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58 results for “Kepler”
A multi-resolution, multi-epoch low Radio Frequency Survey of the Kepler K2 Mission Campaign 1 Field
<p>Data abstract:</p> <p>Contained within are the MWA images used as input data for this study. The production and analysis of these images are described in the linked paper. The final catalogues and light curves are available from VizieR (http://vizier.cfa.harvard.edu/viz-bin/VizieR?-source=J/AJ/152/82).</p> <p>Paper abstract:</p> <p>We present the first dedicated radio continuum survey of a Kepler K2 mission field, Field 1, covering the North Galactic Cap. The survey is wide field, contemporaneous, multi-epoch, and multi-resolution in nature and was conducted at low radio frequencies between 140 and 200 MHz. The multi-epoch and ultra wide field (but relatively low resolution) part of the survey was provided by 15 nights of observation using the Murchison Widefield Array (MWA) over a period of approximately a month, contemporaneous with K2 observations of the field. The multi-resolution aspect of the survey was provided by the low resolution (4‧) MWA imaging, complemented by non-contemporaneous but much higher resolution (20″) observations using the Giant Metrewave Radio Telescope (GMRT). The survey is, therefore, sensitive to the details of radio structures across a wide range of angular scales. Consistent with other recent low radio frequency surveys, no significant radio transients or variables were detected in the survey. The resulting source catalogs consist of 1085 and 1468 detections in the two MWA observation bands (centered at 154 and 185 MHz, respectively) and 7445 detections in the GMRT observation band (centered at 148 MHz), over 314 square degrees. The survey is presented as a significant resource for multi-wavelength investigations of the more than 21,000 target objects in the K2 field. We briefly examine our survey data against K2 target lists for dwarf star types (stellar types M and L) that have been known to produce radio flares.</p>
A join of the Huber et al. (2014) catalog of stellar parameters and the Kepler Input Catalog
<p>This a join of the <a href="http://arxiv.org/abs/1312.0662">Huber et al. (2014)</a> and the <a href="http://arxiv.org/abs/1102.0342">Kepler Input Catalog</a></p>
Kepler PRF Models
<p>This repository contains Point Response Function (PRF) models empirically computed from Kepler's Full Frame Images. Each Kepler's CCD and observation quarter has its own PRF model stored in a single FITS file that contains information of the original data in the header and weight values in a BinaryTable. </p> <p>The PRF model where computing using the procedure described in the Linearized Field Deblending photometric method <a href="https://ui.adsabs.harvard.edu/abs/2021AJ....162..107H/abstract">(Hedges et al. 2021)</a>. This method uses basis splines in polar coordinates to model the PRF profile by solving a linear problem.</p> <p>The PRF models were created using the <a href="https://github.com/SSDataLab/psfmachine"><strong>psfmachine</strong></a> python library and are meant to be used with the same package. Each FITS file contains the parameters to build design matrices and the "weights" that solve the linear problem, both are used to evaluate the PRF in a coordinate grid and perform PSF-photometry. See the package documentation for examples on how to use these files.</p>
A join of the Kepler DR24 injections table with the robovetter table
<p>A join of the injection and robovetter results for Kepler DR24. The references for these data are:</p> <ul> <li>Christiansen et al. (2016): http://adsabs.harvard.edu/abs/2016ApJ...828...99C</li> <li>Coughlin et al. (2016): http://adsabs.harvard.edu/abs/2016ApJS..224...12C</li> <li>Mullally et al. (2016): http://adsabs.harvard.edu/abs/2016PASP..128g4502M</li> </ul>
Planetary perturbers: Flaring star-planet interactions in Kepler and TESS
<p>This data set contains:</p> <p>a. almost 13,000 de-trended Kepler and TESS light curves used in the publication with the same title (Ilin et al. 2024). Each light curve is a fits file with the Kepler or TESS identifier, Quarter or Sector, and, if there are multiuple light curves per Quarter/Sector, the number of the light curve. The light curves can be read with any fits file handler (e.g., astropy), or with the lightkurve package. Each light curve contains arrays for the flux, detrended flux, time, and orbital phase of the innermost planet. Note that for transiting planets the orbital phase is set to zero around transit midtime, while for non-transiting planets, the phase zero is set arbitrarily. There is no particular reason for splitting the data in the zip files except for easier upload.</p> <p>b. Tables 1-4 from Ilin et al. (2024). Tables 1 and 3 are combined into one. Each table includes a description of its columns at the top.</p> <p><a href="https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.3395I/abstract"><strong>Ilin et al. (2024)</strong></a> Ilin, E., Poppenhäger, K., Chebly, J., Ilić, N., Alvarado-Gómez, J.~D.</p> <p>Planetary perturbers: flaring star-planet interactions in Kepler and TESS.</p> <p>Monthly Notices of the Royal Astronomical Society 527, 3395–3417.</p> <p>doi:10.1093/mnras/stad3398</p>
Text corpus of Kepler's Astronomia nova
<p>The JSON file contains preprocessed paragraphs of Kepler’s Astronomia Nova for machine learning. The database is derived from Donahue’s translation: Kepler, Johannes, New Astronomy, rev. edition, tr. by William H. Donahue, Green Lion Press, 2015. The text was digitized using OCR and automated text processing aiming at “pure” text containing machine-readable sentences in UTF8. Special characters, reference marks, and other markings were removed. OCR artefacts and errors may remain. For the authoritative text see Donahue’s edition. Digital Latin version cf. Kepler’s Gesammelte Werke.</p>
LAMOST–Gaia–Kepler Stellar Kinematic catalog
<p>In the second part of the Planets Across the Space and Time (PAST) series, by combining the data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR4 and Gaia DR2 and then applying the revised kinematic methods from PAST I, we present a catalog of kinematic properties (i.e., Galactic positions, velocities, and the relative membership probabilities among the thin disk, thick disk, Hercules stream, and the halo) as well as other basic stellar parameters for 35,835 Kepler stars.</p> <p>The new version combing LAMOST DR8 and Gaia eDR3 will be released soon.</p>
Kepler-200 b
<p>The file contains the parameters of the exoplanet given in Title as referenced on the exoplanet.eu database.</p>
APOGEE-Kepler Catalog SDSS Internal Version
<p>This represents the publication of the SDSS internal version of the APOGEE-Kepler Catalog (v.7.4.0, August 2024), previous versions of which have been available to SDSS-IV collaboration members on the internal wiki page https://trac.sdss.org/wiki/APOGEE2/APOKASC/Catalog and have been used for a variety of projects. It has been designed to include all stars in the Kepler field which had APOGEE spectra at the end of SDSS-IV (DR17) and as such is not limited to giants or seismic oscillators. For giant oscillators, this catalog contains a subset of the information available in all of the tables available with the journal edition of the APOKASC-3 catalog (Pinsonneault et al., 2024), as well as some additional information including matches to external datasets that may be of interest. This table also contains some historical information, previous versions of some values, and so forth that were used for comparison and validation. The header_APOKASC_cat_v7.4.0.txt file contains a list of the available columns as well as some descriptions of where the values are from. These values represent effort from a variety of people including those involved in the APOKASC collaboration as well as related individual efforts and anyone using this data is strongly encouraged to cite the original published version. In all cases where the values in this file and the values in the journal disagree, the journal values should be viewed as the correct version of record. The fits and ascii versions of the APOKASC catalog are the same, and both are provided for ease of use. </p>
Fig. 1 in Occurrence of Metarhizium rileyi (Farlow) Kepler, S. A. Rehner & Humber in Anticarsia gemmatalis Hübner (Lepidoptera: Erebidae) and Trichoplusia ni Hübner (Lepidoptera: Noctuidae) larvae in Tamaulipas and Veracruz, Mexico
Fig. 1. Larvae of (A) Anticarsia gemmatalis and (B) Trichoplusia ni infected by Metarhizium rileyi, collected from soybean plants in the states of Tamaulipas and Veracruz, Mexico; (C) Conidiophores of M. rileyi at 100× magnification and dyed with cotton blue; (D) Spores of M. rileyi at 100× magnification and dyed with cotton blue.
A Unified Treatment of Kepler Occurrence to Trace Planet Evolution: Supplemental Data
<p>Here we present supplementary data underlying the paper "A Unified Treatment of Kepler Occurrence to Trace Planet Evolution I: Methodology." Included are:</p> <ul> <li>Planet catalogs; filenames "dr25_X_PCs_B20_ruwe.csv"</li> <li>Completeness contours; filenames "out0819_X_slog_insol__.fits.gz"</li> <li>Observed planet KDEs; filenames "out0827_X_sboot_1000__avg.npy"</li> </ul>
Gyro-kinematic ages for Kepler stars
<p>Gyro-kinematic agse for Keplers stars with measured rotaiton periods (<a href="https://zenodo.org/api/files/d7f16f8f-ad9b-46cb-a098-c1dea37725b7/Gyrokinage2020_Prot.csv">Gyrokinage2020_Prot.csv</a>) and all other dwarf stars (<a href="https://zenodo.org/api/files/d7f16f8f-ad9b-46cb-a098-c1dea37725b7/Gyrokinage2020_All.csv">Gyrokinage2020_All.csv</a>)</p>
Following up the Kepler field: Masses of Targets for transit timing and atmospheric characterization
<p>These are posterior samples from TTV models presented in "Following up the Kepler field: Masses of Targets for transit timing and atmospheric characterization" by D. Jontof-Hutter, D., A. Wolfgang A., E. B. Ford, J. J. Liassauer, D. C. Fabrycky and J. F. Rowe.</p>
Quasi-periodic Gaussian process rotation period posterior samples of Kepler light curves.
<p>.h5 files containing light curves, hyperparameter priors, period priors and posterior samples for the QP-GP rotation period model in Angus, Morton, Aigrain, Foreman-Mackey & Rajpaul (2017). </p> <p>koi_results_02_15.tgz contains posterior samples for 1132 Kepler objects of interest.</p> <p>results_acfprior_02_16.tgz contains posterior samples for 998 simulated light curves (previously published in Aigrain et al., 2015: https://arxiv.org/abs/1504.04029) with an ACF-based prior.</p> <p>results_noprior_02_16.tgz contains posterior samples for 997 simulated light curves (previously published in Aigrain et al., 2015) with an uninformative prior.</p> <p>To load the samples in python:</p> <p>>>> df = pd.read_hdf("<filename>", key="samples")</p> <p>>>> ln_period_samples = df.ln_period</p> <p>>>> ln_A_samples = df.ln_A</p> <p>>>> ln_l_samples = df.ln_l</p> <p>>>> ln_G_samples = df.ln_G</p> <p>>>> ln_sigma_samples = df.ln_sigma</p> <p> </p>
Quasi-periodic Gaussian process rotation period posterior samples (with an uninformative prior) for 998 simulated Kepler light curves.
<p>997.h5 files containing light curves, hyperparameter priors, period priors and posterior samples for the QP-GP rotation period model in Angus, Morton, Aigrain, Foreman-Mackey & Rajpaul (2017).</p> <p>997 .png light curve images.</p> <p>To load the samples in python:</p> <p>>>> df = pd.read_hdf("1.h5", key="samples")</p> <p>>>> ln_period_samples = df.ln_period</p> <p>>>> ln_A_samples = df.ln_A</p> <p>>>> ln_l_samples = df.ln_l</p> <p>>>> ln_G_samples = df.ln_G</p> <p>>>> ln_sigma_samples = df.ln_sigma</p> <p> </p>
Quasi-periodic Gaussian process rotation period posterior samples (with an ACF prior) for 998 simulated Kepler light curves.
<p>998.h5 files containing light curves, hyperparameter priors, period priors and posterior samples for the QP-GP rotation period model in Angus, Morton, Aigrain, Foreman-Mackey & Rajpaul (2017).</p> <p>998 .png light curve images.</p> <p>To load the samples in python:</p> <p>>>> df = pd.read_hdf("1.h5", key="samples")</p> <p>>>> ln_period_samples = df.ln_period</p> <p>>>> ln_A_samples = df.ln_A</p> <p>>>> ln_l_samples = df.ln_l</p> <p>>>> ln_G_samples = df.ln_G</p> <p>>>> ln_sigma_samples = df.ln_sigma</p>
Statue #2 outside Kepler Oberschule, Berlin
Second statue from row of statues outside the Kepler Oberschule, near Köllnische Heide, Berlin. Small girl saves boy from Lobster? Attributed to "A. Wellmann". Source: Objaverse 1.0 / Sketchfab
Accurate and Robust Stellar Rotation Periods catalog for 82771 Kepler stars using deep learning
<p>This repository is for the paper "Rotation Period for 83022 Kepler Stars: A Deep Learning Approach" by I. Kamai and H. B. Perets. It is associated with manuscript number AAS56501. It consists a frozen repository and the published catalog</p>
Population Models of Rotating Field Stars in Kepler
<p>Model populations are constructed using TRILEGAL galaxy models coupled to YREC stellar evolutionary models and a magnetic braking law, and are described in van Saders, Pinsonneault, & Barbieri, "Forward Modeling of the Kepler Stellar Rotation Period Distribution: Interpreting Periods from Mixed and Biased Stellar Populations," 2019, ApJ, 872, 128 and updated in Hall et al. 2021 (Nature Astronomy, 5, 707) to incorporate the Berger et al. 2020 (AJ, 159, 280) Kepler Stellar Properties Catalog. </p> <p>Two model populations are provided: one in which rotation is modeled with a "standard" magnetic braking law of the form in van Saders et al. 2013, and a second in which stars are subject to weakened magnetic braking past a critical Rossby number, Rocrit. </p> <p>Models can be unpacked with the hdf with pandas functionality, using key='sample'. The keys should be self-explanatory with the possible exception of "evo", which is the evolutionary state. Choose evo = 1 to select only the main sequence.</p> <p>If you use these models in your work, please cite van Saders et al. 2019, with an additional citation to Hall et al. 2021 appreciated. </p> <p> </p>
Statue #1 outside Kepler Oberschule, Berlin
Statue of two children wrestling with a ram, outside of the Kepler Oberschule near Köllnische Heide, Berlin. Attributed to "A. Wellmann". Source: Objaverse 1.0 / Sketchfab
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