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8 results for “sky map”
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>
21 cm intensity mapping: a 900 - 1300 MHz full-sky simulation
<p>This HDF5 file stores the simulation used and described in <a href="http://dx.doi.org/10.1093/mnras/staa2854">Recovery of 21 cm intensity maps with sparse component separation</a> (<a href="https://arxiv.org/abs/2006.05996">arXiv:2006.05996</a>). It is a collection of intensity maps in units of mK, full-sky, in HEALPIX format with nside=256. There are 5 components: 1. 21cm cosmological signal, 2. galactic free-free diffuse emission, 3. galactic synchrotron diffuse emission, 4. extragalactic point sources and background and 5. instrumental polarization leakage. For each component, there are 400 maps, corresponding to 400 channels of 1 MHz from 900 to 1300 MHz. In <a href="https://doi.org/10.1093/mnras/staa2854">the main paper</a> the simulation is used to test the algorithm GMCA as a foreground removal method for 21cm intensity mapping. A practical example of how to use these data and apply GMCA on them is shown at this GitHub <a href="https://github.com/isab3lla/gmca4im">repository</a>.</p> <p>If you are using this dataset or the tools developed to work with it, please do not forget to cite the dataset itself as well as the relevant publication.</p>
Pretty Deep Maps: a detailed all-sky astronomical atlas
<p>The <em>Pretty Deep Maps</em> astronomical atlas is a large hyperlinked collection of charts and indices in PDF format covering the entire sky, in the main to a magnitude of 18, with star-dense sections at a lower magnitude, and selected regions to a deeper magnitude. The atlas is intended as a convenient, portable, deep visual representation of all-sky astronomical datasets, and can be used for tasks such as identification of objects in photographs and observation planning. The charts plot approximately 117k bright stars, 600 million field stars, 2.4 million galaxies, 277k variable stars, 110k multiple stars, 168k quasars, 8955 galaxy groups, 5250 galaxy clusters, 5004 dark nebulae, 2411 planetary nebulae, 1249 bright nebulae, 2167 open clusters, 159 reflection nebulae and 157 globular clusters. The celestial sphere is divided into 6787 charts, each covering 3 degrees of declination at a map scale of 11.74" per mm. Charts employ a gnomonic projection. The charts are accompanied by a set of sortable indices. The atlas can be used on any device with a PDF reader capable of supporting within- and cross-document links. </p> <p>The dataset is described in a detailed technical document (guide.pdf). <br> </p>
All-sky three-dimensional dust density and extinction Maps of the Milky Way out to 2.8 kpc
<p>Three-dimensional dust density maps are crucial for understanding the structure of the interstellar medium of the Milky Way and the processes that shape it. However, constructing these maps requires large datasets and the methods used to analyse them are computationally expensive and difficult to scale up. As a result it is has only recently become possible to map kiloparsec-scale regions of our Galaxy at parsec-scale grid sampling. We present all-sky three-dimensional dust density and extinction maps of the Milky Way out to 2.8~kpc in distance from the Sun using the fast and scalable Gaussian Process algorithm Dustribution. The sampling of the three-dimensional map is $l,b,d = 1^{\circ} \times1^{\circ} \times 1.7$~pc. The input extinction and distance catalogue contains 120 million stars with photometry and astrometry from Gaia DR2, 2MASS and AllWISE. This combines the strengths of optical and infrared data to probe deeper into the dusty regions of the Milky Way. We compare our maps with other published 3D dust maps. All maps quantitatively agree at the $0.001$~mag~pc$^{-1}$ scale with many qualitatively similar features, although each map also has its own features. We recover Galactic features previously identified in the literature. Moreover, we also see a large under-density that may correspond to an inter-arm or -spur gap towards the Galactic Centre.</p> <p> </p> <p>Here we provide the full dataset generated from Dustribution covering the full sky out to 2.8 kpc. We provide the 3D dust extinction and density files as well the l,b,d coordinate grid that the data is presented in. </p> <p> </p> <p>The data in each file is as follows:</p> <ul> <li>lbdGrid_l_bounds.pkl.npy: The boundaries of the grid cells of the merged map in l (degrees). Numpy array of size 881.</li> <li>lbdGrid_b_bounds.pkl.npy: The boundaries of the grid cells of the merged map in b (degrees). Numpy array of size 273.</li> <li>lbdGrid_d_bounds.pkl.npy: The boundaries of the grid cells of the merged map in d (pc). Numpy array of size 1644.</li> <li>Density_Median_lbd.pkl.npy: The median of 100 density samples of the merged map (mag pc^-1). Treat this as the estimate of the density. Numpy array of size (880, 272, 1644)</li> <li>Density_16P_lbd.pkl.npy: The 16th percentile of the density of the merged map (mag pc^-1). Treat median-16p as the estimate of the lower uncertainty on the density. Numpy array of size (880, 272, 1644)</li> <li>Density_84P_lbd.pkl.npy: The 84th percentile of the density of the merged map (mag pc^-1). Treat 84p-median as the estimate of the upper uncertainty on the density. Numpy array of size (880, 272, 1644) </li> <li>Ext_Median_lbd.pkl.npy: The median of the integral of 100 sample maps at each cell in the merged map (mag). Treat this as the estimate of the extinction in each cell. Numpy array of size (880, 272, 1644). </li> <li>Ext_16P_lbd.pkl.npy: The 16th percentile of the integral of 100 sample maps at each cell in the merged map (mag). Treat median-16p as the estimate of the lower uncertainty on the extinction in each cell. Numpy array of size (880, 272, 1644)</li> <li>Ext_84P_lbd.pkl.npy: The 84th percentile of the integral of 100 sample maps at each cell in the merged map (mag). Treat 84p-median as the estimate of the upper uncertainty on the extinction in each cell. Numpy array of size (880, 272, 1644)</li> <li>read_and_plot.ipynb: a short jupyter notebook demonstrating how to read in the data files, with some quick examples of plotting them.</li> </ul>
The Sloan Digital Sky Survey Reverberation Mapping Project: the XMM-Newton X-ray source catalog and multi-band counterparts
<p>The XMM-RM project was designed to provide X-ray coverage of the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) field. 41 XMM-Newton exposures, placed surrounding the Chandra AEGIS field, were taken, covering an area of 6.13 deg2 and reaching a nominal exposure depth of ∼ 15 ks. We present an X-ray catalog of 3553 sources detected in these data, using a PSF-fitting algorithm and a sample selection threshold that produces a ∼ 5% fraction of spurious sources. The Bayesian method “NWAY” was employed to identify counterparts of the X-ray sources from the optical Legacy and the IR unWISE catalogs, using a 2-dimensional unWISE magnitude-color prior created from optical/IR counterparts of Chandra X-ray sources. 932 of the XMM-RM sources are covered by SDSS spectroscopic observations. 89% of them are classified as AGN, and 71% of these AGN are in the SDSS-RM quasar catalog. Among the SDSS-RM quasars, 80% are detectable at the depth of the XMM observations. Forced X-ray photometry is performed at the positions of the undetected SDSS-RM quasars.</p>
Aquarius Celestial Sky Microwave Emission Map Ancillary Dataset V1.0
This datasets contains three maps of L-band (wavelength = 21 cm) brightness temperature of the celestial sky ("Galaxy") used in the processing of the NASA Aquarius instrument data. The maps report Sky brightness temperatures in Kelvin gridded on the Earth Centered Inertial (ECI) reference frame epoch J2000. They are sampled over 721 Declinations between -90 degrees and +90 degrees and 1441 Right Ascensions between 0 degrees and 360 degrees, all evenly spaced at 0.25 degrees intervals. The brightness temperatures are assumed temporally invariant and polarization has been neglected. They include microwave continuum and atomic hydrogen line (HI) emissions. The maps differ only in how the strong radio source Cassiopeia A has been included into the whole sky background surveys: 1/ TB_no_Cas_A does not include Cassiopeia A and reports only the whole Sky surveys. 2/ TB_Cas_A_1cell spread Cas A total flux homogeneously over 1 map grid cell (i.e. 9.8572E-6 sr). 3/ TB_Cas_A_beam spreads Cas A over surrounding grid cells using a convolution by a Gaussian beam with HPBW of 35 arcmin (equivalent to the instrument used for the Sky surveys). Cassiopeia A is a supernova remnant (SNR) in the constellation Cassiopeia and the brightest extra-solar radio source in the sky at frequencies above 1.
ULY JUPITER INTERSTELLAR NEUTRAL-GAS EXPERIMENT SKY MAPS
Ulysses interstellar neutral gas (GAS) experiment sky maps of the count rates of interstellar helium particles (in the NG-mode) or from celestial UV-intensities (UV-mode).
ULY JUPITER INTERSTELLAR NEUTRAL-GAS EXPERIMENT SKY MAPS
not applicable
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