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33 results for “hubble”
Hubble and Spitzer data around a z=7.2 quasar in the GOODS-North Field
<p>This dataset provides 10-arcminute HST and Spitzer mosaics of the GOODS-North survey field, centered on the z=11.1 galaxy GNz11 (<a href="https://ui.adsabs.harvard.edu/abs/2016ApJ...819..129O/abstract">Oesch et al. 2016</a>) and including a z=7.2 quasar (Fujimoto et al., in prep). Complete mosaics are available at https://s3.amazonaws.com/grizli-v1/Mosaics/index.html.</p> <p>The mosaics were produced with the <a href="https://github.com/gbrammer/grizli">grizli</a> (HST) and <a href="https://github.com/gbrammer/golfir">golfir</a> (Spitzer) software modules.</p> <p>Also included are the 2D extracted grism spectra (gnz7qso_16155.beams.fits) that can be analyzed with grizli.</p> <p><strong>Table 1:</strong> HST exposure summary</p> <pre><strong>Filter N t(ks) Proposal ID</strong> f435w 6 7.2 9583 f606w 23 9.3 9583,10339,12443,13779 f775w 35 19.1 9583,9727,9728,10339,11600 f814w 42 23.8 12442,12443,12444,12445,13420 f850lp 82 36.9 9583,9727,9728,10189,10339,12444,13063 f105w 6 3.3 12442,13420 f125w 8 4.4 12443,12444,12445 f140w 6 1.2 11600 f160w 8 5.4 12443,12444,12445 g102 4 5.0 13420 g141 8 8.6 11600 </pre>
The data for "Reconnaissance with JWST of the J-region Asymptotic Giant Branch in Distance Ladder Galaxies: From Irregular Luminosity Functions to Approximation of the Hubble Constant"
<p>Data used for "Reconnaissance with JWST of the J-region Asymptotic Giant Branch in Distance Ladder Galaxies: From Irregular Luminosity Functions to Approximation of the Hubble Constant" by Siyang Li, Adam G. Riess, Stefano Casertano, Gagandeep S. Anand, Daniel M. Scolnic, Wenlong Yuan, Louise Breuval, and Caroline D. Huang. Magnitudes provided are after correcting for foreground extinction and crowding bias.</p>
Hubble and Webb Space Telescope data for the cluster field RXJ-2129
<p>This repository contains reduced image mosaics from the Hubble and Webb Space Telescopes of the galaxy cluster RXJ-2129.</p> <p>Data were processed with the <a href="https://github.com/gbrammer/grizli">grizli</a> software pipeline, as described by <a href="https://arxiv.org/abs/2302.10936">Valentino et al. (2023, ApJ, in press)</a>, with the software and observatory calibrations available as of October 2022.</p> <p>For a given broad-band filter, the science data are given in the "sci.fits" files. Inverse variance weight images are provided in the "wht.fits" files. </p> <p>Aperture photometry following the methodology described by Valentino et al. is provided in "rxj2129-grizli-v4.0-fix_phot_apcorr.fits", and photometric redshift estimates derived with the <a href="https://github.com/gbrammer/eazy-py/">eazy-py </a>software are tabulated in "rxj2129-grizli-v4.0-fix.zout.fits".</p>
Tables for: The Panchromatic Hubble Andromeda Treasury XXI. The Legacy Resolved Stellar Photometry Catalog
<p>This deposit contains the full machine-readable tables for the accepted version of the manuscript, "<em>The Panchromatic Hubble Andromeda Treasury XXI. The Legacy Resolved Stellar Photometry Catalog</em>", submitted and accepted to the Astrophysical Journal Supplments. </p> <p>The specific files included in this deposit are the full version of Tables 1-3 in this manuscript:</p> <ul> <li>Table 1: Simplified table of PHAT photometry for easy use;</li> <li>Table 2: Simplified table of artificial star test results for easy use;</li> <li>Table 3: Summary of artificial star statistics as a function of brightness and stellar density.</li> </ul> <p>The *.txt files are formatted according to the machine-readable standards adopted by the AAS Journals and CDS/Vizier. Documentation of this format can be found at these links:</p> <ul> <li><a href="https://journals.aas.org/mrt-overview/">AAS Journals MRT overview</a></li> <li><a href="http://vizier.u-strasbg.fr/doc/catstd.htx">CDS/Vizier standards</a></li> </ul> <p>These files can be read in python using the astropy package or with the most recent version of <a href="https://www.star.bris.ac.uk/~mbt/topcat/">TOPCAT</a> (> Version 4.8). An example script for reading these files in astropy is given here:</p> <pre><code class="language-python"> from astropy.table import Table data = Table.read("datafile3.txt", format="ascii.cds") </code></pre> <p>In addition, a headerless, compressed TeX (&-delimited; "full_table.tex.xz") version of Table 1, and a header-only, dataless version of Table 1 ("datafile1_headeronly.txt") are provided to give users additional tools for dealing with this large dataset. </p> <p>The compression routine was applied using xz <https://tukaani.org/xz/> with the encodings</p> <ul> <li> <p><code>xz -z -7 -T 0 full_table.tex</code></p> </li> <li> <p><code>xz -z -9 -T 0 datafile1.txt</code></p> </li> </ul> <p>The Table 1 files on Zenodo were then split into smaller chunks to upload them to Zenodo using the GNU <a href="https://www.gnu.org/software/coreutils/manual/html_node/split-invocation.html"><code>split</code></a> routine. The full files can be recovered by recombining them before decompressing them. The list of related commands and the expected md5 hexidecimal checksums are given here:</p> <ul> <li> <p><code>split --bytes=512M ../full_table.tex.xz full_table.tex.xz.</code></p> </li> <li> <p><code>split --bytes=512M ../datafile1.txt.xz datafile1.txt.xz.</code></p> </li> <li> <p><code>cat full_table.tex.xz.a* > full_table.tex.xz</code></p> </li> <li> <p><code>cat datafile1.txt.xz.a* > datafile1.txt.xz</code></p> </li> <li> <p><code>MD5 (full_table.tex.xz) = 7f9195210bec61c08d04926ada4a021a</code></p> </li> <li> <p><code>MD5 (datafile1.txt.xz) = 63205fe1051e97f4e04380dd23469893</code></p> </li> </ul> <p>Finally, those interested in generating their own cuts from the DOLPHOT quality parameters can access the full photometry tables, available at MAST as a High Level Science Product via <a href="https://doi.org/10.17909/T91S30">doi.org/10.17909/T91S30</a></p>
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains
<p>We publish the training/validation/test datasets, trained model weights, configuration files, Bayesian neural network samples, and MCMC chains used to produce the figures in the LSST DESC paper, "Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant." They are formatted to be used with the DESC package "H0rton" (<a href="https://github.com/jiwoncpark/h0rton">https://github.com/jiwoncpark/h0rton</a>). Additional descriptions can be found in the README. Please contact Ji Won Park (@jiwoncpark) on GitHub or <a href="https://github.com/jiwoncpark/h0rton/issues">make an issue</a> for any questions.</p>
Hubble eXtreme Deep Field that has been clipped and processed for ML applications
<p>This is a set of FITS files downloaded from https://archive.stsci.edu/ .</p> <p> </p> <p>The *.npy file has been clipped to the 99.99th percentile and then minmax normalised along each channel.</p>
Extended Files for "Lessons from Hubble & Spitzer: 1D Self-Consistent Model Grids for 19 Hot Jupiter Emission Spectra"
<p>This directory includes extended files for Wiser et al. 2024, "Lessons from Hubble & Spitzer: 1D Self-Consistent Model Grids for 19 Hot Jupiter Emission Spectra." </p> <p>Files:</p> <ul> <li><strong>Extended Planet Figures:</strong> For each of the 20 planets discussed in the manuscript, <em>[PlanetName].pdf </em>includes figures showing the secondary eclipse spectra and parameter estimations for each model scenario. A file for Kepler-13Ab illustrates our grid models' inability to explain the WFC3 and Spitzer observations simultaneously. </li> <li><strong>Internal Temperature Tests:</strong><em> InternalTemperatureTests.pdf</em> includes figures illustrating our inability to constrain an atmosphere's internal temperature with these model grids and the WFC3 and Spitzer observations.</li> <li><strong>Parameter Estimates .csv Tables:</strong> <ul> <li>Both .csv files include planet and star parameters (temperatures, radii, mass, logg, semimajor axis) and parameter ranges for each planet grid. They also include parameter estimations for each model scenario. Listed are the medians of each parameter's posterior probability distribution and pos/neg values encompassing the one-sigma confidence region. This information is shown visually in the extended planet figures. </li> <li><em>fiducial_stats.csv</em> includes parameter estimations for the fiducial model scenario. For planets with multiple solutions (as described in Wiser et al. 2024), multiple rows detail each solution. There is also a "limit" flag for parameters with an upper limit, lower limit, or unconstrained (UL, LL, or UC, respectively).</li> <li><em>nonfiducial_stats.csv </em>includes parameter estimates for all other model scenarios. This table does not account for multiple solutions or "limit" flags. </li> </ul> </li> <li>For complete model grids, please contact the authors. </li> </ul>
Hubble's Constant with GW170817 Standard Siren and GW190814 Dark Siren
<p>The local universe expansion rate is one of the most fundamental and essential cosmological parameters. This value which is known by the name of Hubble’s Constant is scientifically measured by electromagnetic sources called distance ladder. Surprisingly, using Gravitational Wave (GW) analysis this value can be measured making GW sources another significant method to act as standard sirens with their electromagnetic counterparts from their host galaxy. The gravitational wave event GW 170817 was the outcome of the merger of two different neutron stars. The electromagnetic event was recorded from the host galaxy NGC4993. The GW170817 has been a considerable success in this direction measuring the value of universe acceleration H0 = 70.0+12.0 −8.0 kms−1 Mpc−1. Another event in this series GW190817 is Compact Binary Coalescence involving a 22.2 – 24.3 The EM counterpart of this event is unknown so far and hence the event is named Dark Siren.The Hubble’s value proposed with this even is close to H0 = 75+59 −13 km s−1Mpc−1 .The source GW190814 which involves a massive black hole and the other compact object as the lightest black hole or the heaviest neutron star was localized to 18.5 deg2 at a distance of Mpc.</p>
The Impact of Satellite Trails on Hubble Space Telescope Observations: satellite classifications
<p>This repository contains the Hubble Space Telescope (HST) observations with satellite classifications, released in the paper "<a href="https://www.nature.com/articles/s41550-023-01903-3"><em>The Impact of Satellite Trails on Hubble Space Telescope Observations</em></a>" (DOI: 10.1038/s41550-023-01903-3<em>).</em></p> <p>This table contains 114 607 individual HST images taken in the last 19 years and publicly released in the <a href="https://hst.esac.esa.int/">eHST</a> archive by 3 October 2021, with satellite trail classifications made with machine learning and citizen science.</p> <p>We processed the individual images by adding the two ACS/WFC (WFC3/UVIS, respectively) apertures side-by-side, without correcting for geometric distortions and without the gap between the two detectors (hence why the satellite trails can appear discontinuous in the images). Note that these are not original images from the eHST archive, and therefore are not meant for other scientific analysis. The dataset contains 3072 HST images with satellites (2.7% of the dataset) and 3228 satellite trails in total. The classifications were visually inspected and vetted by the authors (images are flagged with the 'satellite' flag). </p> <p>The table contains the following columns:</p> <ul> <li>observation IDs: both individual exposures (simple_id) and composite images, multiple individual exposures processed and stacked (composite_id);</li> <li>instrument: ACS/WFC or WFC3/UVIS;</li> <li>start time and end time of exposure;</li> <li>exposure duration; </li> <li>right ascension (ra) and declination (dec);</li> <li>'satellite' flag [empty otherwise];</li> <li>no_sat: number of satellites in the image;</li> <li>image URL - URL for the individual HST observations used for satellite classification;</li> <li>additional metadata columns, as available in the <a href="https://hst.esac.esa.int/">eHST</a> archive.</li> </ul> <p>The satellites were classified by volunteers on the <a href="http://www.asteroidhunter.org">Hubble Asteroid Hunter</a> citizen science project and with a machine learning classifier. Please cite the paper (<a href="https://www.nature.com/articles/s41550-023-01903-3">Kruk et al.</a>, <a href="https://www.nature.com/articles/s41550-023-01903-3">https://www.nature.com/articles/s41550-023-01903-3</a>) when using the data in this repository.</p>
Hubble and Spitzer imaging data around the z=7.54 quasar J1342+09
<p>This repository provides Hubble and Spitzer imaging data around the z=7.54 quasar J1342+09, nicknamed "Pisco".</p> <p>Data reduction and model photometry with the <a href="https://github.com/gbrammer/grizli">grizli</a> and <a href="https://github.com/gbrammer/golfir">golfir</a> software is performed as described by <a href="https://ui.adsabs.harvard.edu/abs/2022ApJS..263...38K">Kokorev et al. (2022).</a></p>
Hubble COS NUV Dataset
<p>COS NUV spectrum, GD71 (Star).</p>
Hubble COS FUV Dataset
<p>COS FUV spectrum of NGC 5548; configurations G130M/1291,1327.</p>
Hubble Frontier Field Clusters and their Parallel Fields: Photometric and Photometric Redshift Catalogs
<p>Source catalogs of the Hubble Frontier Field clusters and parallel fields. If used, please cite https://ui.adsabs.harvard.edu/abs/2021arXiv210301952P/abstract</p>
Strong lensing mass models for the paper "Model-Independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS \\ Based on Self-Consistent Strong Lensing Data"
<p><strong>Codes for evaluating multiple image scatters</strong></p> <p>The code "eval_source_scatter.py" generates the source plane scatters for multiple images.</p> <p>In the folder "Image_plane_scatters", there are codes for computing image plane scatters.<br> "lens_rms.py": to find the location of the multiple images in the image plane.<br> "plot_result.py": to plot the result rms scatters.<br> We uploaded our results and code for computing scatters in both the source and the image planes.</p> <p> </p> <p><strong>Results from the MARS algorithm</strong></p> <p>In each folder, there are 'result_fits.fits', 'resut_kappa_w_header.fits', 'deflection_angle_w_header.fits', and 'catalog.txt' files.<br> All kappa and deflection angle maps are scaled to Dds/Ds= 1.</p> <p>"result_fits.fits" contains all parameters produced by MARS and has a size of (140x140 + alpha), where alpha is the number of model redshifts.<br> "result_kappa_w_header.fits" is the 100x100 convergence map.<br> "deflection_angle_w_header.fits" is the 100x100 deflection angle map in the unit of arc second.<br> "catalog.txt" is the multiple image catalog. The positions are given in pixel unit.</p> <p>For more details, readers are referfed to arXiv:2301.08765. Also, feel free to contact us (<a href="mailto:sang6199@yonsei.ac.kr">sang6199@yonsei.ac.kr</a>) if you have any questions.</p> <ul> <li>We found errors in WCS for the fits files and re-uploaded corrected files on 2023-01-27. We thank Jori Liesenborgs for pointing this out.</li> <li>We updated files on 2023-04-06.</li> </ul>
The R136 star cluster dissected with Hubble Space Telescope/STIS. III. The most massive stars and their clumped winds
<p>Supplemental material to 'The R136 star cluster dissected with Hubble Space Telescope/STIS. III. The most massive stars and their clumped winds'. This includes, for each star in the sample: a plot of the observed spectrum overlaid with best fitting models and fitness diagrams for all free parameters. Furthermore we include data (the normalised spectra used in the analysis, and best fitting models) and a basic reproduction package. </p>
Hubble STIS FUV Dataset
<p>STIS FUV/MAMA spectrum, GD71 (Star).</p>
Hubble STIS NUV Dataset
<p>STIS NUV/MAMA spectrum, GD71 (Star).</p>
Hubble STIS CCD Dataset
<p>STIS optical spectrum, GD71 (Star).</p>
Data for: Harnessing the Hubble Space Telescope Archives: A Catalogue of 21,926 Interacting Galaxies
<p>This repository contains the data released in the paper "Harnessing the Hubble Space Telescope Archives: A Catalogue of 21,926 Interacting Galaxies"<em> </em>(DOI: <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...948...40O/abstract">10.3847/1538-4357/acc0ff</a>).</p> <p>We release the catalogue of interacting galaxies found in this work, as well as any objects of interest found during the visual inspection stage of de-contamination. Each catalogue contains the SourceID, Right Ascension, Declination and the "Status" of each object. The status shows whether an object has appeared in the astrophysical literature prior to this work. <strong>Each catalogue is contained in a .csv file</strong>.</p> <p>The exception to this is the interacting galaxy catalogue itself, which also contains the Zoobot prediction of each source to be an interacting galaxy.</p> <p>We also include the images that correspond to each catalogue. <strong>These are contained within the .tar.gz files in the repository.</strong> Each .tar.gz filename corresponds to the catalogue .csv filename. The individual filenames are the SourceIDs of the corresponding objects.</p> <p>Please note: These images have been saved as 150x150 gray images using only the F814W filter of the <em>HST</em>. Different dimension images/multi-band photometry will have to be found by the user. When input into our Zoobot model, these had been resized to 300x300.</p> <p>Please also note: <strong>Each sub-category of object has</strong> <strong>only been classified visually</strong>.</p> <p>A list of the catalogue definitions is below:</p> <ol> <li>agn-catalogue - Catalogue of sources containing an Active Galactic Nuclei or a Quasar.</li> <li>groups-catalogue - Catalogue of sources containing a Galaxy Group.</li> <li>high_z-catalogue - Catalogue of sources containing high redshift galaxies.</li> <li>interacting-catalogue - Catalogue of sources predicted to be interacting galaxies. This is the main catalogue.</li> <li>jellyfish-catalogue - Catalogue of sources containing a Jellyfish galaxy.</li> <li>jets-catalogue - Catalogue of sources containing a galaxy with a jet.</li> <li>lenses-catalogue - Catalogue of sources containing a gravitational lense.</li> <li>ly-catalogue - Catalogue of sources which are Lyman-Alpha galaxies.</li> <li>overlap-catalogue - Catalogue of sources which contain two galaxies which overlap by projection, but are not interacting.</li> <li>planetary-catalogue - Catalogue of sources which contain edge on planetary disks.</li> <li>radio-catalogue - Catalogue of sources which contain a radio source/jet.</li> <li>ring-catalogue - Catalogue of sources which contain ring galaxies.</li> <li>submillimetre-dusty-catalogue - Catalogue of sources which contain submillimetre or dusty galaxies.</li> <li>supernova-catalogue - Catalogue of sources which contain a supernova remnant.</li> <li>unknown-catalogue - Catalogue of sources which could not be classified visually.</li> <li>ysc-catalogue - Catalogue of sources which contain a Young Stellar Cluster.</li> <li>yso-catalogue - Catalogue of sources which contain a Young Stellar Object.</li> </ol>
Multi-messenger constraints on the neutron-star equation of state and the Hubble constant -- Data and Codes
<p>This repository contains the data and the codes used to produce the results presented in the article: "Multi-messenger constraints on the neutron-star equation of state and the Hubble constant " by Dietrich et al., arXiv:2002.11355 . </p> <p>The uploaded software packages are snapshots of actively developed code. We refer to the original repositories:</p> <p>https://git.ligo.org/lscsoft/bilby<br> https://git.ligo.org/lscsoft/parallel_bilby/ <br> https://github.com/mcoughlin/gwemlightcurves<br> https://git.ligo.org/lscsoft<br> <br> and to the original works for further details. In addition, we ask people to cite the original articles mentioned on the code repositories if some of the software packages are used.</p> <p><br> license: GNU General Public License agreement. </p>
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