Publications based on DECam data (2018)

Publications based on DECam data (2018) [1]

Community papers:

Bhandari et al. (2018), MNRAS, 475, 1427: The SUrvey for Pulsars and Extragalactic Radio Bursts - II. New FRB discoveries and their follow-up [2]
Butler et al (2018), A&A, 620, A3: The XXL Survey. XVIII. ATCA 2.1 GHz radio source catalogue and source counts for the XXL-South field [3]
Butler et al (2018), A&A, 620, A16: The XXL Survey. XXXI. Classification and host galaxy properties of 2.1 GHz ATCA XXL-S radio sources [4]
Carballo-Bello et al. (2018), MNRAS, 474, 683: Tails and streams around the Galactic globular clusters NGC 1851, NGC 1904, NGC 2298 and NGC 2808 [5]
Chandler et al. (2018), PASP, 130, 114502: SAFARI: Searching Asteroids for Activity Revealing Indicators [6]
Chiappetti et al. (2018), Astronomy & Astrophyscis: The XXL Survey: XXVII. The 3XLSS point source catalogue [7]
Choi et al. (2018), ApJ, 869, 125: SMASHing the LMC: Mapping a Ring-like Stellar Overdensity in the LMC Disk [8]
Choi et al (2018), Apj, 866, 90: SMASHing the LMC: A Tidally Induced Warp in the Outer LMC and a Large-scale Reddening Map [9]
Circuendez et al. (2018), A&A, 609, 53: Tracing the stellar component of low surface brightness Milky Way dwarf galaxies to their outskirts. I. Sextans [10]
Circuendez & Battaglia, MNRAS, 480, 251: Appearances can be deceiving: clear signs of accretion in the seemingly ordinary Sextans dSph [11]
Cowperthwaite et al. (2018), ApJ, 858, 18: An Empirical Study of Contamination in Deep, Rapid, and Wide-field Optical Follow-up of Gravitational Wave Events [12]
Dhawan et al. (2018), MNRAS 480, 1445: iPTF16abc and the population of Type Ia supernovae: comparing the photospheric, transitional, and nebular phases [13]
Eigenthaler et al. (2018), ApJ, 855, 142: The Next Generation Fornax Survey (NGFS). II. The Central Dwarf Galaxy Population [14]
Favole et al. (2018), MNRAS, 480, 1415: The mass-size relation of luminous red galaxies from BOSS and DECaLS [15]
Forster et al. (2018), Nature Astronomy, in press: The delay of shock breakout due to circumstellar material evident in most type II supernovae [16]
Gao et al. (2018), ApJ, 869, 15: Mass-Metallicity Relation and Fundamental Metallicity Relation of Metal-poor Star-forming Galaxies at 0.6 < Z < 0.9 from the eBOSS Survey [17]
Garling et al. (2018), ApJ, 852, 44: Mapping the Tidal Destruction of the Hercules Dwarf: A Wide-field DECam Imaging Search for RR Lyrae Stars [18]
Gonzalez et al. (2018), Astronomy & Computing, 25, 103: Galaxy detection and identification using deep learning and data augmentation [19]
Holman et al. (2018), ApJ, 855, L6: A Dwarf Planet Class Object in the 21:5 Resonance with Neptune [20]
Hood et al. (2018), ApJ, 857, 144: The Origin of Faint Tidal Features around Galaxies in the RESOLVE Survey [21]
Jethwa et al. (2018), MNRAS, 480, 5342: Discovery of a thin stellar stream in the SLAMS survey [22]
Kerzendorf et al. (2018), MNRAS, 479, 192: A search for a surviving companion in SN 1006 [23]
Koposov et al. (2018), MNRAS, 479, 5343: Snake in the Clouds: a new nearby dwarf galaxy in the Magellanic bridge [24]
Kuzma et al. (2018), MNRAS, 473, 2881: The outer envelopes of globular clusters. II. NGC 1851, NGC 5824 and NGC 1261 [25]
Lan et al (2018), ApJ, 866, 36: The Circumgalactic Medium of eBOSS Emission Line Galaxies: Signatures of Galactic Outflows in Gas Distribution and Kinematics [26]
Li et al. (2018), ApJ, 861, 6: The Ensemble Photometric Variability of Over 10^5 Quasars in the Dark Energy Camera Legacy Survey and the Sloan Digital Sky Survey [27]
Mackey et al. (2018), ApJL, 858, L21: Substructures and Tidal Distortions in the Magellanic Stellar Periphery [28]
Martinez-Palomera (2018), AJ, 156, 186: The High Cadence Transit Survey (HiTS): Compilation and Characterization of Light-curve Catalogs [29]
Medina et al. (2018), ApJ, 855, 43: Discovery of Distant RR Lyrae Stars in the Milky Way Using DECam [30]
Minniti et al. (2018), ApJ, 866, 12: Confirmation of a New Metal-poor Globular Cluster in the Galactic Bulge [31]
Muñoz et al. (2018), ApJ, 860, 65: A MegaCam Survey of Outer Halo Satellites. I. Description of the Survey [32]
Muñoz et al. (2018), ApJ, 860, 66: A MegaCam Survey of Outer Halo Satellites. III. Photometric and Structural Parameters [33]
Nidever et al. (2018), AJ, 156, 131: First Data Release of the All-sky NOAO Source Catalog [34]
Ordenes-Briceño et al. (2018), ApJ, 859, 52: The Next Generation Fornax Survey (NGFS). III. Revealing the Spatial Substructure of the Dwarf Galaxy Population Inside Half of Fornax's Virial Radius [35]
Ordenes-Briceño et al. (2018), ApJ, 860, 4: The Next Generation Fornax Survey (NGFS). IV. Mass and Age Bimodality of Nuclear Clusters in the Fornax Core Region [36]
Peña et al. (2018), AJ, 155, 135: Asteroids in the High Cadence Transient Survey [37]
Piatti et al. (2018), MNRAS, 473, 105: Star cluster formation history along the minor axis of the Large Magellanic Cloud [38]
Piatti & Mackey (2018), MNRAS, 478, 2164: Evidence of differential tidal effects in the old globular cluster population of the Large Magellanic Cloud [39]
Plionis et al. (2018), A&A, 620, A17: The XXL Survey. XXXII. Spatial clustering of the XXL-S AGN [40]
Pota et al. (2018), MNRAS, 481, 1744: The Fornax Cluster VLT Spectroscopic Survey - I. VIMOS spectroscopy of compact stellar systems in the Fornax core region [41]
Ramirez-Moreta et al. (2018), A&A, 619, A163: Unveiling the environment and faint features of the isolated galaxy CIG 96 with deep optical and HI observations [42]
Ross et al. (2018), MNRAS, in press: A new physical interpretation of optical and infrared variability in quasars [43]
Schlafly et al. (2018), ApJSS, 234, 39: The DECam Plane Survey: Optical Photometry of Two Billion Objects in the Southern Galactic Plane [44]
Smith et al. (2018), MNRAS, 480, 1466: Light echoes from the plateau in Eta Carinae's Great Eruption reveal a two-stage shock-powered event [45]
Stevans et al. (2018), ApJ, 863, 63: Bridging Star-forming Galaxy and AGN Ultraviolet Luminosity Functions at z = 4 with the SHELA Wide-field Survey [46]
Taylor et al (2018), ApJL, 867, L15: A Collection of New Dwarf Galaxies in NGC 5128’s Western Halo [47]
Torrealba et al. (2018), MNRAS, 475, 5085: Discovery of two neighbouring satellites in the Carina constellation with MagLiteS [48]

Dark Energy Survey Collaboration papers:

Abbott et al. (2018), MNRAS, in press: Dark Energy Survey Year 1 Results: A Precise H0 Estimate from DES Y1, BAO, and D/H Data [49]
Abbott et al. (2018), ApJS, 239, 18: The Dark Energy Survey: Data Release 1 [50]
Abbott et al. (2018), Physical Review D, 98, 043526: Dark Energy Survey year 1 results: Cosmological constraints from galaxy clustering and weak lensing [51]
Agnello et al. (2018), MNRAS, 479, 4345: DES meets Gaia: discovery of strongly lensed quasars from a multiplet search [52]
Anguita et al. (2018), MNRAS, in press: The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign. II. New quasar lenses from double component fitting [53]
Avila et al. (2018), MNRAS, 479, 94: Dark Energy Survey Year-1 results: galaxy mock catalogues for BAO [54]
Baxter et al. (2018), MNRAS, 476, 2674: A measurement of CMB cluster lensing with SPT and DES year 1 data [55]
Becker et al. (2018), AJ, 156, 81: Discovery and Dynamical Analysis of an Extreme Trans-Neptunian Object with a High Orbital Inclination [56]
Bernstein et al. (2018), PASP, 130, 054501: Photometric Characterization of the Dark Energy Camera [57]
Burke et al. (2018), AJ, 155, 41: Forward Global Photometric Calibration of the Dark Energy Survey [58]
Cawthon et al. (2018), MNRAS, 481, 2427: Dark Energy Survey Year 1 Results: calibration of redMaGiC redshift distributions in DES and SDSS from cross-correlations [59]
Chan et al. (2018), MNRAS, 480, 3031: BAO from angular clustering: optimization and mitigation of theoretical systematics [60]
Chang et al. (2018), MNRAS, 475, 3165: Dark Energy Survey Year 1 results: curved-sky weak lensing mass map [61]
Chang et al. (2018), ApJ, 864, 83: The Splashback Feature around DES Galaxy Clusters: Galaxy Density and Weak Lensing Profi [62]les
Chiu et al. (2018), MNRAS, 478, 3072: Baryon content in a sample of 91 galaxy clusters selected by the South Pole Telescope at 0.2 <z < 1.25 [63]
Courbin et al. (2018), A&A, 609, 71: COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses. XVI. Time delays for the quadruply imaged quasar DES J0408-5354 with high-cadence photometric monitoring [64]
Davis et al. (2018), MNRAS, 477, 2196: Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data [65]
Drlica-Wagner et al. (2108), ApJS, 235, 33: Dark Energy Survey Year 1 Results: The Photometric Data Set for Cosmology [66]
Elvin-Poole et al. (2018), Physical Review D, 98, 042006: Dark Energy Survey year 1 results: Galaxy clustering for combined probes [67]
Erkal et al. (2018), MNRAS, 481, 3148: Modelling the Tucana III stream - a close passage with the LMC [68]
Fausti Neto et al. (2018), Astronomy & Computing, 24, 52: DES science portal: Creating science-ready catalogs [69]
Friedrich et al. (2018), Physical Review D, 98, 023508: Density split statistics: Joint model of counts and lensing in cells [70]
Garcia-Fernandez et al. (2018), MNRAS, 476, 1071: Weak lensing magnification in the Dark Energy Survey Science Verification data [71]
Gatti et al. (2018), MNRAS, 477, 1664: Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization [72]
Gruen et al. (2018), Physical Review D, 98, 023507: Density split statistics: Cosmological constraints from counts and lensing in cells in DES Y1 and SDSS data [73]
Gschwend et al. (2018), Astronomy & Computing, 25, 58: DES science portal: Computing photometric redshifts [74]
Hoyle et al. (2108), MNRAS, 478, 592: Dark Energy Survey Year 1 Results: redshift distributions of the weak-lensing source galaxies [75]
Jeffrey et al. (2018), MNRAS, 479, 2871: Improving weak lensing mass map reconstructions using Gaussian and sparsity priors: application to DES SV [76]
Klein et al. (2018), MNRAS, 474, 3324: A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets [77]
Khain et al. (2018), AJ, 156, 273: Dynamical Analysis of Three Distant Trans-Neptunian Objects with Similar Orbits [78]
Li et al. (2018), ApJ, 866, 22: The First Tidally Disrupted Ultra-faint Dwarf Galaxy?: A Spectroscopic Analysis of the Tucana III Stream [79]
Luque et al. (2018), MNRAS, 478, 2006: Deep SOAR follow-up photometry of two Milky Way outer-halo companions discovered with Dark Energy Survey [80]
MacCrann et al. (2018), MNRAS, in press: DES Y1 Results: Validating cosmological parameter estimation using simulated Dark Energy Surveys [81]
Morganson et al. (2018), PASP, 130, 074501: The Dark Energy Survey Image Processing Pipeline [82]
Mudd et al. (2018), ApJ, 862, 123: Quasar Accretion Disk Sizes from Continuum Reverberation Mapping from the Dark Energy Survey [83]
Nagasawa et al. (2018), ApJ, 852, 99: Chemical Abundance Analysis of Three alpha-poor, Metal-poor Stars in the Ultrafaint Dwarf Galaxy Horologium I [84]
Prat et al. (2018), MNRAS, 473, 1667: Galaxy bias from galaxy-galaxy lensing in the DES science verification data [85]
Prat et al. (2018), Physical Review D, 98, 042005: Dark Energy Survey year 1 results: Galaxy-galaxy lensing [86]
Pursiainen et al. (2018), MNRAS, 481, 849: Rapidly evolving transients in the Dark Energy Survey [87]
Rumbaugh et al. (2018), MNRAS, 473, 1667: Extreme Variability Quasars from the Sloan Digital Sky Survey and the Dark Energy Survey [88]
Samuroff et al. (2018), MNRAS, 475, 4524: Dark Energy Survey Year 1 results: the impact of galaxy neighbours on weak lensing cosmology with IM3SHAPE [89]
Sevilla-Noarbe et al. (2018), MNRAS, 481, 5451: Star-galaxy classification in the Dark Energy Survey Y1 data set [90]
Shipp et al. (2018), ApJ, 862, 114: Stellar Streams Discovered in the Dark Energy Survey [91]
Smith et al. (2018), ApJ, 854, 37: Studying the Ultraviolet Spectrum of the First Spectroscopically Confirmed Supernova at Redshift Two [92]
Tarsitano et al. (2018), MNRAS, 481, 2018: A catalogue of Structural And Morphological Measurements for DES Y1 [93]
Treu et al. (2018), MNRAS, 481, 1041: The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign - I. Overview and classification of candidates selected by two techniques [94]
Troxel et al. (2018), Physical Review D, 98, 043528: Dark Energy Survey Year 1 results: Cosmological constraints from cosmic shear [95]
Troxel et al. (2018), MNRAS, 479, 4998: Survey geometry and the internal consistency of recent cosmic shear measurements [96]
Wethers et al. (2018), MNRAS, 475, 3682: UV-luminous, star-forming hosts of z~2 reddened quasars in the Dark Energy Survey [97]
Zuntz et al. (2019), MNRAS, 481, 1149: Dark Energy Survey Year 1 results: weak lensing shape catalogues [98]

Links
[1] http://www.ctio.noao.edu/noao/node/16387
[2] http://adsabs.harvard.edu/abs/2018MNRAS.475.1427B
[3] https://ui.adsabs.harvard.edu//#abs/2018A&A...620A...3B/abstract
[4] https://ui.adsabs.harvard.edu//#abs/2018A&A...620A..16B/abstract
[5] http://adsabs.harvard.edu/abs/2018MNRAS.474..683C
[6] http://adsabs.harvard.edu/abs/2018PASP..130k4502C
[7] https://ui.adsabs.harvard.edu/#abs/2018A&A...620A..12C
[8] https://ui.adsabs.harvard.edu/#abs/2018ApJ...869..125C/abstract
[9] https://ui.adsabs.harvard.edu//#abs/2018ApJ...866...90C/abstract
[10] http://adsabs.harvard.edu/abs/2018A%26A...609A..53C
[11] http://adsabs.harvard.edu/abs/2018MNRAS.480..251C
[12] http://adsabs.harvard.edu/abs/2018ApJ...858...18C
[13] http://adsabs.harvard.edu/abs/2018MNRAS.480.1445D
[14] http://adsabs.harvard.edu/abs/2018ApJ...855..142E
[15] http://adsabs.harvard.edu/abs/2018MNRAS.480.1415F
[16] https://ui.adsabs.harvard.edu//#abs/2018NatAs.tmp..122F/abstract
[17] https://ui.adsabs.harvard.edu//#abs/2018ApJ...869...15G
[18] http://adsabs.harvard.edu/abs/2018ApJ...852...44G
[19] http://adsabs.harvard.edu/abs/2018A%26C....25..103G
[20] http://adsabs.harvard.edu/abs/2018ApJ...855L...6H
[21] http://adsabs.harvard.edu/abs/2018ApJ...857..144H
[22] http://adsabs.harvard.edu/abs/2018MNRAS.480.5342J
[23] http://adsabs.harvard.edu/abs/2018MNRAS.479..192K
[24] http://adsabs.harvard.edu/abs/2018MNRAS.479.5343K
[25] http://adsabs.harvard.edu/abs/2018MNRAS.473.2881K
[26] https://ui.adsabs.harvard.edu/#abs/2018ApJ...866...36L
[27] http://adsabs.harvard.edu/abs/2018ApJ...861....6L
[28] http://adsabs.harvard.edu/abs/2018ApJ...858L..21M
[29] https://ui.adsabs.harvard.edu//#abs/2018AJ....156..186M/abstract
[30] http://adsabs.harvard.edu/abs/2018ApJ...855...43M
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[35] http://adsabs.harvard.edu/abs/2018ApJ...859...52O
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[40] https://ui.adsabs.harvard.edu/#abs/2018A&A...620A..17P
[41] https://ui.adsabs.harvard.edu/#abs/2018MNRAS.481.1744P
[42] https://ui.adsabs.harvard.edu/#abs/2018A&A...619A.163R
[43] http://adsabs.harvard.edu/doi/10.1093/mnras/sty2002
[44] http://adsabs.harvard.edu/abs/2018ApJS..234...39S
[45] http://adsabs.harvard.edu/abs/2018MNRAS.480.1466S
[46] http://adsabs.harvard.edu/abs/2018ApJ...863...63S
[47] https://ui.adsabs.harvard.edu//#abs/2018ApJ...867L..15T/abstract
[48] http://adsabs.harvard.edu/abs/2018MNRAS.475.5085T
[49] http://adsabs.harvard.edu/doi/10.1093/mnras/sty1939
[50] https://ui.adsabs.harvard.edu/#abs/2018ApJS..239...18A/abstract
[51] https://ui.adsabs.harvard.edu//#abs/2018PhRvD..98d3526A/abstract
[52] https://ui.adsabs.harvard.edu//#abs/2018MNRAS.479.4345A/abstract
[53] http://adsabs.harvard.edu/doi/10.1093/mnras/sty2172
[54] http://adsabs.harvard.edu/abs/2018MNRAS.479...94A
[55] http://adsabs.harvard.edu/abs/2018MNRAS.476.2674B
[56] http://adsabs.harvard.edu/abs/2018AJ....156...81B
[57] http://adsabs.harvard.edu/abs/2018PASP..130e4501B
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[59] https://ui.adsabs.harvard.edu//#abs/2018MNRAS.481.2427C/abstract
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[64] http://adsabs.harvard.edu/abs/2018A%26A...609A..71C
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[66] http://adsabs.harvard.edu/abs/2018ApJS..235...33D
[67] https://ui.adsabs.harvard.edu//#abs/2018PhRvD..98d2006E/abstract
[68] https://ui.adsabs.harvard.edu/#abs/2018MNRAS.481.3148E
[69] http://adsabs.harvard.edu/abs/2018A%26C....24...52F
[70] http://adsabs.harvard.edu/abs/2018PhRvD..98b3508F
[71] http://adsabs.harvard.edu/abs/2018MNRAS.476.1071G
[72] http://adsabs.harvard.edu/abs/2018MNRAS.477.1664G
[73] http://adsabs.harvard.edu/abs/2018PhRvD..98b3507G
[74] https://ui.adsabs.harvard.edu//#abs/2018A&C....25...58G/abstract
[75] http://adsabs.harvard.edu/abs/2018MNRAS.478..592H
[76] http://adsabs.harvard.edu/abs/2018MNRAS.479.2871J
[77] http://adsabs.harvard.edu/abs/2018MNRAS.474.3324K
[78] https://ui.adsabs.harvard.edu/#abs/2018AJ....156..273K/abstract
[79] https://ui.adsabs.harvard.edu/#abs/2018ApJ...866...22L
[80] http://adsabs.harvard.edu/abs/2018MNRAS.478.2006L
[81] http://adsabs.harvard.edu/doi/10.1093/mnras/sty1899
[82] http://adsabs.harvard.edu/abs/2018PASP..130g4501M
[83] http://adsabs.harvard.edu/abs/2018ApJ...862..123M
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[89] http://adsabs.harvard.edu/abs/2018MNRAS.475.4524S
[90] https://ui.adsabs.harvard.edu/#abs/2018MNRAS.481.5451S/abstract
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[94] https://ui.adsabs.harvard.edu//#abs/2018MNRAS.481.1041T/abstract
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[96] http://adsabs.harvard.edu/abs/2018MNRAS.479.4998T
[97] http://adsabs.harvard.edu/abs/2018MNRAS.475.3682W
[98] https://ui.adsabs.harvard.edu//#abs/2018MNRAS.481.1149Z/abstract