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131 results for “agn”
Database of fitted spectra for: Changing-Look AGNs - I. Tracking the transition on the main sequence of quasars
<h3>Results from the spectral fitting for a sample of changing-look active galactic nuclei (AGNs) with SDSS spectroscopy using PyQSOFit.</h3>
X-rays across the galaxy population: The distribution of AGN accretion rates as a function of stellar mass and redshift
<p>We provide measurements of the probability distribution function of specific black hole accretion rates within a sample of galaxies of a given stellar mass and redshift, <span class="math-tex">\(p(\log \lambda_{sBHAR} | M_*,z)\)</span>. Measurements are provided for all galaxies, star-forming galaxies and quiescent galaxies. We also provide estimates of the AGN duty cycle, <span class="math-tex">\(f(\lambda_{sBHAR} >0.01)\)</span> i.e. the fraction of galaxies with an AGN above a given limit in specific accretion rate, based on the probability distribution functions. Full details are provided in Aird et al. (2018, MNRAS, 474, 1225); please cite this publication if you use these measurements. </p>
Review of redshift values of bright AGNs with hard spectra in 4LAC catalog v3
<p>Review of redshift values of bright AGNs with hard spectra in 4LAC catalog</p> <p>FITS table and description file (pdf)</p>
LSSTC AGN Data Challenge 2021
<p>This repository hosts the dataset used in the LSSTC AGN Data Challenge (DC) 2021 (PI: Gordon Richards). More information about the data challenge can be found in the DC GitHub repository @ https://github.com/RichardsGroup/AGN_DataChallenge. </p> <p><strong>Dataset Versions: </strong></p> <p><strong>1.0: </strong>The initial dataset used in the DC, as well as the blinded dataset (ObjectTable_Blinded.parquet) that was used to evaluate submissions. Note that the image cutouts are not included here due to the large size, but the script used to generate those cutouts using SDSS archive services is included in the DC GitHub repository.</p> <p><strong>1.1: </strong>The same dataset as in v1.0 but with the following updates:</p> <ul> <li>Uncovered the true coordinates of each source in the dataset</li> <li>Added E(B-V) for every source using the SFD1998 dust map</li> <li>Added spectrum source information (i.e., SDSS fiberid, plate, mjd) if available. </li> </ul> <p> </p> <p><strong>Caveat:</strong> </p> <ul> <li>The optical (grizY) and NIR photometry of sources in the XMM-LSS field is a product of the HSC/VISTA pixel-level joint processing initiative led by Raphael Shirley and Manda Banerji. Thus, it is an early prototype dataset and is still subject to testing and characterization.</li> </ul> <p> </p> <p><strong>Citation:</strong></p> <p>The DC dataset released here is a compilation of data from various sources. If you find the DC dataset useful for your research and would like to acknowledge it, please also reference the original sources of the data. Below is a list of publications that you should consider citing. </p> <p><em>X-ray in XMM-LSS (XMM-SERVS): </em>2018MNRAS.478.2132C</p> <p><em>UV Photometry (GALEX): </em>2017ApJS..230...24B</p> <p><em>Optical Photometry (in the object/source tables): </em></p> <ul> <li>DES: 2021ApJS..255...20A</li> <li>SDSS Stripe 82 Coadd: 2014ApJ...794..120A</li> <li>HSC DR2: 2019PASJ...71..114A</li> </ul> <p><em>Optical Light Curves (in the ForcedSource table):</em></p> <ul> <li>SDSS DR7: 2009ApJS..182..543A</li> <li>SDSS II Supernova Survey: 2008AJ....135..338F</li> </ul> <p><em>Astrometry (i.e., parallax, proper motion):</em></p> <ul> <li>Gaia EDR3: 2021A&A...649A...1G</li> <li>NOIRLab Source Catalog DR2: 2021AJ....161..192N</li> </ul> <p><em>NIR in XMM-LSS (VISTA/VIDEO): </em>2013MNRAS.428.1281J</p> <p><em>NIR in Stripe 82 (UKIDSS):</em></p> <ul> <li> <p>2006MNRAS.367..454H</p> </li> <li> <p>2007MNRAS.379.1599L</p> </li> <li> <p>2008MNRAS.384..637H</p> </li> <li> <p>2009MNRAS.394..675H</p> </li> </ul> <p><em>Optical u-band in XMM-LSS (CFHTLS):</em> 2012yCat.2317....0H</p> <p><em>MIR in XMM-LSS </em>(Spitzer DeepDrill): 2021MNRAS.501..892L</p> <p><em>MIR in Stripe 82 </em>(SpIES): 2016ApJS..225....1T</p> <p><em>FIR</em> (Hershel/HELP): 2019MNRAS.490..634S</p> <p><em>Radio</em> (FIRST): 1994ASPC...61..165B</p> <p><em>HighZ QSOs: </em></p> <ul> <li>2016ApJ...819...24W</li> <li>2016ApJ...829...33Y</li> </ul> <p><em>SDSS Spectroscopy:</em></p> <ul> <li>SDSS DR16: 2020ApJS..249....3A</li> <li>SDSS DR16 Quasar Catalog: 2020ApJS..250....8L</li> </ul> <p> </p> <p> </p>
Agnes Pauline Prell (p1382)
<b>-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> --</b><br><br><u>Name</u>: Agnes Pauline Prell<br><u>musiXplora-ID</u>: p1382<br><u>musiXplora-URI</u>: <a href="https://musixplora.de/mxp/p1382">https://musixplora.de/mxp/p1382</a><br><u>Gender</u>: f<br><u>Date of Birth</u>: 14 September 1922<br><u>Place of Birth</u>: München<br><u>Date of Death</u>: 20 March 1982<br><u>Place of Death</u>: München<br><u>First Mentioned</u>: 1927<br><u>Sectors</u>: Kabarett/Kleinkunst<br><u>Professions (Historical)</u>: Volkssänger<br><u>Professions (Musical)</u>: Sängerin, Unterhaltungskünstlerin<br><u>Main Place of Activity</u>: München<br><br><br><u>Herkunftsfamilie:</u><br><table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Eltern</td><td>Tochter</td><td>Ludwig Prell</td><td><a href="https://musixplora.de/mxp/p1374">p1374</a></td></tr></tbody></table><br><br><u>Changelog</u>:<br> - v0.0.1: Initial Upload.<br>
Catalog Data for Prior-Informed AGN-Host Spectral Decomposition Using PyQSOFit
<p>This catalog contains 76,565 AGN-host decomposed spectral measurements for all quasars with z<0.8 in SDSS DR16Q. Our prior-informed decomposition method significantly improved the decomposition success rate from less than 60% to 94%. For the first time, we perform the AGN-host spectral decomposition on survey scale catalog.</p> <p>Our spectral decomposition results are highly consistent to those of HSC image decomposition. Our catalog suggests that an average host galaxy contribution at 5100A is 38.8%, which would lead to an overestimation of 0.215 dex in L5100 and 0.219 dex in black hole mass if the host is not removed. The Dn4000 and stellar velocity dispersion measurements from the decomposed host galaxy spectra are also provided.</p> <p>Please read this paper for more techinique details: <a href="https://arxiv.org/abs/2406.17598">arXiv: 2406.17598</a></p>
Basic Considerations for the Observability of Kinematically Offset Binary AGN
<p>KDE resampled massive black-hole (MBH) binary population used for the analysis in Kelley 2020, <em>Considerations for the Observability of Kinematically Offset Binary AGN</em> (2005.10255).</p> <p>We start with a population of MBH binaries derived from the Illustris cosmological simulations, and evolved using semi-analytic post-processing models. These methods are described in Kelley et al. 2016 (1606.01900) and Kelley et al. 2017a,b (1702.02180 and 1711.00075). We then use the kernel density estimation (KDE) technique to resample this population from the Illustris volume, into a sample of binaries from a full, simulated light-cone of observations. The binaries are resampled in bins of observed orbital period. The number of resampled binaries in a given period bin are restricted to 500,000. When this occurs, the 'weight' of those binaries is assigned a value greater than one, while the 'weight' of binaries in unrestricted period bins is set to unity. For example, if the 'true' number of binaries in a bin should have been 1e6, the number of samples would be restricted to 5e5, and the weight of each of those binaries would be set to 2.0. If the number of binaries in a bin were instead 2e5, which is less than the limit, then each of those binaries is given a weight of 1.0. Only a single realization of this sample is included, but additional realizations can be produced if needed and on request.</p> <p>The data are presented in hdf5 format and contain the following arrays:</p> <pre><code># Meta-Data `periods`: shape: (201,) units: seconds descr: the edges of the bins in observed orbital period from which the population was sampled. `counts`: shape: (200,) units: None descr: The number of binaries produced in each period bin. This number for each bin is capped at 500,000. The sum of these values equals the total number of samples (70622013). # Data In this particular realization of data, the number of sampled binaries is `S = 70622013`. `mtot`: shape: (S,) units: grams descr: the total mass of each binary (`M = M1 + M2`). `mrat`: shape: (S,) units: None descr: The mass ratio of each binary, `q = M2/M1 <= 1.0`, where M2 is the mass of the secondary (lower mass) component. `pobs`: shape: (S,) units: seconds descr: The orbital period of each binary in the observer's rest frame (at redshift, `z = 0`). `redz`: shape: (S,) units: None descr: The redshift of each binary. `weights`: shape: (S,) units: None descr: The number of 'true' binaries (i.e. the number that are expected to occur in this realization of an observed universe) represented by this individual 'sample', and having similar binary parameters.</code></pre> <p> </p>
SED templates for "Dwarf AGNs from Variability for the Origins of Seeds (DAVOS): Intermediate-mass black hole demographics from optical synoptic surveys"
<p>FITS file containing the pre-computed grid of Done or Nemmen model SEDs. See Table 2 in the publication for details.</p>
The Accretion History of AGN I: Supermassive Black Hole Population Synthesis Model
<p>The X-ray Luminosity Function attached to this paper: https://ui.adsabs.harvard.edu/#abs/arXiv:1810.02298</p> <p>The python script contains instructions on how to calculate space densities using the numpy array.</p>
Catalog of X-ray & WISE AGN in the SDSS-IV eBOSS Stripe 82X Survey
<p>This catalog contains 4847 spectroscopically identified X-ray sources and <em>WISE</em> AGN candidates within the 36.8 deg<sup>2</sup> SDSS-IV eBOSS Stripe 82X survey area. This survey overlaps the largest contiguous portion of the Stripe 82 X-ray survey (15.6 deg<sup>2</sup>). Based on X-ray luminosities or <em>WISE</em> <em>W1</em>-<em>W2</em> colors (based on Assef et al. 2018), there are 4730 AGN in this catalog: 1790 X-ray AGN and 3638 <em>WISE</em> AGN, of which 698 are X-ray and <em>WISE</em> AGN. The sample is 82% complete to <em>r</em> ~ 22, where the X-ray and <em>WISE</em> AGN samples are 88% and 82% complete, respectively, at this magnitude limit.</p> <p>The redshifts and spectroscopic classifications include spectra from the SDSS-IV eBOSS Stripe 82X survey, previous data releases of SDSS (Abazajian et al. 2009; Aihara et al. 201; Alam et al. 2015; Albareti et al. 2017; Abolfathi et al. 2019; Pâris et al. 2017, 2018), 2SLAQ (Croom et al. 2009), 6dF (Jones et al. 2004, 2009), and dedicated follow-up programs of Stripe 82 X-ray sources (LaMassa et al. 2016, 2017, and published here for the first time). Description of the catalog columns are given in LaMassa et al. (2019). </p>
Predicted UV-to-Radio SEDs of little red dots: AGN and SF
<p>Predicted Dust SEDs for JWST's Little Red Dots<br>17-Sep-2024</p> <p>Here are the average UV through radio spectral energy distributions predicted for the LRD population from Figure 2 of Casey et al. (2024b, https://arxiv.org/abs/2407.05094, ApJL in press). There are two SEDs: one predicting the emission is due to AGN and one that it is due to star-formation. Wavelength is given as log10 of rest-frame wavelength in microns. Flux density is log10 Fnu in mJy. Email cmcasey.astro@gmail.com with questions.</p>
Linked collectors and determiners for: Agnes Marion Ayre Herbarium (NFLD).
Natural history specimen data linked to collectors and determiners held within, "Agnes Marion Ayre Herbarium (NFLD)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/cd4cd181-ae56-4595-8c80-d4311654ad03">https://bionomia.net/dataset/cd4cd181-ae56-4595-8c80-d4311654ad03</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/cd4cd181-ae56-4595-8c80-d4311654ad03">https://gbif.org/dataset/cd4cd181-ae56-4595-8c80-d4311654ad03</a>. Formatted as a Frictionless Data package.
Coordinates of the low-lying energy Agn isomers and the Agn-Tyr complexes
<p>Noble metal clusters with a size around the Fermi wavelength of electrons display quantum confinement effects and properties such as photoluminescence, two-photon absorption, and second and third-harmonic generation. As a result of these unique features, noble metal clusters are increasingly gaining popularity in optics and catalysis. Being highly reactive, it is standard practice to use capping agents to stabilize them.</p> <p>This dataset contains the structural parameters for the low-lying energy Ag<sub>n</sub> isomers and the Ag<sub>n</sub>-Tyr complexes from n = 3–12, all fully optimized at the B3PW91 functional combined with the def2-TZVP basis set. The structural parameters were obtained using a global search strategy combined with DFT calculations to explore the potential energy surface of clusters of atoms and molecules.</p>
The TELPERION Survey for Extended Emission Regions around AGN: a strongly-interacting and merging galaxy sample
<p>FITS files of narrowband and broadband images used in the search of the TELPERION merging-galaxy sample for AGN-ionized extended [O III] clouds, and confirming longslit spectrum as described in the manuscript. A full list of observation sites and dates, and guide to file names, are in the file 000Readme.txt</p> <p>Analysis is in the paper of the same title submitted to the Monthly Notices of the Royal Astronomical Society.</p> <p> </p>
Supporting Materials for: The calm before the (next) storm: no third outburst in 2019--2020, and ongoing monitoring of the transient AGN IC 3599
<p>This deposit contains supporting materials for the article "The calm before the (next) storm: no third outburst in 2019--2020, and ongoing monitoring of the transient AGN IC 3599" by Grupe, Komossa, and Wolsing (2024), ApJ. </p> <p>The deposit has the following machine-readable tables:</p> <p><a href="../api/records/10899673/draft/files/MRT_longterm_xray_fig1.txt/content" target="_blank" rel="noopener noreferrer">MRT_longterm_xray_fig1.txt</a>: contains the data used to create Figure 1. These are 0.2-2.0 keV fluxes of IC 3599 fromm ROSAT, Chandra, and Swift observations. </p> <div> </div> <div><a href="../api/records/10899673/draft/files/MRT_swift_observations.txt/content" target="_blank" rel="noopener noreferrer">MRT_swift_observations.txt </a>: contains the information about the Swift XRT and UVOT observations, including the Target ID, segement, start and end times in UT, the MJD of the middle of the exposure times in the XRET and each of the UVOT filters. This table is Table 1 in the Appendix of the paper</div> <div> </div> <div> </div> <div><a href="../api/records/10899673/draft/files/MRT_Swift_results.txt/content" target="_blank" rel="noopener noreferrer">MRT_Swift_results.txt</a> : contains the fluxes measured in the XRT and UVOT filters. These results were used to create Figures 2 - 7. This table is Table 3 in the Appendix of the paper. </div> <div> </div> <p>The deposit conatins the UV W2 image that was use to create Figure 10. This is <a href="../api/records/10899673/draft/files/uvw2_sum_low_2013_2023.fits/content" target="_blank" rel="noopener noreferrer">uvw2_sum_low_2013_2023.fits</a></p> <p> </p> <p>The files <a href="../api/records/10899673/draft/files/arf_pc_2013_2023.fits/content" target="_blank" rel="noopener noreferrer">arf_pc_2013_2023.fits</a> , <a href="../api/records/10899673/draft/files/backgr_spec_pc_2013_2023.fits/content" target="_blank" rel="noopener noreferrer">backgr_spec_pc_2013_2023.fits</a> , <a href="../api/records/10899673/draft/files/source_spec_pc_2013_2023.fits/content" target="_blank" rel="noopener noreferrer">source_spec_pc_2013_2023.fits </a>were used for the X-ray spectral analysis of the low state data between 2013-2023. This low state spectrum is displayed in Figures 8 and 9, and was used for the</p> <p>spectral energy distribution in Fugure 11. </p> <p> </p> <p>The files <span><a href="../api/records/10899673/draft/files/arf_pc_high_2010.fits/content" target="_blank" rel="noopener noreferrer">arf_pc_high_2010.fits</a></span> , <span><a href="../api/records/10899673/draft/files/backgr_spec_high_2010.fits/content" target="_blank" rel="noopener noreferrer">backgr_spec_high_2010.fits</a></span> , <span><a href="../api/records/10899673/draft/files/source_spec_high_2010.fits/content" target="_blank" rel="noopener noreferrer">source_spec_high_2010.fits</a></span> were used to do the X-ray spectral</p> <p>analysis of the 2010 high state data. This spectrum is displayed in Figure 9 and was used in Figure 11 to show the spectral energy distribution. </p> <p> </p>
AGN Unification Diagram
<p>Schematic representation of our understanding of AGN in the orientation unified scheme. The type of object seen depends on the viewing angle, whether or not the AGN produces a significant jet (radio loud or radio quiet), and the rate of accretion onto the central SMBH (low or high electromagnetic power). The centre of the schematic shows the typical components of an AGN but we note that the geometry of many of these components are still unknown. Radio-loud objects are generally thought to display bipolar jet emission whereas it is only shown on the radio-loud side here. Note radio-quiet is not the same as radio-silent as many galaxies have low level radio emission, which is not significantly above that expected from star-formation and therefore it is unknown if these host radio jets or not. The upper left and upper right quandrants are commonly referred to as low and high excitation radio galaxies (LERG/HERG) respectively. LERGs are also known as hot mode, radio mode, jet mode, and radiatively inefficient sources, while HERGs are also known as cold mode, quasar mode, radiative mode, and radiatively efficient sources. We include some of the most commonly used names for different classes of AGN including broad line radio galaxy (BLRG), narrow line radio galaxy (NLRG), narrow emission line galaxy (NELG), flat spectrum radio quasar (FSRQ), steep spectrum radio quasar (SSRQ), optically violent variables (OVV), and quasi-stellar objects (QSO). Note that while we separate quasars and QSOs as being radio loud and radio quiet respectively, these names are often used interchangeably. Surrounding the central schematic we show whether a particular combination of power, radio emission, and geometry is expected to produce broad or narrow emission lines, or MIR, radio, X-ray, or gamma-ray emission. The transparency of the colour in each ring corresponds to the increasing strength or prevalence of a particular emission type.</p>
All-sky AGN catalogue used in Veronesi et al. 2024b, and results of its cross-matching with GW events
<p>The files below contain the catalogue and the results of its cross-match with GW sky maps used in the analysis presented in Veronesi et al. 2024b (https://arxiv.org/abs/2407.21568).<br><br>Short description of the content:</p> <ul> <li><strong>Quaia_z15.csv</strong>: catalogue containing all the objects of Quaia with a redshift estimate of z<=1.5. The parent catalogue is presented in Storey-Fisher 2024 (https://ui.adsabs.harvard.edu/abs/2024ApJ...964...69S/abstract) and the related data is publicly available at https://zenodo.org/records/10403370;</li> <li><strong>completeness.csv</strong>: completeness for the 8 linear redshift bins between z=0.0 and z=1.5. Different columns correspond to different cuts in bolometric luminosity. The values of the different luminosity thresholds can be found in the parent paper;</li> <li><strong>result_crossmatch.csv</strong>: results of the cross-match between the AGN catalogue and 159 GW sky maps. For each skymap we indicate the ID of the GW event, the value of average completeness within the 90 per cent credibility level localisation volume, the sum of the probability densities associated to each AGN within such volume, weighted by the number density of the catalogue, and the difference of the logarithm of the single-event likelihood calculated at f_AGN=1 and the one at f_AGN=0.</li> </ul>
Unified Clumpy AGN Torus Model and X-ray spectrum
<p>In Buchner et al. (in prep) we develop a geometry for the X-ray obscurer of AGN. Its cloud population is consistent with existing CLUMPY (Nenkova+02) infrared models. However, we find that a inner torus ring component is required to fit local Compton-thick AGN.</p> <p>More information at <a href="https://github.com/JohannesBuchner/xars/blob/master/doc/uxclumpy.rst">https://github.com/JohannesBuchner/xars/blob/master/doc/uxclumpy.rst</a></p> <p>Our model has two geometry parameter:<br> 1) The opening of the torus, or the vertical extent of the clouds (sigma)<br> 2) The covering of the inner Compton-thick wall.<br> Further parameters are:<br> 3) Photon index and energy cut-off of the corona<br> 4) Column density in the line of sight (up to 10^26)<br> 5) Viewing angle.</p> <p>We release XSPEC table spectra here.</p>
Complementary dataset of the paper "The viewing angle in AGN SED models, a data-driven analysis"
<p>In this repository, you can find the SED data from the X-CIGALE estimates from the article: "<a href="https://academic.oup.com/mnras/article/510/1/687/6448487">The viewing angle in AGN SED models: a data-driven analysis</a>"</p>
The TELPERION Survey for Distant [O III] Clouds Around Luminous and Hibernating AGN
<p>The collection includes the FITS files of newly-obtained data used for the study “The TELPERION Survey for Distant [O III] Clouds Around Luminous and Hibernating AGN” by William C. Keel et al., submitted to Monthly Notices of the Royal Astronomical Society.</p> <p>Zip files for objects in the VCV sample (and the best-observed in the Toomre merger <br> sample) use object names as in the tablesin the manuscript. File names use these conventions:<br> Suffix o3.fits : narrowband F510 filter including redshifted [O III] emission<br> Suffix o3co.fits: as above with WCS information from the astrometry.net web service<br> Suffix v.fits: in the Johnson V band<br> Suffix vco.fits: V band, with WCS coordinate metadata<br> Suffix v2o3.fits: V image resampled to the same WCS coordinate grid as the F510 image, when the two are from different cameras and not related by a simple shift.<br> vscale.fits: resampled V image scaled for continuum subtraction from the F510 data.<br> vs.fits: as above, with small shifts accounting for asymmetric point-spread functions (PSFs).<br> vg.fits, vsg.fits: as above images, with Gaussian blur for first-order accounting of PSF differences.<br> diff.fits - difference image nominally representing pure [O III] emission. There may be a version numberb(diff2, diff3) if multiple iterations were done. These may also have names such as diff2g.fits, diff1s.fits if Gaussian blur or small shifts were done as for vs.fits, vsg.fits files.</p> <p>"flat" denotes that a low-pass spatial filter (such as a large median) has been used to reduce the effects of stray light on a difference image.</p> <p>Toomre.zip includes F510 and V images for those galaxies in the Toomre-sequence sample not included in the SARA data.</p> <p>LongSlit.zip includes reduced two-dimensional spectral data as detailed in the paper. _abs indicates that the data values are calibrated to intensity units (ergs/(cm^2 s Angstrom)) using standard-star observations; otherwise they are in instrumental units. Wavelengths are in Angstroms, in air. Data using the ADAM instrument are prefixed with that string.</p> <p>Tunable.zip includes the results of the MaNGAL and SCORPIO tunable-filter observations. The string “5007net” denotes that the continuum (“cont”) has been subtracted; “5007” by itself marks images including the [O III] line but not yet continuum-subtracted.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.