and GYRE inlists associated with <a href="https://arxiv.org/abs/2005.09658">Burssens et al. 2020</a>. MESA v. 12155, GYRE version v. 5.2. Context: Lack of high-precision long-term continuous photometric data for large samples of stars has prevented the large-scale exploration of pulsational variability in the OB star regime. As a result, the candidates for in-depth asteroseismic modelling remained limited to a few tens of dwarfs. The TESS nominal space mission has surveyed the southern sky, including parts of the galactic plane, yielding continuous data of at least 27 d for hundreds of OB stars. Aims: We aim to couple TESS data in the southern sky with ground-based spectroscopy to study the variability in two dimensions, mass and evolution. We focus mainly on the presence of coherent pulsation modes that may or may not be present in the predicted theoretical instability domains and unravel all frequency behaviour in the amplitude spectra of the TESS data. Methods: We compose a sample of 98 OB-type stars observed by TESS in Sectors 1-13 and with available multi-epoch, high-resolution spectroscopy gathered by the IACOB and OWN surveys. We present the short-cadence 2-min light curves of dozens of OB-type stars, that have one or more spectra in the IACOB or OWN database. Based on these light curves and their Lomb-Scargle periodograms we perform variability classification and frequency analysis. We place the stars in the spectroscopic Hertzsprung-Russell diagram to interpret the variability in an evolutionary context. Results: We deduce diverse origins of the mmag-level variability found in all of the 98 OB stars in the TESS data. We find among the sample several new variable stars, including three hybrid pulsators, three eclipsing binaries, high frequency modes in a Be star, and potential heat-driven pulsations in two Oe stars.  Conclusions: We identify stars for which future asteroseismic modelling is possible, provided mode identification is achieved. By comparing the position of the variables to theoretical instability strips we discuss the current shortcomings in non-adiabatic pulsation theory, and the distribution of pulsators in the upper Hertzsprung-Russell diagram.

opencc-by-4.0Dec 2023View details →

WACCM Test File for the Variable Star Phase Curve Package

This is a Whole Atmosphere Community Climate Model (WACCM) dataset that is used to test WACCM integration for the Variable Star Phase Curve (VSPEC) code.

opencc-by-4.0Feb 2022View details →

supplementary materials: Classifying Be star variability with TESS I: the southern ecliptic

The archived files contain ascii light curves (LC_data.tgz) and plots (LC_plots.tgz) from TESS cycle 1 for the Be star sample of "Classifying Be star variability with TESS I: the southern ecliptic". The light curve files have columns: 1) TESS JD (JD - 2457000), 2) relative flux, 3) photometric error.

opencc-by-4.0Nov 2022View details →

Cool, Luminous, and Highly Variable Stars in the Magellanic Clouds. II: Spectroscopic Data of Thorne-Zytkow Object and Super-AGB Star Candidates

This dataset contains Magellan MIKE spectroscopy of a population of cool, luminous stars in the Magellanic Clouds, a sample of confirmed Magellanic Cloud red supergiants, and spectrophotometric standard stars. The spectra were analyzed in the paper "Cool, Luminous, and Highly Variable Stars in the Magellanic Clouds. II: Spectroscopic and Environmental Analysis of Thorne-\.Zytkow Object and Super-AGB Star Candidates" by O'Grady et al. (2022). More details are provided in the README.

opencc-by-4.0Jul 2023View details →

Additional ASAS-SN 100 Million Variable Star Database Python Filter CSV files

Additional ASAS-SN 100 Million Variable Star Database Python Filter CSV files

opencc-by-4.0Nov 2021View details →

X-ray Variability of the Massive O star zeta Pup

Analysis of very deep, high resolution X-ray spectroscopy of the early O supergiant zeta Pup, acquired by Chandra in 2018-9, is presented. The cumulative spectrum has an exposure time of 820 kiloseconds (almost 10 days) and covers the wavelength range 3-20 Å. The X-ray broad-band light curve displays significant variability with one clear period, 1.78d, which has been previously detected in optical. The correlation with optical and UV data is discussed, notably in the context of CIRs and (possibly magnetic?) spots on the stellar surface with at least one stable period. The possible correlation of periods with optical and UV data is discussed. The X-ray spectrum is divided into several wavelength bands which are explored for variability. These divisions allow construction of light curves for hard, medium, and soft bands individually (which allows calculations of time-dependent hardness ratios), along with independently investigating the temporal behavior of strong X-ray emission lines. New constraints on the structure of stellar winds for the most massive stars are discussed.

opencc-by-4.0Jan 2022View details →

Far Ultraviolet Variable Stars in M31:

The AstroSAT/UVIT survey of M31 has observed the central part of M31 in FUV at different epochs, allowing a search for FUV variables. Here we report the detection of >100 variables (at >5-sigma confidence) and >1000 variables (at >3-sigma confidence). Counterparts are found for most of the >5-sigma variables. Most of the counterparts are young massive stars or stellar clusters. Results on the nature of the counterparts will be presented.

opencc-by-4.0Jul 2018View details →

Wide-field Infrared Survey Explorer (WISE) Catalog of Periodic Variable Stars

Wide-field Infrared Survey Explorer (WISE) Catalog of Periodic Variable Stars  Xiaodian Chen, Shu Wang, Licai Deng, Richard de Grijs and Ming Yang  We have compiled the first all-sky mid-infrared variable-star catalog based on Wide-field  Infrared Survey Explorer (WISE) five-year survey data. Requiring more than 100 detections  for a given object, 50,282 carefully and robustly selected periodic variables are discovered,  of which 34,769 (69%) are new. Most are located in the Galactic plane and near the equatorial  poles. A method to classify variables based on their mid-infrared light curves is established  using known variable types in the General Catalog of Variable Stars. Careful classification of  the new variables results in a tally of 21,427 new EW-type eclipsing binaries, 5654 EA-type   eclipsing binaries, 1312 Cepheids, and 1231 RR Lyraes. By comparison with known variables   available in the literature, we estimate that the misclassi- fication rate is 5% and 10% for  short- and long-period variables, respectively. A detailed comparison of the types, periods,   and amplitudes with variables in the Catalina catalog shows that the independently obtained   classifications parameters are in excellent agreement. This enlarged sample of variable   stars will not only be helpful to study Galactic structure and extinction properties,   they can also be used to constrain stellar evolution theory and as potential candidates for  the James Webb Space Telescope.   These supplementary materials contain ALLWISE and NEOWISE-R single-exposure photometry tables of variables list  in Table 2 and 6 of the paper, and light curve figures for the 50,282 periodic variables in Table 2.  SourceID is identifier join these attachments to Table 2 and 6. Example: For variable star WISEJ094812.4+093448 in Table 2, the SourceID=170 is adopted to search  corresponding single-exposure information in both 'allwise12.txt' and 'neowise12.txt'.   File Description: allwise12.txt                Single exposure photometry data of variables from ALLWISE.    Bytes Format Units   Label   Explanations -----------------------------------------------------------------------------------------     1- 8  I5     ---  SourceID   Internal source identifier             10- 20 F11.7  deg     RAdeg   Right Ascension in decimal degrees (J2000)                    22- 32 F11.7  deg     DEdeg   Declination in decimal degrees (J2000)    34- 47 F14.8  day      MJD    Modified Julian date of the mid-point of the observation        49- 54 F6.3   mag     W1mag   Single exposure WISE W1 (3.35 micron) band magnitude   56- 63 F6.3   mag    eW1mag   W1 band uncertainty   65- 77 F6.3   mag     W2mag   Single exposure WISE W2 (4.6 micron) band magnitude    79- 86 F6.3   mag    eW1mag   W2 band uncertainty -----------------------------------------------------------------------------------------      neowise12.txt                Single exposure photometry data of variables from NEOWISE-R.    Bytes Format Units   Label   Explanations -----------------------------------------------------------------------------------------    1- 8  I5     ---  SourceID   Internal source identifier             10- 21 F11.7  deg     RAdeg   Right Ascension in decimal degrees (J2000)                    23- 34 F11.7  deg     DEdeg   Declination in decimal degrees (J2000)    36- 44 F6.3   mag     W1mag   Single exposure WISE W1 (3.35 micron) band magnitude   46- 54 F6.3   mag    eW1mag   W1 band uncertainty   56- 64 F6.3   mag     W2mag   Single exposure WISE W2 (4.6 micron) band magnitude    66- 74 F6.3   mag    eW1mag   W2 band uncertainty   76- 90 F14.8  day      MJD    Modified Julian date of the mid-point of the observation -----------------------------------------------------------------------------------------   figure0.zip -- figure23.zip  Full figures of 50282 WISE variables. They are divided into 24  packages by the order of Right Ascension.

opencc-by-4.0Mar 2019View details →

The OmegaWhite Survey for Short-period Variable Stars. V. Discovery of an Ultracompact Hot Subdwarf Binary with a Compact Companion in a 44-minute Orbit

MESA inlists and run_star_extras associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017ApJ...851...28K">Kupfer et al. (2017)</a>. MESA version 9793. Publication DOI: <a href="https://doi.org/10.3847/1538-4357/aa9522">10.3847/1538-4357/aa9522</a>

opencc-by-4.0Nov 2024View details →

The variable evolution of accretor stars in binary systems due to accretion of increasingly helium-rich material

Dataset for paper "The variable evolution of accretor stars in binary systems due to accretion of increasingly helium-rich material". You will need the <a href="https://github.com/Krytic/Kaitiaki">Kaitiaki code</a>.

opencc-by-4.0Sep 2021View details →

Variable stellar outflows as a probe to magnetic fields and other physical characteristics of hot, massive stars

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.