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2,555 results for “catalogs”
Catalog of 1600+ New Variables around V1821 Cyg in NGC 6871
<p>Utilizing TESS data, the author has screened a small sky region of a one-degree radius centered on the known $\delta$ Scuti star V1821 Cyg within the young open cluster NGC 6871. The selected samples had TESS magnitude values ranging from 6 to 16 mag, matching the TESS premium targets exhibiting good quality photometry and effective temperature between 10000 and 6000 K, roughly corresponding to main sequence stars of spectral types A to F. Among the 3600 candidate stars surveyed, 1530 were discovered to be new variables of types $\delta$ Scuti, $\gamma$ Doradus, Maia, eclipsing binary, rotational, and solar-like oscillators.</p>
Data for The UNCOVER Survey: A First-Look HST+JWST Catalog of Galaxy Redshifts and Stellar Populations Properties Spanning 0.2 ≲ z ≲ 15
<p>The recent UNCOVER survey with the James Webb Space Telescope (JWST) exploits the nearby cluster Abell 2744 to create the deepest view of our universe to date by leveraging strong gravitational lensing. In this work, we perform photometric fitting of more than 50,000 robustly detected sources out to z ~ 15. We show the redshift evolution of stellar ages, star formation rates, and rest-frame colors across the full range of 0.2 < z < 15. The galaxy properties are inferred using the Prospector Bayesian inference framework using informative Prospector-beta priors on masses and star formation histories to produce joint redshift and stellar populations posteriors, and additionally lensing magnification is performed on-the-fly to ensure consistency with the scale-dependent priors. We show that this approach produces excellent photometric redshifts with NMAD ~ 0.03, of a similar quality to the established photometric redshift code EAzY. In line with the open-source scientific objective of the Treasury survey, we publicly release the stellar populations catalog with this paper, derived from the photometric catalog adapting aperture sizes based on source profiles. This release includes posterior moments, maximum-likelihood spectra, star-formation histories, and full posterior distributions, offering a rich data set to explore the processes governing galaxy formation and evolution over a parameter space now accessible by JWST.</p>
Catalog of NE Italy earthquakes Mw with related velocimetric time series
<p>Mw catalog (xlsx format) of earthquakes occurred in Norheastern Italy from 2016 to 2023; the catalog reports estimations for:</p> <ul> <li>ML (Bragato and Tento, 2005);</li> <li>Mw calculated from SA (Moratto et al., 2017);</li> <li>Mw calculated from MT (Moment Tensor; Saraò et al., 2021);</li> <li>The tgz file with the corrected velocimetric waveforms (SAC fomat with P and S arrival times used for the locations and units in m/s); tgz file can be found in Waveforms.tgz. EVDP SAC header is expressed in meters.</li> </ul> <p>Continuous raw time series can be dowloaded from Oasis website (Priolo et al., 2015).</p> <p> </p>
Calibrated Relocations for the TXAR Catalog (2009–2016)
<p>This dataset contains the relocated earthquake catalog for the Southern Delaware Basin, as described in the published research paper titled <strong>"Insights into Temporal Evolution of Induced Earthquakes in the Southern Delaware Basin Using Calibrated Relocations from the TXAR Catalog (2009–2016)"</strong>.</p> <p>The earthquake relocation was performed using <strong>Hypocentroidal Decomposition</strong> technique, which provided improved spatial resolution for 73 events of magnitude 1.5 or greater in the TXAR catalog. The virtual hypocentroid used for relocating the TXAR catalog events was inverted from a core cluster of 116 post-2020 events recorded by the Texas Seismological Network. This relocated catalog includes key hypocentral parameters for each event—latitude, longitude, and depth—along with origin time, associated uncertainty estimates, and magnitude.</p> <p>This dataset serves as a critical resource for understanding the temporal and spatial patterns of induced seismicity related to anthropogenic activities, such as shallow fluid injection, in the Southern Delaware Basin before the operation of local seismic networks in the region. It is well-suited for use in further seismic hazard assessments, modeling studies, and comparisons with other induced seismicity datasets.</p> <h3>Citation:</h3> <p>Asiye Aziz Zanjani, Heather R. DeShon, Vamshi Karanam, Alexandros Savvaidis; <strong>Insights into Temporal Evolution of Induced Earthquakes in the Southern Delaware Basin Using Calibrated Relocations from the TXAR Catalog (2009–2016)</strong>. <em>The Seismic Record</em>, 2024; 4(2): 140–150. DOI: <a href="https://doi.org/10.1785/0320240011" target="_new" rel="noopener">https://doi.org/10.1785/0320240011</a></p>
Sevilleta LTER Vegetation Sample Catalog- Ground Samples for Chemical Analysis
Several long-term studies at the Sevilleta LTER measure net primary production (NPP) across ecosystems and treatments. Net primary production is a fundamental ecological variable that quantifies rates of carbon consumption and fixation. Estimates of NPP are important in understanding energy flow at a community level as well as spatial and temporal responses to a range of ecological processes. The NPP weight data (SEV 157) is obtained by harvesting a series of covers for species observed during plot sampling. These species are always harvested from habitat comparable to the plots in which they were recorded. This data is then used to make volumetric measurements of species and build regressions correlating biomass and volume. From these calculations, seasonal biomass and seasonal and annual NPP are determined. These sampled are then vouchered for use to do analyses of inorganic and organic components such as carbon, nitrogen, and phosphorous as well as and other macro and micro nutrients and organic components such as cellulose and lignin.
Variability Census of Legacy Catalogs: New Pulsating Variables and Eclipsing Binaries
<div> <p>I present the preliminary results of a comprehensive variability census of the four legacy catalogs: BD (+CD+SD), HD, SAO, and PPM. This dedicated survey project aims to identify bright A-F type variable stars using high-precision space photometry from the Transiting Exoplanet Survey Satellite (TESS ) and Gaia. Phases I through V of this survey, encompassing analyses of 193,940 A-F stars selected from the aforementioned catalogs, have been completed. To date, the project has yielded a substantial number of new variable star discoveries, including: over 14,510 new δ Scuti stars, more than 18,382 new γ Doradus stars, and over 2,354 new eclipsing binary systems, with approximately 360 binaries exhibiting pulsations in the primary components. Furthermore, thousands of rotational variables and dozens of Heartbeat stars and RR Lyrae stars have been identified, demonstrating the power of this systematic approach in revealing the rich diversity of stellar variability. Due to potential blending and contamination in TESS photometry, the binarity of a few pulsating stars or those eclipsing binaries exhibiting superimposed intrinsic pulsations of <em>δ</em> Scuti and <em>γ</em> Doradus types should be rechecked. Follow-up studies of individual systems are necessary to resolve contamination issues and accurately identify the true source of variability.</p> <p> </p> </div> <div> <p>The full list of newly identified variable stars is presented in machine-readable format in the attached file `PPM_AFstars_NewVar_R5.csv', and an atlas of selected representative light curves is provided as a separate PDF.</p> </div> <p> </p> <p><strong>Citation:</strong> Zhou, Ai-Ying: 2023, <em>Res. Notes AAS,</em> Vol.<strong>7, </strong> 210 (I)</p> <p> Zhou, Ai-Ying: 2024, <em>Res. Notes AAS,</em> Vol.<strong>8, </strong> 81 (II)</p> <p> Zhou, Ai-Ying: 2024, <em>Res. Notes AAS,</em> Vol.<strong>8, </strong> 190 (III)</p> <p> Zhou, Ai-Ying: 2025, <em>Res. Notes AAS,</em> Vol.<strong>9, </strong> 56 (IV)</p> <p> Zhou, Ai-Ying: 2025, <em>Res. Notes AAS,</em> Vol.<strong>9, </strong> 1?? (V)</p>
Documents first indexed in the SLUB catalog in 2022
<p>The data set is available as a gzip-compressed, line-delimited JSON file and contains the 7,127,497 documents first indexed in the <a href="https://katalog.slub-dresden.de">SLUB catalog</a> in 2022 with the fields id (document identifier) and first_indexed (timestamp). The id consists of a creator id (optional), source id and a record id according to the scheme [{creator_id}-]{source_id}-{record_id}. If the record id contains characters that are unsuitable for URLs, it is base64-encoded without any padding. The first_indexed field, which is part of VuFind's Solr index schema, was determined using a Django application that regularly monitors the Solr cores of the SLUB catalog. The respective document sets from different points in time are compared with each other in order to determine new documents, i.e. document identifiers. If a new document is found, first_indexed is assigned the timestamp from the last_indexed field. The field obtained in this way serves as the basis for creating a list of new titles. However, it should be noted that neither all first indexed documents necessarily represent new titles, nor do the documents contained in this data set still have to be in the catalog. To check whether a document is currently in the SLUB catalog, its detailed view can be retrieved using the following URL scheme: https://katalog.slub-dresden.de/id/{id}. Example: <a href="https://katalog.slub-dresden.de/id/0-173837243X">https://katalog.slub-dresden.de/id/0-173837243X</a>.</p>
Documents first indexed in the SLUB catalog in 2023
<p>The data set is available as a gzip-compressed, line-delimited JSON file and contains the 17,182,153 documents first indexed in the <a href="https://katalog.slub-dresden.de/">SLUB catalog</a> in 2023 with the fields id (document identifier) and first_indexed (timestamp). The id consists of a creator id (optional), source id and a record id according to the scheme [{creator_id}-]{source_id}-{record_id}. If the record id contains characters that are unsuitable for URLs, it is base64-encoded without any padding. The first_indexed field, which is part of VuFind's Solr index schema, was determined using a Django application that regularly monitors the Solr cores of the SLUB catalog. The respective document sets from different points in time are compared with each other in order to determine new documents, i.e. document identifiers. If a new document is found, first_indexed is assigned the timestamp from the last_indexed field. The field obtained in this way serves as the basis for creating a list of new titles. However, it should be noted that neither all first indexed documents necessarily represent new titles, nor do the documents contained in this data set still have to be in the catalog. To check whether a document is currently in the SLUB catalog, its detailed view can be retrieved using the following URL scheme: https://katalog.slub-dresden.de/id/{id}. Example: <a href="https://katalog.slub-dresden.de/id/0-185178604X">https://katalog.slub-dresden.de/id/0-185178604X</a>.</p>
New items activated in the SLUB catalog in 2022
<p>The data set is available as a gzip-compressed, line-delimited JSON file and contains the 18,790 documents with new items activated in the <a href="https://katalog.slub-dresden.de">SLUB catalog</a> in 2022 with the fields id (document identifier), de14_new_item_act_date (timestamp) and de14_new_item_act_date_mv (timestamps). The id consists of a source id and a record id according to the scheme {source_id}-{record_id} and enables the detailed view of a document to be retrieved using the following URL scheme: https://katalog.slub-dresden.de/id/{id}. Example: <a href="https://katalog.slub-dresden.de/id/0-173837243X">https://katalog.slub-dresden.de/id/0-173837243X</a>. Since the documents in this data set originate exclusively from the Southwest German Library Network (SWB), the source id is always 0 and the record id corresponds to the Pica Production Number (PPN) of the K10plus. The values for the fields de14_new_item_act_date and de14_new_item_act_date_mv are based on the NewItemActDate field of the corresponding items in the Libero Library Management System. While the multi-valued field de14_new_item_act_date_mv contains all dates from the year 2022 that could be assigned to a document, only the most recent date is specified in the field de14_new_item_act_date. Both fields are dynamic fields according to VuFind's Solr index schema. Until January 2021, the date values were used to display a list of new acquisitions on the SLUB website.</p>
Newly purchased items in the SLUB catalog in 2022
<p>The data set is available as a gzip-compressed, line-delimited JSON file and contains the 39,013 documents with newly purchased items in the <a href="https://katalog.slub-dresden.de">SLUB catalog</a> in 2022 with the fields id (document identifier), de14_purchase_date (timestamp), de14_purchase_date_mv (timestamps) and facet_de14_acquisition_code (parameters). The id consists of a source id and a record id according to the scheme {source_id}-{record_id} and enables the detailed view of a document to be retrieved using the following URL scheme: https://katalog.slub-dresden.de/id/{id}. Example: <a href="https://katalog.slub-dresden.de/id/0-173837243X">https://katalog.slub-dresden.de/id/0-173837243X</a>. Since the documents in this data set originate exclusively from the Southwest German Library Network (SWB), the source id is always 0 and the record id corresponds to the Pica Production Number (PPN) of the K10plus. The values for the fields de14_purchase_date and de14_purchase_date_mv are based on the DatePurchased field of the corresponding items in the Libero Library Management System. While the multi-valued field de14_purchase_date_mv contains all dates from the year 2022 that could be assigned to a document, only the most recent date is specified in the field de14_purchase_date. Both fields are dynamic fields according to VuFind's Solr index schema. The acquisition parameters specified in the field facet_de14_acquisition_code are based on the AcquisitionType field of the corresponding items in the Libero Library Management System. The multi-valued facet field is a dynamic field according to finc's Solr index schema. A complete list of acquisition types that appear in the data set is available as a CSV file. In addition to the codes, their translations can be found there.</p>
VAST void catalogs for SDSS DR7
<p><em>Version 1.3.1 of the void catalogs; the NSAID column in the V2*galzones.dat have been corrected (previous versions incorrectly listed the row number of the galaxy into the NSA catalog as the NSAID). The peer-reviewed publication for these catalogs is published in the Astrophysical Journal Supplemental Series, an American Astronomical Society journal. The paper is available at <a href="https://iopscience.iop.org/article/10.3847/1538-4365/acabcf" target="_blank" rel="noopener">https://iopscience.iop.org/article/10.3847/1538-4365/acabcf</a>; please cite this article when using any of these catalogs.</em></p> <p>We provide three void catalogs using a volume-limited subsample of the SDSS DR7 for two cosmologies (Planck 2018 and WMAP5) using new implementations of two different void-finding algorithms from the Void Analysis Software Toolkit (<a href="https://vast.readthedocs.io/en/latest/">VAST</a>): VoidFinder and Voronoi Voids (V<sup>2</sup>). We identify 1163 cosmic voids with VoidFinder, 531 with V<sup>2</sup> using VIDE pruning, and 518 with V<sup>2</sup> using REVOLVER pruning, with the Planck 2018 cosmology, and 1184, 535, and 519 voids with the WMAP5 cosmology, respectively. These catalogs exist within the SDSS DR7 main survey volume, out to a maximum redshift of 0.114. Effective radii and centers for all voids are computed and included with the catalogs; the median void effective radius is 15-19 <em>h</em><sup>-1</sup> Mpc for all three catalogs, and none have an effective radius larger than 54 <em>h</em><sup>-1</sup> Mpc.</p> <p>All catalog files are in ASCII format with commented headers. An example of each file is shown in Tables 1-5 in the associated journal article. For each galaxy in the _galzones.dat files, the NSAID column corresponds to that galaxy's ID number in the NASA-Sloan Atlas. Guidance on how to use these catalogs can be found at <a href="https://vast.readthedocs.io/en/latest/">https://vast.readthedocs.io/en/latest/</a>. We also provide the mask file used in generating the VoidFinder void catalog with Planck 2018 cosmology.</p> <p><strong>Planck 2018 cosmology</strong></p> <ul> <li><strong>VoidFinder</strong> <ul> <li>VoidFinder-nsa_v1_0_1_Planck2018_comoving_holes.txt</li> <li>VoidFinder-nsa_v1_0_1_Planck2018_comoving_maximals.txt</li> <li>NSA_main_mask.pickle</li> </ul> </li> <li><strong>V<sup>2</sup></strong> <ul> <li><strong>VIDE pruning</strong> <ul> <li>V2_VIDE-nsa_v1_0_1_Planck2018_galzones.dat</li> <li>V2_VIDE-nsa_v1_0_1_Planck2018_zonevoids.dat</li> <li>V2_VIDE-nsa_v1_0_1_Planck2018_zobovoids.dat</li> </ul> </li> <li><strong>REVOLVER pruning</strong> <ul> <li>V2_REVOLVER-nsa_v1_0_1_Planck2018_galzones.dat</li> <li>V2_REVOLVER-nsa_v1_0_1_Planck2018_zonevoids.dat</li> <li>V2_REVOLVER-nsa_v1_0_1_Planck2018_zobovoids.dat</li> </ul> </li> </ul> </li> </ul> <p><strong>WMAP5 cosmology</strong></p> <ul> <li><strong>VoidFinder</strong> <ul> <li>VoidFinder-nsa_v1_0_1_WMAP5_comoving_holes.txt</li> <li>VoidFinder-nsa_v1_0_1_WMAP5_comoving_maximals.txt</li> </ul> </li> <li><strong>V<sup>2</sup></strong> <ul> <li><strong>VIDE pruning</strong> <ul> <li>V2_VIDE-nsa_v1_0_1_WMAP5_galzones.dat</li> <li>V2_VIDE-nsa_v1_0_1_WMAP5_zonevoids.dat</li> <li>V2_VIDE-nsa_v1_0_1_WMAP5_zobovoids.dat</li> </ul> </li> <li><strong>REVOLVER pruning</strong> <ul> <li>V2_REVOLVER-nsa_v1_0_1_WMAP5_galzones.dat</li> <li>V2_REVOLVER-nsa_v1_0_1_WMAP5_zonevoids.dat</li> <li>V2_REVOLVER-nsa_v1_0_1_WMAP5_zobovoids.dat</li> </ul> </li> </ul> </li> </ul>
FraneItalia: a catalog of recent Italian landslides
<p><strong>FraneItalia</strong> is a geo-referenced catalog of recent landslides affecting the Italian territory. The catalog has been <strong>developed consulting online news sources from 2010 </strong><strong>onward</strong> and it includes both fatal landslide events and events that did not produce physical harm to people. Landslide events are classified considering two numerosity categories and three consequence categories.</p> <p>NUMEROSITY CATEGORIES</p> <ul> <li><strong>Single Landslide Events</strong> (<strong>SLE</strong>), for records only reporting one landslide;</li> <li><strong>Areal Landslide Events</strong> (<strong>ALE</strong>), for records referring to multiple landslides triggered by the same cause in the same geographic area.</li> </ul> <p>Note: the ALE category has been introduced to simplify collection of the landslide records for the numerous cases when many landslides are mentioned together in the news.</p> <p>CONSEQUENCE CATEGORIES</p> <ul> <li><strong>Very severe consequences</strong> (<strong>C1</strong>), for events with victims and/or missing people;</li> <li><strong>Severe consequences</strong> (<strong>C2</strong>), for events with injured persons and/or evacuations;</li> <li><strong>Minor consequences</strong> (<strong>C3</strong>), for events that did not cause physical harm to people.</li> </ul> <p>Note: the consequence classification is based on the severity of the effects to human life not considering other consequence measures (e.g., economic loss, environmental damage)</p> <p>INFORMATION on each recorded landslide event includes:</p> <ul> <li>data on the location of the event [compulsory entries]</li> <li>day of occurrence of the landslide(s) [compulsory entry]</li> <li>duration of the landslide event [if applicable]</li> <li>number of landslides for ALE [compulsory entry]</li> <li>classes of accuracy of the spatial and temporal data [compulsory entries]</li> <li>source(s) of information [compulsory entries]</li> <li>landslide characteristics [optional entries]</li> <li>phase of activity [optional entry]</li> <li>details on the consequences [optional entries]</li> </ul>
The Spitzer Spectroscopic Data Fusion - Merged Spectroscopic Redshift Catalogs in Spitzer Fields
<p>The Spitzer Spectroscopic Data Fusion merges miscellaneous spectroscopic information available within "popular" extragalactic survey fields.</p> <p>Last Updated on 20 March 2025 - <a href="https://zenodo.org/record/6368347">https://zenodo.org/record/6368347</a> - <a href="https://www.mattiavaccari.net/df/specz">https://www.mattiavaccari.net/df/specz</a></p> <p>Based on the Spitzer Data Fusion Project - <a href="https://doi.org/10.5281/zenodo.7850783">https://doi.org/10.5281/zenodo.7850783</a> - <a href="https://mattiavaccari.net/df">https://mattiavaccari.net/df</a></p> <p>Merged Spec-Z ("specz-merged") catalogs merge miscellaneous spec-z information available within a given field. Different spec-z catalogs available within a given field are merged (using a search radius of 1.0 arcsec), and for sources with multiple spec-z measurements the most reliable one is chosen following the (largely arbitrarily) assumed order of decreasing reliability indicated below for each field. If CAT1,...,CATN spec-z catalogs are available in a given field, Z_1 from CAT1 (i.e. NED) is adopted as "best" redshift (i.e. ZBEST), if available, otherwise Z_2 from CAT_2 is adopted if available, and so on up to Z_N and CAT_N. In using ZBEST it's thus important to bear in mind that this is not necessarily actually the "best" redshift for science purposes, and in particular that the choice of NED as CAT1 is often not ideal. However, Z_1,...,Z_N are included to allow users to define the "best" redshift based on their science needs when multiple redshift estimates are available for a given source. ZFLAG specifies which catalog is providing the ZBEST value according to the CATN number below. ZCLASS is meant to provide further info about the class/quality of the spectroscopic redshift measurement, but for the time being is not populated and is simply a copy of ZFLAG. ZWHERE is an additional binary/bit flag indicating in which of the N catalogs each source was given a spec-z estimate in. ZWHERE will e.g. be 2^0=1 if a redshift if available <em>only</em> from CAT_1, whereas it will be 2^0+2^1=3 if a redshift is available *only* from CAT1 and CAT2,<br>so that a source with a redshift available from all catalogues will have ZWHERE=2^0+...+2^n.</p> <p>See AAAREADME.SPECZ-MERGED within the ZIP archive for further information.</p>
Deep learning-based earthquake catalog of the 2022 MW 6.9 Chihshang, Taiwan, earthquake sequence
<p>On 18 September 2022, the MW 6.9 Chihshang earthquake struck the southern Longitudinal Valley, Taiwan. We use SeisBlue, a deep-learning platform/package, to extract the two-month earthquake sequence from September to October 2022, including the MW 6.5 Guanshan foreshock, the MW 6.9 mainshock, over 14,000 aftershocks, and 866 focal mechanisms from two sets of broadband networks. For more details, please refer to our research article published at TAO (Sun et al., 2024; https://doi.org/10.1007/s44195-024-00063-9). The refined SeisBlue earthquake, FMS, and 20-year M3+ relocated CWA earthquake catalogs obtained in this study are listed here.</p> <ol> <li>The refined, deep-learning-based earthquake catalog of the 2022 Mw 6.9 Chihshang, Taiwan, earthquake sequence contains 5,151 seismic events with event time, location and error information, local and moment magnitudes, and hypoDD location. </li> <li>The FMS (focal mechanism solution) catalog is obtained by the P-wave polarities of 14 broadband stations and the FPFIT program (Reasenberg & Oppenheimer, 1985). 865 out of 1629 FMSs with at least six readings of P-wave polarity, F-fator <span>≤ </span>0.1 (F <span>< </span>0.5 for a good fit), and errors of strike, dip, and rake are all <span>< </span>20<span>°</span>, respectively, are listed in the attached FMS catalog.</li> <li>The 2001-2020 3D-hypoDD-relocated M3+ CWA earthquake catalog: We applied the HypoDD program (Waldhauser & Ellsworth, 2000) to the CWA (Central Weather Administration (CWA, Taiwan), 2012) catalog with P- and S-wave arrivals and obtained 5862 M3+ events between 2001 and 2020 for eastern Taiwan. The 3D velocity models used for this catalog are the local models from Kuo-Chen et al. (2012).</li> </ol> <p> </p>
Utah FORGE 2024 stimulations: Microseismic event catalog from seismic surface network
<p>This microseismic catalog of the 2024 stimulations at Utah FORGE is based on the surface monitoring network consisting of 5 permanent seismic stations deployed by the University of Utah Seismograph Stations and a temporary deployment of 144 nodal geophones.<br> <br>The catalog and its compilation are described in:<br>Niemz et al. (2024). Mapping Fracture Zones with Nodal Geophone Patches: Insights from Induced Microseismicity during the 2024 Stimulations at Utah FORGE. Submitted to Seismological Research Letters.<br> <br>The local coordinate system is relative to well 16A(78)-32 (lat=38.50402147, lon=-112.8963897, elev=1650m). The magnitudes in this catalog were calibrated based on the local magnitude provided by the University of Utah Seismograph Stations. They are not authoritative.</p>
Fermi High-Latitude Extended Sources Catalog (FHES)
<p>The data set contains results of the Fermi High-Latitude Extended Sources Catalog.</p> <p>The FITS file contains the Fermi High-Latitude Extended Sources Catalog (FHES). It provides source extension parameters (or upper limits thereof) and additional information for objects measured in 90 months of observations with the Large Area Telescope (LAT) on board NASA's Fermi satellite.<br> It includes the complete analysis results for 2546 sources. The analysis and data products contained in the catalog are described in detail in the accompanying paper, published in the Astrophysical Journal Supplement, <a href="https://doi.org/10.3847/1538-4365/aacdf7">https://doi.org/10.3847/1538-4365/aacdf7</a>. The preprint of the manuscript can be found here: <a href="https://arxiv.org/abs/1804.08035">https://arxiv.org/abs/1804.08035</a><br> <br> We further provide the 95% lower limits on the intergalactic magnetic field (IGMF) as plain ASCII files for different assumptions on the blazar duty cycles. These correspond to the limits shown in Figure 17 (right panel) of the paper.</p>
Supplemental catalogs for "The Sloan Digital Sky Survey Reverberation Mapping Project: Sample Characterization"
<p>We have compiled additional properties for the SDSS-RM sample in several ancillary catalogs. Below are the notes on these supplemental catalogs. There are .readme files for each additional catalog. We also include the quality assurance plots for the global spectral fits.</p> <p><strong>QA-0000-56837.ps.gz </strong>The full set of 849 quality assessment plots for the global spectral fitting. Each plot includes a top panel showing the continuum (brown) and Fe II (blue) model components; the red line is the sum of the two. The cyan diamonds are pixels masked as absorption or bad pixels. The gray brackets near the top of the panel indicate the windows used for the continuum+Fe II fit. The bottom panels present the emission line fits for five line complexes.</p> <p><strong>allqso_sdssrm.fits</strong> A FITS table of all 1214 known quasars in the 7 square degree SDSS-RM field. Only 849 of them received a fiber in the SDSS-RM spectroscopy. This table lists the basic target information of these quasars.</p> <p><strong>QSObased_Expanded_SDSSRM_107.fits</strong> The narrow MgII/FeII absorber catalog for SDSS-RM quasars, following the methodology outlined in Zhu & Ménard (2013). Each entry corresponds to one quasar. The search for narrow absorbers includes systems that have absorber redshift close to the quasar systemic redshift (|dz|<0.04). MgII absorbers blueshifted from the quasar by dz>0.04 and also redward of CIV by dz>0.02 are of high purity. MgII absorbers with |dz|<0.04 or those at wavelength blueward of CIV, or those with FeII detection but no MgII detections (likely due to bad pixels), while included in this catalog, should be treated with caution, and may contain a small fraction of false positives (mainly CIV absorbers).</p> <p>For convenience, we also provide a version of the absorber catalog organized by absorbers (<strong>Expanded_SDSSRM_107.fits</strong>), i.e., each entry corresponds to one absorber system.</p> <p><strong>rmqso32_aegis_multi_lambda.fits</strong> Multi-wavelength data compiled from Nandra et al. (2015) or 32 SDSS-RM quasars in the AEGIS field.</p> <p><strong>spitzer_seip_rm_match_1.5arcsec.fits</strong> Spitzer IRAC and MIPS data from the Spitzer Enhanced Imaging Products (SEIP) source list for 176 SDSS-RM quasars, with a matching radius of 1.5 arcseconds. This file also compiles infrared fluxes (if available) from 2MASS (Skrutskie et al. 2006).</p> <p><strong>spec_2014_BALrobust.csv</strong> List of 95 BALQSOs (including mini-BALQSOs) identified from the first-year coadded spectroscopy. This file includes BAL flags on CIV, AlIII, MgII, and FeII/FeIII. It also includes notes on individual objects.</p> <p><strong>PS1_MD07_LC_sdssrm.fits</strong> PS1 Medium Deep light curves for the SDSS-RM quasars used to compute PS1_NMAG_OK and PS1_RMS_MAG in the main catalog. Note this is the unofficial release of the PS1 MD07 data, which was approved by the PS1 collaboration. These photometric light curves may differ slightly from the final official release of the PS1 Medium Deep field data. </p>
Vortex Catalog from Jovian Vortex Hunter Zooniverse citizen science project
<p>This dataset contains the aggregated results from the <a href="https://www.zooniverse.org/projects/ramanakumars/jovian-vortex-hunter/" target="_blank" rel="noopener">Jovian Vortex Hunter citizen science project</a>, where citizen science volunteers labeled images from the JunoCam instrument and determined locations and sizes of vortices.</p> <p>The CSV file contains results from the first workflow and details the consensus from volunteers on different features in each image (given by the Zooniverse Subject ID). There are five categories to choose from:</p> <ol> <li>Vortex</li> <li>Turbulent (i.e. Folded Filamentary Regions: FFRs)</li> <li>Cloud bands</li> <li>Blurry (i.e., image issues)</li> <li>Featureless (there is no discernable feature in the image)</li> </ol> <p>The CSV file also contains an additional column defining the number of classifications of the subject.</p> <p>The JSON file contains the aggregated catalog of vortices and their properties from the second workflow. The format of the JSON file is as below:</p> <p>Each entry contains a dictionary of vortex properties, as shown below. The entry is determined by aggregating the vortex properties across multiple Zooniverse images which share the vortex, and building a consensus from multiple volunteer responses.</p> <pre><code>{ "subject_ids": [array of Zooniverse subject ID for each vortex], "perijove": the perijove corresponding to the image from this vortex was determined "color": the aggregated color of the vortex determined from volunteer responses, "lon": System III planetographic longitude [degree], "lat": planetographic latitude [degree], "x0", "y0": reference coordinate on the Zooniverse crop image for longitude/latitude, "x", "y": coordinate of the vortex center on the Zooniverse crop image "rx", "ry": radius of the vortex in pixel coordinates on the Zooniverse crop image "angle": angle in degree from horizontal of the orientation of the vortex in the Zooniverse crop image, "sigma": 1sigma error in the scale of the vortex, "angular_width": width of the vortex in degrees on the planet, "angular_height": height of the vortex in degrees on the planet, "physical_width", "physical width": width/height of the vortex in km, "extracts": [ array of dictionaries consisting of individual ellipses that make up the vortex consensus ] "colors": { "brown": consensus on the vortex being brown [0-1], "red": consensus on the vortex being red [0-1], "dark": consensus on the vortex being dark [0-1], "white": consensus on the vortex being white [0-1], "white-brown": consensus on the vortex being white and brown [0-1], "white-red": consensus on the vortex being white and red [0-1], "red-brown": consensus on the vortex being red and brown [0-1], } }</code></pre> <p>Each extract is a dictionary containing the following properties. An extract is a single aggregated ellipse on a single Zooniverse image.</p> <pre><code>{ "subject_id": Zooniverse subject ID, "perijove": the perijove when the JunoCam image was taken, "color": the color of the vortex with the highest vote fraction, "lon": System III longitude of the vortex [degree], "lat": planetographic latitude of the vortex [degree], "x0", "y0": reference coordinate on the Zooniverse crop image for longitude/latitude, "x", "y": coordinate of the vortex center on the Zooniverse crop image "rx", "ry": radius of the vortex in pixel coordinates on the Zooniverse crop image "angle": angle in degree from horizontal of the orientation of the vortex in the Zooniverse crop image, "probability": the 1sigma error in the scale of the vortex, "angular_width": width of the vortex in degrees on the planet, "angular_height": height of the vortex in degrees on the planet, "physical_width", "physical width": width/height of the vortex in km, }</code></pre>
Calibrated Earthquake Relocations from the TexNet Catalog (2017–2022) and Vertical Surface Deformation (2016–2022)
<p>This repository contains the relocated earthquake catalog for the Southern Delaware Basin, as presented in the manuscript titled "<em><strong>Insights into Spatiotemporal Evolution of Induced Earthquakes in the Southern Delaware Basin Using Calibrated Relocations from the TexNet Catalog (2017-2022)</strong>".</em></p> <h3>Citations:</h3> <p>Asiye Aziz Zanjani, Heather R. DeShon, Vamshi Karanam, Alexandros Savvaidis; <strong>Insights into Temporal Evolution of Induced Earthquakes in the Southern Delaware Basin Using Calibrated Relocations <em>from the TexNet Catalog (2017-2022</em>) (2025)</strong>. <em>Earth and Space Science, 12 (6), e2024EA004027. <a title="https://doi.org/10.1029/2024EA004027" href="https://doi.org/10.1029/2024EA004027"><strong>https://doi.org/10.1029/2024EA004027</strong></a></em></p> <p>The earthquake relocations were conducted using the Hypocentroidal Decomposition technique with the <strong>open-source MLOC code</strong>, achieving enhanced spatial resolution for over 5,000 events from the TexNet catalog. The relocated catalog includes critical hypocentral parameters—latitude, longitude, depth—as well as origin time, associated uncertainties, and magnitude for each event.</p> <p>This dataset is an essential resource for analyzing the spatiotemporal patterns of induced seismicity associated with anthropogenic activities, such as shallow fluid injection, in the Southern Delaware Basin following the operation of TexNet in 2017. It is suitable for use in seismic hazard assessments, modeling studies, and comparisons with other induced seismicity datasets. Additional data produced during this research includes vertical surface deformation measurements from 2016 through the end of 2022.</p> <p>The repository also contains data referenced in the manuscript’s “Data Availability Statement” and “Open Research” sections. </p> <p>List of files attached to this repository:</p> <ul> <li><strong>catalog.xls</strong>: Primary earthquake relocated catalog developed in this study</li> <li><strong>2016_2022_deformation.csv</strong>: Vertical displacement data (2016–2018) developed in this study</li> <li><strong>2019_2022_deformation.csv</strong>: Vertical displacement data (2016–2022) developed in this study</li> <li><strong>post-2017-injection.xlsx</strong>: Injection data from the Railroad Commission of Texas (<a href="https://www.rrc.texas.gov">source</a>)</li> <li><strong>Hydrofracking-post2017.xlsx</strong>: Hydrofracking well data from FracFocus (<a href="https://fracfocus.org">source</a>)</li> <li><strong>GrowClust-common.xls</strong>: 2-D GrowClust catalog for supplemental information (<a href="https://hirescatalog.texnet.beg.utexas.edu/">source</a>), https://doi.org/10.15781/76hj-ed46</li> <li><strong>TexNet-Catalog</strong>: Initial TexNet catalog's origin and phase data, https://doi.org/10.7914/SN/TX</li> </ul>
Updated NLL-SSST-coherence earthquake relocation catalog for the 2020 Mw 6.5 Monte Cristo Range, Nevada earthquake sequence.
<p>CSV catalog and plots of NLL-SSST-coherence earthquake relocations of 17583 events M≥1 2020.01.01 to 2021.08.20 for the 2020 Mw 6.5 Monte Cristo Range, Nevada earthquake sequence.</p> <p>This dataset is an update of the relocations presented in the pre-print article:<br> The 2020 Mw 6.5 Monte Cristo Range, Nevada earthquake: relocated seismicity shows rupture of a complete shear-crack system<br> https://eartharxiv.org/repository/view/1904/</p> <p> </p> <p>Plots show map, view from south and view from N73E of NLL-SSST-coherence relocations events with error-ellipsoid, semi-major axis ≤ 5 km. Caption (adapted from https://eartharxiv.org/repository/dashboard/1904/ ; Fig 2):</p> <p>Event color showing hypocenter depth and symbol size proportional to magnitude. Re-picked Mw6.5 hypocenter and its proxy (mean hypocenter of 3 well constrained foreshocks) indicated by small and large, dark red, cross symbols, respectively. SHmin and SHmax show directions of regional minimum and maximum compressive stress, respectively; the intermediate principal stress axis is vertical. Seismic stations shown as dark gray tetrahedrons. Brown lines show faults from the Quaternary fault and fold database for the United States. Background topography image from OpenTopgraphy.org. Red lines show mapped surface ruptures from http://www.nbmg.unr.edu/Geohazards/Earthquakes/MonteCristoRangeEQData.html and https://doi.org/10.1785/0220200371</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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