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62 results for “sdss”
All Spectra Associated with "An Empirical Template Library of Stellar Spectra for a Wide Range of Spectral Classes, Luminosity Classes, and Metallicities Using SDSS BOSS Spectra"
<p>Zip files of all the individual SDSS BOSS spectra. They are sorted by metallicity, luminosity class and spectral type, where each zip file contains all the original SDSS spectra to be co-added into each template. The fits files are in the following format: The primary HDU contains comments about the right ascension, declination and other useful object information. The first table extension contains the spectrum information (wavelength, flux, inverse variance, etc.) The second table extension contains other parameter information (object type, flags, and more). </p> <p> </p>
SDSS DR7 survey mask polygon file
<p>This is a polygon file for the <a href="https://github.com/mollyswanson/mangle">Mangle</a> software that defines the survey mask geometry for the <a href="https://classic.sdss.org/dr7/">SDSS DR7</a>. It was originally available at this, now defunt, <a href="http://space.mit.edu/~molly/mangle/download/data/sdss_dr72safe0_res6d.pol.gz">link</a>. The file was originally created and distributed by <a href="https://github.com/mollyswanson">Molly Swanson</a>.</p>
Dataset for: Star Photometry for DECaLS and SDSS Images Based on Convolutional Neural Networks
<p>The dataset consists of two parts, the training dataset and the comparison dataset. The training dataset and the comparison dataset are each divided into three parts, namely the simulation dataset, the SDSS dataset and the DECaLs dataset.</p> <p>The simulation dataset is simulated by PhoSim software and the original size of the simulation data is 512x512 pixels. The SDSS dataset is from DR12 and the ObjId of the target as well as other parameters are given in the csv file.The DECaLs dataset is from DR9.</p>
A strange dwarf scenario for the formation of the peculiar double white dwarf binary SDSS J125733.63+542850.5
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.476..109J/abstract">Jiang et al. (2018)</a>. MESA version 8845.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/sty238">10.1093/mnras/sty238</a></p>
Studies of ALMA counterparts of SDSS quasars
<p><strong>Studies of ALMA counterparts of SDSS quasars</strong></p> <p>Using a sample of 112 quasars from the 14th Data Release of the Sloan Digital Sky Survey (SDSS) within the Atacama Large Millimetre/submillimetre Array (ALMA) footprint, we explore the spectral properties of the high ionisation, broad emission \Civ. Specifically, we investigate the differences between the objects in the sample with submillimetre (submm) counterparts and those without them. We carried out a three-Gaussian fitting to model the C IV emission line in order to analyse relevant spectral properties of the total and individual components. We found a blueshift excess in the objects with submm counterparts with respect to those without submm counterparts, besides a stronger correlation between the blueshift and the line width in the former sample. Considering these findings within the context of an accretion disk wind model, these are indications of stronger outflows occurring in the quasars with submm counterparts. Furthermore, the objects in our sample had bolometric luminosity (Lbol >10^45 erg/s), indicating the potential for outflow feedback. We observe large blueshifts in high accretion rates objects, suggesting the presence of strong disk winds requiring L/LEdd > 0.1 and Mbh > 10^8 Mo. The individual components analysis showed that, in our sample, the C IV emission line can be decomposed into a narrow core (NC) with no significant shift from the line centre, a low blueshift broad component (BC) consistent with disk wind models and a redshifted very broad component (VBC). The subsample with submm counterparts exhibited higher BC widths, further supporting the presence of stronger outflows.</p>
Identifying galaxies, quasars and stars with machine learning: a new catalogue of classifications for 111 million SDSS sources without spectra - parquet format
<p>This is the same as the published data available under 10.5281/zenodo.3768398, but in the format of parquet files. This means you can access it using Dask for convenience when using cloud compute facilities. </p> <p>Abstract: We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to train an optimised random forest classifier using photometry from the SDSS and the Widefield Infrared Survey Explorer (WISE). We applied this machine learning model to 111 million previously unlabelled sources from the SDSS photometric catalogue which did not have existing spectroscopic observations. Our new catalogue contains 50.4 million galaxies, 2.1 million quasars, and 58.8 million stars. We provide individual classification probabilities for each source, with 6.7 million galaxies (13%), 0.33 million quasars (15%), and 41.3 million stars (70%) having classification probabilities greater than 0.99; and 35.1 million galaxies (70%), 0.72 million quasars (34%), and 54.7 million stars (93%) having classification probabilities greater than 0.9. Precision, Recall, and F1 score were determined as a function of selected features and magnitude error. We investigate the effect of class imbalance on our machine learning model and discuss the implications of transfer learning for populations of sources at fainter magnitudes than the training set. We used a non-linear dimension reduction technique (Uniform Manifold Approximation and Projection: UMAP) in unsupervised, semi-supervised, and fully-supervised schemes to visualise the separation of galaxies, quasars, and stars in a two-dimensional space. When applying this algorithm to the 111 million sources without spectra, it is in strong agreement with the class labels applied by our random forest model.</p> <p>When using this dataset, please reference our paper via the journal (<a href="https://arxiv.org/abs/1909.10963">https://arxiv.org/abs/1909.10963</a>) and this DOI (10.5281/zenodo.4060257). If you make use of our scripts please reference our Github repository DOI (10.5281/zenodo.3855160).</p> <p>File descriptions:</p> <p>All of these files are Pandas Dataframes, saved as uncompressed parquet files for ease of access when using cloud compute such as Dask. df_spec_classprobs.parquet contains the spectroscopically observed sources used for training and testing. This has been cleaned, and has the results of the random forest classifier added as additional columns (sources used for training have NaNs in the class_pred column). SDSS-ML-all.parquet contains the 111 million photometrically observed sources, with our class labels and probabilities added.</p>
Validation of the Bond et. al. (2010) SDSS-derived kinematic models for the Milky Way's disk and halo stars with Gaia Data Release 3 proper motion and radial velocity data
<p>We validate the Bond et. al. (2010) kinematic models for the Milky Way's disk and halo stars with Gaia Data Release 3 data. Bond et al. constructed models for stellar velocity distributions using stellar radial velocities measured by the Sloan Digital Sky Survey (SDSS) and stellar proper motions derived from SDSS and the Palomar Observatory Sky Survey astrometric measurements. These models describe velocity distributions as functions of position in the Galaxy, with separate models for disk and halo stars that were labeled using SDSS photometric and spectroscopic metallicity measurements. We find that the Bond et al. model predictions are in good agreement with recent measurements of stellar radial velocities and proper motions by the Gaia survey. In particular, the model accurately predicts the skewed non-Gaussian distribution of rotational velocity for disk stars and its vertical gradient, as well as the dispersions for all three velocity components. Additionally, the spatial invariance of velocity ellipsoid for halo stars when expressed in spherical coordinates is also confirmed by Gaia data at galacto-centric radial distances of up to 15 kpc.</p>
Efficiency of Spatially Distributed Sequential Stimulation (Sdss) for Functional Electrical Stimulation (FES) of Upper Motor Neuron Syndrome (UMR) Patients
ClinicalTrials.gov study NCT06421753. IPD Sharing: NO. Countries: 1. Publications: 0.
SDSS MOVING OBJECT CATALOG V2.0
The Sloan Digital Sky Survey (SDSS) Moving Object Catalog 3rd release lists astrometric and photometric data for moving objects detected in the SDSS. The catalog includes various identification parameters, SDSS astrometric measurements (five SDSS magnitudes and their errors), and orbital elements for previously cataloged asteroids. The data set also includes a list of the runs from which data are included, and filter response curves.
CHAMP/SDSS Nearby Low-Luminosity AGN Catalog
The combination of the Sloan Digital Sky Survey (SDSS) and the Chandra Multiwavelength Project (ChaMP; Green et al. 2004, ApJS, 150, 43) currently offers the largest and most homogeneously selected sample of nearby galaxies for investigating the relations between X-ray nuclear emission, nebular line emission, black hole masses, and the properties of the associated stellar populations. The authors provide X-ray spectral fits and valid uncertainties for all the galaxies with counts ranging from 2 to 1325 (mean 76, median 19). They present in their paper novel constraints that both X-ray luminosity L<sub>X</sub> and X-ray spectral energy distribution bring to the galaxy evolutionary sequence HII -> Seyfert/Transition Object -> LINER -> Passive suggested by optical data. In particular, the authors show that both L<sub>X</sub> and Gamma, the slope of the power law that best fits the 0.5 - 8 keV spectra, are consistent with a clear decline in the accretion power along the sequence, corresponding to a softening of their spectra. This implies that, at z ~ 0, or at low-luminosity active galactic nucleus (AGN) levels, there is an anticorrelation between Gamma and L/L<sub>Edd</sub>, opposite to the trend which is exhibited by high-z AGN (quasars). The turning point in the Gamma - L/L<sub>Edd</sub> LLAGN + quasars relation occurs near Gamma ~ 1.5 and L/L<sub>Edd</sub> ~ 0.01. Interestingly, this is identical to what stellar mass X-ray binaries exhibit, indicating that the authors have probably found the first empirical evidence for an intrinsic switch in the accretion mode, from advection-dominated flows to standard (disk/corona) accretion modes in supermassive black hole accretors, similar to what has been seen and proposed to happen in stellar mass black hole systems. The anticorrelation the authors find between Gamma and L/L<sub>Edd</sub> may instead indicate that stronger accretion correlates with greater absorption. Therefore, the trend for softer spectra toward more luminous, high-redshift, and strongly accreting (L/L<sub>Edd</sub> >~ 0.01) AGNs/quasars could simply be the result of strong selection biases reflected in the dearth of type 2 quasar detections. The cross-match of all ChaMP sky regions imaged by Chandra/ACIS with the SDSS DR4 spectroscopic footprint results in a parent sample of 15,955 galaxies on or near a chip and a subset of 199 sources that are X-ray detected. Among those, only 107 sources have an off-axis angle (OAA) Theta <0.2 degrees and avoid ccd=8 due to high serial readout noise; these 107 objects comprise the main sample that the authors employ for this study and that are listed in this table. The authors performed direct spectral fits to the X-ray counts distribution using the full instrument calibration, known redshift, and Galactic 21-cm column nH<sub>Gal</sub>. Source spectra were extracted from circular regions with radii corresponding to energy encircled fractions of ~90%, while the background region encompasses a 20 arcsec annulus, centered on the source, with separation 4 arcsecs, from the source region. Any nearby sources were excised, from both the source and the background regions. The spectral fitting was done via yaxx ('Yet Another X-ray eXtractor': Aldcroft 2006, BAAS, 38, 376), an automated script that employs the CIAO Sherpa tool. Each spectrum was fitted in the range 0.5 - 8 keV by two different models: (1) a single power law plus absorption fixed at the Galactic 21-cm value (model 'PL'), and (2) a fixed power law of photon index Gamma = 1.9 plus intrinsic absorption of column nH (model 'PLfix'). For the nine objects with more than 200 counts, the authors employed a third model in which both the slope of the power law and the intrinsic absorption were free to vary (model 'PL_abs'). This table was created by the HEASARC in January 2012 based on <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/ApJ/705/1336/">CDS Catalog J/ApJ/705/1336/</a> file table1.dat. This is a service provided by NASA HEASARC .
SDSS MOVING OBJECT CATALOG V3.0
The Sloan Digital Sky Survey (SDSS) Moving Object Catalog 4th release lists astrometric and photometric data for moving objects detected in the SDSS. The catalog includes various identification parameters, SDSS astrometric measurements (five SDSS magnitudes and their errors), and orbital elements for previously cataloged asteroids. The data set also includes a list of the runs from which data are included, and filter response curves.
Spitzer Extragalactic First Look Survey SDSS Spectroscopic Catalog
The Extragalactic First Look Survey is composed of 4 square degrees of imaging with MIPS and IRAC centered at J1718+5930, with extensive ancillary data from ground-based optical and radio telescopes. As one of the first observations made with Spitzer after the completion of Science Verification at the end of 2003 November, the aim of this 67 hr survey was to characterize the extragalactic source populations observed with Spitzer down to sub-millijansky levels in the mid-infrared. This catalog presents the SDSS spectroscopic information from Papovich et al. (2006).
Australia Telescope Chandra Deep Field-South and SDSS Stripe 82 20-GHz Sources
This table contains a source catalog, one of the first results from a deep, blind radio survey carried out at 20 GHz with the Australia Telescope Compact Array, with follow-up observations at 5.5, 9 and 18 GHz. The Australia Telescope 20GHz (AT20G) deep pilot survey covers a total area of 5 deg<sup>2</sup> in the Chandra Deep Field South and in Stripe 82 of the Sloan Digital Sky Survey. The authors estimate the survey to be 90% complete above 2.5 mJy. Of the 85 sources detected, 55% have steep spectra (spectral index alpha<sub>1.4</sub><sup>20</sup> < -0.5) and 45% have flat or inverted spectra (alpha<sub>1.4</sub><sup>20</sup> >= -0.5). The steep-spectrum sources tend to have single power-law spectra between 1.4 and 18 GHz, while the spectral indices of the flat- or inverted-spectrum sources tend to steepen with frequency. Among the 18 inverted-spectrum (alpha<sub>1.4</sub><sup>20</sup> >= 0.0) sources, 10 have clearly defined peaks in their spectra with alpha<sub>1.4</sub><sup>5.5</sup> > 0.15 and alpha<sub>9</sub><sup>18</sup> < -0.15. On a 3-yr time-scale, at least 10 sources varied by more than 15 percent at 20 GHz, showing that variability is still common at the low flux densities probed by the AT20G-Deep Pilot (AT20GDP) survey. The AT20G-Deep Pilot survey was carried out with he ATCA in 2009 July, shortly after the telescope was provided with a new wide-bandwidth correlator, the CABB. As a result of this upgrade to the telescope, the observing bandwidth was increased by a factor of 16, from 2x128 to 2x2048 MHz, in all bands (ranging from 1.1 to 105 GHz), greatly increasing the sensitivity of continuum observations. These observations were made in continuum mode using two 2048-MHz CABB bands centered at 19 and 21 GHz, with each 2048-MHz band divided into 2048 1-MHz channels. All four Stokes parameters were measured. This table was created by the HEASARC in August 2015 based on the union of <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/MNRAS/439/1212">CDS Catalog J/MNRAS/439/1212</a> files table2.dat (the 50 sources in the 3-hr field) and table3.dat (the 35 sources in the 21-hr field). This is a service provided by NASA HEASARC .
ROSAT All-Sky Survey and SDSS DR5 Sample of X-Ray Emitting AGN
This table contains further results of a program aimed at yielding ~ 10<sup>4</sup> fully characterized optical identifications of ROSAT X-ray sources. The program employs X-ray data from the ROSAT All Sky Survey (RASS) and both optical imaging and spectroscopic data from the Sloan Digital Sky Survey (SDSS). RASS/SDSS data from 5740 deg<sup>2</sup> of sky spectroscopically covered in SDSS Data Release 5 (DR5) provide an expanded catalog of 7000 confirmed quasars and other active galactic nuclei (AGN) that are probable RASS identifications. Again, in this expanded catalog the identifications as X-ray sources are statistically secure, with only a few percent of the SDSS AGNs likely to be randomly superposed on unrelated RASS X-ray sources. Most identifications continue to be quasars and Seyfert 1 galaxies with 15 < m < 21 and 0.01 < z < 4, but the total sample size has grown to include very substantial numbers of even quite rare AGN, e.g., it now includes several hundreds of candidate X-ray-emitting BL Lac objects and narrow-line Seyfert 1 galaxies. In addition to exploring rare subpopulations, such a large total sample may be useful when considering correlations between the X-ray and the optical and may also serve as a resource list from which to select the ``best'' object (e.g., the X-ray-brightest AGN of a certain subclass at a preferred redshift or luminosity) for follow-up X-ray spectral or alternate detailed studies. Much more information on the SDSS is available at the project's web site at <a href="http://www.sdss.org/">http://www.sdss.org/</a>. This table was created by the HEASARC in February 2007 based on the combination of the electronic versions of tables 1 through 6 from the above reference which were obtained from the electronic AJ website. It replaces a previous version containing the results presented by Anderson et al. (2003, AJ, 126, 2209) which were based on a cross-correlation of the RASS with optical data from very early on in the SDSS program, e.g., extending back to the 'Early Data Release' before SDSS photometric calibrations were complete. This is a service provided by NASA HEASARC .
GALEX/SDSS Quasar Catalog
This table contains the result of an analysis of the broad-band UV and optical properties of z ~< 3.4 quasars matched in the Galaxy Evolution Explorer (GALEX) General Data Release 1 (GR1) and the Sloan Digital Sky Survey (SDSS) Data Release 3 (DR3). Of the 6371 SDSS DR3 quasars covered by 204 GALEX GR1 tiles and listed in this table, 5380 (84%) have near-UV detections, while 3034 (48%) have both near-UV and far-UV detections using a matching radius of 7 arcseconds. Most of the DR3 sample quasars are detected in the near-UV until z ~ 1.7, with the near-UV detection fraction dropping to ~50% by z ~ 2. Statistical tests performed on the distributions of non-detections indicate that the optically selected quasars missed in the UV tend to be optically faint or at high redshift. The GALEX positions are shown to be consistent with the SDSS astrometry to within an rms scatter of 0.6 - 0.7 arcsecs in each coordinate, and the empirically determined photometric errors from multi-epoch GALEX observations significantly exceed the Poissonian errors quoted in the GR1 object catalogs. The UV-detected quasars are well separated from stars in UV-optical color-color space, with the UV-optical relative colors suggesting a marginally detected population of reddened objects due to absorption along the line of sight or dust associated with the quasar. The resulting spectral energy distributions (SEDs) cover ~350 - 9000 Angstroms (rest frame), where the overall median SED peaks near the Lyman-Alpha emission line, as found in other UV quasar studies. The large sample size allows the authors to construct median SEDs in small bins of redshift and luminosity, and they find that the median SED becomes harder (bluer) at UV wavelengths for quasars with lower continuum luminosity. The detected UV-optical flux as a function of redshift is qualitatively consistent with attenuation by intervening Lyman-absorbing clouds. This table was created by the HEASARC in October 2009 based on the electronic version of Table 2 from the reference paper which was obtained from the CDS (their catalog J/AJ/133/1780 file table2.dat). This is a service provided by NASA HEASARC .
2XMMi/SDSS Galaxy Cluster Survey Extension
This table contains results from the analysis of a sample of 383 X-ray selected galaxy groups and clusters with spectroscopic redshift measurements (up to z ~ 0.79) from the 2XMMi/SDSS Galaxy Cluster Survey. The X-ray cluster candidates were selected as serendipitously detected sources from the 2XMMi-DR3 catalog that were located in the footprint of the Sloan Digital Sky Survey (SDSS-DR7). The cluster galaxies with available spectroscopic redshifts were selected from the SDSS-DR10. The authors developed an algorithm for identifying the cluster candidates that are associated with spectroscopically targeted luminous red galaxies and for constraining the cluster spectroscopic redshift. A cross-correlation of the constructed cluster sample with published optically selected cluster catalogs yielded 264 systems with available redshifts. The present redshift measurements (presented in reference paper III) are consistent with the published values. The current cluster sample extends the optically confirmed cluster sample from the authors' cluster survey by 67 objects. Moreover, it provides spectroscopic confirmation for 78 clusters among their published cluster sample, which previously had only photometric redshifts. Of the new cluster sample that comprises 67 systems, 55 objects are newly X-ray discovered clusters and 52 systems are sources newly discovered as galaxy clusters in optical and X-ray wavelengths. Based on the measured redshifts and the fluxes given in the 2XMMi-DR3 catalogue, the authors have estimated the X-ray luminosities and masses of the cluster sample. This table contains 145 entries, 67 of which are new (as of Paper III) optically confirmed clusters (marked by values of ref_source = 'Paper III') and 78 of which are clusters from Paper II which have now been spectroscopically confirmed (marked by values of ref_source = 'Paper II'). The tabular information on the 530 clusters that was presented in Paper II of this set of papers is available as the HEASARC <a href="/W3Browse/xmm-newton/xmmsdssgcs.html">XMMSDSSGCS table</a>). The following parameters were obtained from the current optical-band cluster detection algorithm: sdss_dr10_bcg_id, sdss_dr10_bcg_ra, sdss_dr10_bcg_dec, bcg_rmag, redshift, num_spect_members, phot_redshift, num_phot_members, and spatial_offset. This table was created by the HEASARC in July 2014 based on <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/A+A/564/A54">CDS catalog J/A+A/564/A54</a> file table1.dat. This is a service provided by NASA HEASARC .
SDSS ConeSearch
All MAST catalog holdings are available via a ConeSearch endpoint. The Sloan Digital Sky Survey (SDSS) Data Release 12 (SDSS DR12) contains all SDSS observations through July 2014. The STScI mirror is available here.More information on SDSS and this data release are available at http://www.sdss.org/dr12/.All available missions are listed at http://archive.stsci.edu/vo/mast_services.html.
VLA 6-GHz Observations of Low-Redshift SDSS QSOs
This table contains results from 6-GHz Jansky Very Large Array (JVLA) observations covering a volume-limited sample of 178 low-redshift (0.2 < z <0.3) optically selected quasi-stellar objects (QSOs). These 176 radio detections fall into two clear categories: (1) about 20% are radio-loud QSOs (RLQs) with spectral luminosities of L<sub>6</sub> >~ 10<sup>23.2</sup> W/Hz that are primarily generated in the active galactic nucleus (AGN) responsible for the excess optical luminosity that defines a bona fide QSO; and (2) the remaining 80% that are radio-quiet QSOs (RQQs) that have 10<sup>21</sup> <~ L<sub>6</sub> <~ 10<sup>23.2</sup> W/Hz and radio sizes <~ 10 kpc, and the authors suggest that the bulk of their radio emission is powered by star formation in their host galaxies. "Radio-silent" QSOs (L_6_<~ 10<sup>21</sup> W/Hz) are rare, so most RQQ host galaxies form stars faster than the Milky Way; they are not "red and dead" ellipticals. Earlier radio observations did not have the luminosity sensitivity of L<sub>6</sub> <~ 10<sup>21</sup> W/Hz that is needed to distinguish between such RLQs and RQQs. Strong, generally double-sided radio emission spanning >> 10 kpc was found to be associated with 13 of the 18 RLQ cores with peak flux densities of S<sub>p</sub> > 5 mJy/beam (log(L) >~ 24). The radio luminosity function of optically selected QSOs and the extended radio emission associated with RLQs are both inconsistent with simple "unified" models that invoke relativistic beaming from randomly oriented QSOs to explain the difference between RLQs and RQQs. Some intrinsic property of the AGN or their host galaxies must also determine whether or not a QSO appears radio-loud. The authors have reprocessed the VLA observations of a sample of SDSS QSOs discussed in Kimball et al. (2011, ApJ, 739, L29). These were obtained using the VLA C configuration with a central frequency of 6 GHz and a bandwidth of 2 GHz in each of the two circular polarizations: with natural weighting the synthesized beam width was 3.5 arcseconds FWHM. The authors generated a catalog of radio sources associated with each QSO. They detected radio emission at 6 GHz from all but two of the 178 color-selected SDSS QSOs contained in this volume-limited sample of QSOs more luminous than M<sub>i</sub> = -23 and with redshifts 0.2 < z < 0.3. All calculations in the reference paper assume a flat LambdaCDM cosmology with H<sub>0</sub> = 70 km s<sup>-1</sup> Mpc<sup>-1</sup> and Omega<sub>Lambda</sub> = 0.7. Spectral luminosities are specified by their source-frame frequencies, flux densities are specified in the observer's frame, and a mean spectral index of alpha = d(log S)/d(log nu) = -0.7 is used to make frequency conversions This table was created by the HEASARC in April 2017 based upon the <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/ApJ/831/168">CDS Catalog J/ApJ/831/168</a> file table1.dat. This is a service provided by NASA HEASARC .
SDSS-IV/SPIDERS XMM-Based X-Ray Point Source Spectroscopic Catalog
This catalog aims to provide a detailed description of the SPectroscopic IDentification of ERosita Sources (SPIDERS) survey, an SDSS-IV program aimed at obtaining spectroscopic classification and redshift measurements for complete samples of sufficiently bright X-ray sources. The authors describe the SPIDERS X-Ray Point Source Spectroscopic Catalog, considering its store of 11,092 observed spectra drawn from a parent sample of 14,759 ROSAT and XMM sources over an area of 5,129 deg<sup>2</sup> covered in SDSS-IV by the eBOSS survey. This catalog presents the SPIDERS XMM subsample of 3,196 sources which were drawn from the XMM Slew Survey source catalog, version 2 (XMMSL2), provided by the HEASARC in <a href="/W3Browse/xmm-newton/xmmslewful.html">XMMSLEWFUL</a>. The accompanying <a href="/W3Browse/rosat/spidersros.html">SPIDERSROS</a> table contains the 21,288 sources drawn from the Second ROSAT All-Sky Survey (2RXS) Source Catalog, available from the HEASARC as <a href="/W3Browse/rosat/rass2rxs.html">RASS2RXS</a>. This program represents the largest systematic spectroscopic observation of an X-ray selected sample. A total of 10,970 (98.9%) of the observed objects are classified and 10,849 (97.8%) have secure redshifts. The majority of the spectra (10,070 objects) are active galactic nuclei (AGN), 522 are cluster galaxies, and 294 are stars. The SDSS-IV/BOSS spectrographic observations are taken between 2014 and 2019. This table was created by the HEASARC in May 2020 based upon the <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/A+A/636/A97">CDS Catalog J/A+A/636/A97</a> file vcxmmsl2.dat. This is a service provided by NASA HEASARC .
SDSS MOVING OBJECT CATALOG
The Sloan Digital Sky Survey (SDSS) Moving Object Catalog 4th release lists astrometric and photometric data for moving objects detected in the SDSS. The catalog includes various identification parameters, SDSS astrometric measurements (five SDSS magnitudes and their errors), and orbital elements for previously cataloged asteroids. The data set also includes a list of the runs from which data are included, and filter response curves.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.