Publications based on DECam data (2019)

Publications based on DECam data (2019) [1]

Community Papers

Andreoni et al. (2019), ApJL, 881, L16: GROWTH on S190510g: DECam Observation Planning and Follow-up of a Distant Binary Neutron Star Merger Candidate [2]
Bait et al. (2019), MNRAS, 485, 428: Outlying Halpha emitters in SDSS IV MaNGA [3]
Barba et al. (2019), ApJL, 870, L24: A Sequoia in the Garden: FSR 1758—Dwarf Galaxy or Giant Globular Cluster? [4]
Bell et al. (2019), MNRAS, 489, 3200: The intrinsic reddening of the Magellanic Clouds as traced by background galaxies - I. The bar and outskirts of the Small Magellanic Cloud [5]
Belladita et al. (2019), A&A, 629, A68: An extremely X-ray weak blazar at z = 5 [6]
Bettinelli et al. (2019), MNRAS, 487, 5862: The star formation history of the Sculptor dwarf spheroidal galaxy [7]
Bonaca et al. (2019), ApJL, 881, L37: Multiple Components of the Jhelum Stellar Stream [8]
Burke et al. (2019), MNRAS, 490, 3952: Deblending and classifying astronomical sources with Mask R-CNN deep learning [9]
Carrasco-Davis et al. (2019), PASP, 131, 108006: Deep Learning for Image Sequence Classification of Astronomical Events [10]
Chen et al. (2019), MNRAS, 484, 431: Characterizing circumgalactic gas around massive ellipticals at z ~ 0.4 - III. The galactic environment of a chemically pristine Lyman limit absorber [11]
Chang et al. (2019), MNRAS, 482, 3696: A unified analysis of four cosmic shear surveys [12]
Costanzi et al. (2019), MNRAS, 482, 490: Modelling projection effects in optically selected cluster catalogues [13]
Dame et al. (2019), MNRAS, 490, 1066: The DECam Minute Cadence Survey II: 49 Variables but No Planetary Transits of a White Dwarf [14]
Dey et al. (2019), AJ, 157, 168: Overview of the DESI Legacy Imaging Surveys [15]
Dimitriadis et al. (2019), ApJL, 870, L1: K2 Observations of SN 2018oh Reveal a Two-component Rising Light Curve for a Type Ia Supernova [16]
Dobie et al. ApJL, 887, L13: An ASKAP Search for a Radio Counterpart to the First High-significance Neutron Star-Black Hole Merger LIGO/Virgo S190814bv [17]
Dzudzar et al. (2019), MNRAS, 483, 5409: The neutral hydrogen properties of galaxies in gas-rich groups [18]
Dzudzar et al. (2019), MNRAS, 490, L6: Group pre-processing versus cluster ram-pressure stripping: the case of ESO156-G029 [19]
Fan et al. (2019), ApJ, 887, 74: ALMA Reveals a Gas-rich, Maximum Starburst in the Hyperluminous, Dust-obscured Quasar W0533-3401 at z ~ 2.9 [20]
For et al. (2019), MNRAS, 489, 5723: WALLABY early science - V. ASKAP H I imaging of the Lyon Group of Galaxies 351 [21]
Goldstein et al. (2019), ApJL, 881, L7: GROWTH on S190426c: Real-time Search for a Counterpart to the Probable Neutron Star-Black Hole Merger using an Automated Difference Imaging Pipeline for DECam [22]
Heinze et al. (2019), AJ, 158, 232: The Flux Distribution and Sky Density of 25th Magnitude Main Belt Asteroids [23]
Hosseinzadeh et al. (2019), ApJL, 880, L4: Follow-up of the Neutron Star Bearing Gravitational-wave Candidate Events S190425z and S190426c with MMT and SOAR [24]
Hu et al. (2019), ApJ, 886, 90: The Ly alpha Luminosity Function and Cosmic Reionization at z ~ 7.0: A Tale of Two LAGER Fields [25]
Jewitt et al. (2019), AJ, 157, 54: Active Asteroid P/2017 S5 (ATLAS) [26]
Jones et al. (2019), A&A, 632, A78: Evolution of compact groups from intermediate to final stages. A case study of the H I content of HCG 16 [27]
Joshi et al. (2019), ApJ, 887, 266: X-shaped Radio Galaxies: Optical Properties, Large-scale Environment, and Relationship to Radio Structure [28]
Kleiner et al. (2019), MNRAS, 488, 5352: WALLABY Early Science - IV. ASKAP H I imaging of the nearby galaxy IC 5201 [29]
Koposov et al. (2019), MNRAS, 485, 4726: Piercing the Milky Way: an all-sky view of the Orphan Stream [30]
Leistedt et al. (2019), ApJ, 881, 80: Hierarchical Modeling and Statistical Calibration for Photometric Redshifts [31]
Li et al. (2019), ApJ, 870, 12: Photometric and Spectroscopic Properties of Type Ia Supernova 2018oh with Early Excess Emission from the Kepler 2 Observations [32]
Li et al. (2019), MNRAS, 490, 3508: The southern stellar stream spectroscopic survey (S5): Overview, target selection, data reduction, validation, and early science [33]
Marubini et al. (2019), MNRAS, 489, 3403: A new sample of southern radio galaxies: host-galaxy masses and star-formation rates [34]
Mau et al. (2019), ApJ, 875, 154: A Faint Halo Star Cluster Discovered in the Blanco Imaging of the Southern Sky Survey [35]
Moolekamp et al. (2019), MNRAS, 484, 5049: DECam survey for low-mass stars and substellar objects in the UCL and LCC subgroups of the Sco-Cen OB Association (SCOCENSUS) [36]
Muller et al. (2019), A&A, 629, A18: The dwarf galaxy satellite system of Centaurus A [37]
Nidever et al. (2019), ApJ, 874, 118: Exploring the Very Extended Low-surface-brightness Stellar Populations of the Large Magellanic Cloud with SMASH [38]
Price-Whelan et al. (2019), ApJ, 887, 19: Discovery of a Disrupting Open Cluster Far into the Milky Way Halo: A Recent Star Formation Event in the Leading Arm of the Magellanic Stream? [39]
Reguitti et al. (2019), MNRAS, 482, 2750: Signatures of an eruptive phase before the explosion of the peculiar core-collapse SN 2013gc [40]
Reynolds et al. (2019), MNRAS, 482, 3591: WALLABY early science - I. The NGC 7162 galaxy group [41]
Ridden-Harper et al. (2019), MNRAS, 490, 5551: Discovery of a new WZ Sagittae-type cataclysmic variable in the Kepler/K2 data [42]
Saha et al. (2019), ApJ, 874, 30: Mapping the Interstellar Reddening and Extinction toward Baade’s Window Using Minimum Light Colors of ab-type RR Lyrae Stars: Revelations from the De-reddened Color-Magnitude Diagrams [43]
Senchyna et al. (2019), MNRAS, 488, 3492: Extremely metal-poor galaxies with HST/COS: laboratories for models of low-metallicity massive stars and high-redshift galaxies [44]
Sheppard et al. (2019), AJ, 157, 139: A New High Perihelion Trans-Plutonian Inner Oort Cloud Object: 2015 TG387 [45]
Shipp et al. (2019), ApJ, 885, 3: Proper Motions of Stellar Streams Discovered in the Dark Energy Survey [46]
Shirley et al. (2019), MNRAS, in press: HELP: A catalogue of 170 million objects, selected at 0.36—4.5 um, from 1270 deg^2 of prime extragalactic fields [47]
Stetson et al. (2019), MNRAS, 485, 3042: Homogeneous photometry - VII. Globular clusters in the Gaia era [48]
Suarez et al. (2019), MNRAS, 486, 1718: System initial mass function of the 25 Ori group from planetary-mass objects to intermediate/high-mass stars [49]
Torrealba et al. (2019), MNRAS, in press: Nine tiny star clusters in Gaia DR1, PS1 and DES [50]
Torrealba et al. (2019), MNRAS, 488, 2743: The hidden giant: discovery of an enormous Galactic dwarf satellite in Gaia DR2 [51]
Torres et al. (2019), MNRAS, 487, 2296: Constraining the nature of the accreting binary in CXOGBS J174623.5-310550 [52]
Trujillo et al. (2019), MNRAS, 486, 1192: A distance of 13 Mpc resolves the claimed anomalies of the galaxy lacking dark matter [53]
Vivas et al. (2019), AJ, 157, 35: The Population of Pulsating Variable Stars in the Sextans Dwarf Spheroidal Galaxy [54]
Walker et al. (2019), MNRAS, 490, 4121: A DECam view of the diffuse dwarf galaxy Crater II: the colour-magnitude diagram [55]
Whidden et al. (2019), AJ, 157, 119: Fast Algorithms for Slow Moving Asteroids: Constraints on the Distribution of Kuiper Belt Objects [56]
Wold et al. (2019), ApJS, 240, 5: The Spitzer-HETDEX Exploratory Large Area Survey. II. The Dark Energy Camera and Spitzer/IRAC Multiwavelength Catalog [57]
Yang et al. (2019), A&A, 629, A91: Evolved massive stars at low-metallicity. I. A source catalog for the Small Magellanic Cloud [58]
Zaritsky et al. (2019), ApJS, 240, 1: Systematically Measuring Ultra-diffuse Galaxies (SMUDGes). I. Survey Description and First Results in the Coma Galaxy Cluster and Environs [59]
Zheng et al. (2019), PASP, 131, 074502: Design for the First Narrowband Filter for the Dark Energy Camera: Optimizing the LAGER Survey for z~7 Galaxies [60]
Zucker et al. (2019), ApJ, 879, 125: A Large Catalog of Accurate Distances to Local Molecular Clouds: The Gaia DR2 Edition [61]

Papers from the Dark Energy Survey (DES) Collaboration:

Abbott et al. (2019), MNRAS, 483, 4866: Dark Energy Survey Year 1 Results: Measurement of the Baryon Acoustic Oscillation scale in the distribution of galaxies to redshift 1. [62]
Abbott et al. (2019), ApJL, 872, L30: First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters [63]
Abbot et al. (2019), Physical Review D, 99, 123505: Dark Energy Survey year 1 results: Constraints on extended cosmological models from galaxy clustering and weak lensing [64]
Abbott et al. (2019), Physical Review D, 100, 023541: Dark Energy Survey year 1 results: Joint analysis of galaxy clustering, galaxy lensing, and CMB lensing two-point functions [65]
Abbott et al. (2019), Physcial Review Letters, 122, 171301: Cosmological Constraints from Multiple Probes in the Dark Energy Survey [66]
Angus et al. (2019), MNRAS, 487, 2215: Superluminous supernovae from the Dark Energy Survey [67]
Banda_Huarca et al. (2019), AJ, 157, 120: Astrometry and Occultation Predictions to Trans-Neptunian and Centaur Objects Observed within the Dark Energy Survey [68]
Baxter et al. (2019), Physical Review D, 99, 023508: Dark Energy Survey Year 1 results: Methodology and projections for joint analysis of galaxy clustering, galaxy lensing, and CMB lensing two-point functions [69]
Brout et al. (2019), ApJ, 874, 150: First Cosmology Results Using SNe Ia from the Dark Energy Survey: Analysis, Systematic Uncertainties, and Validation [70]
Brout et al. (2019), ApJ, 874, 106: First Cosmology Results Using Type Ia Supernovae from the Dark Energy Survey: Photometric Pipeline and Light-curve Data Release [71]
Buchs et al. (2019), MNRAS, in press: Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing [72]
Camacho et al. (2019), MNRAS, 487, 3870: Dark Energy Survey Year 1 results: measurement of the galaxy angular power spectrum [73]
Carnero Rosell et al. (2019), MNRAS, 489, 5301: Brown dwarf census with the Dark Energy Survey year 3 data and the thin disc scale height of early L types [74]
Constanzi et al. (2019), MNRAS, 488, 4779: Methods for cluster cosmology and application to the SDSS in preparation for DES Year 1 release [75]
Crocce et al. (2019), MNRAS, 482, 2807: Dark Energy Survey year 1 results: galaxy sample for BAO measurement [76]
Doctor et al. (2019), ApJL, 873, L24: A Search for Optical Emission from Binary Black Hole Merger GW170814 with the Dark Energy Camera [77]
Dominguez-Sanchez et al. (2019), MNRAS, 484, 93: Transfer learning for galaxy morphology from one survey to another [78]
Fang et al. (2019), MNRAS, 490, 3573: Dark Energy Survey year 1 results: the relationship between mass and light around cosmic voids [79]
Farahi et al. (2019), MNRAS, Mass variance from archival X-ray properties of Dark Energy Survey Year-1 galaxy clusters [80]
Gruen et al. (2019), MNRAS, 488, 4389: Dark Energy Survey Year 1 results: the effect of intracluster light on photometric redshifts for weak gravitational lensing [81]
Guarnieri et al. (2019), MNRAS, 483, 3060: Candidate massive galaxies at z ~ 4 in the Dark Energy Survey [82]
Hinton et al. (2019), ApJ, 876, 15: Steve: A Hierarchical Bayesian Model for Supernova Cosmology [83]
Hoormann et al. (2019), MNRAS, 487, 3650: C IV black hole mass measurements with the Australian Dark Energy Survey (OzDES) [84]
Jacobs et al. (2019), MNRAS, 484, 5330: Finding high-redshift strong lenses in DES using convolutional neural networks [85]
Kessler et al. (2019), MNRAS, 485, 1171: First cosmology results using Type Ia supernova from the Dark Energy Survey: simulations to correct supernova distance biases [86]
Klein et al. (2019), MNRAS, 488, 739: A new RASS galaxy cluster catalogue with low contamination extending to z~1 in the DES overlap region [87]
Kovacs et al. (2019), MNRAS, 484, 5267: More out of less: an excess integrated Sachs-Wolfe signal from supervoids mapped out by the Dark Energy Survey [88]
Lasker et al. (2019), MNRAS, 485, 5329: First cosmology results using Type IA supernovae from the dark energy survey: effects of chromatic corrections to supernova photometry on measurements of cosmological parameters [89]
Lee et al. (2019), MNRAS, 489, 2887: Producing a BOSS CMASS sample with DES imaging [90]
Lin et al. (2019), Icarus, 321, 426: Evidence for color dichotomy in the primordial Neptunian Trojan population [91]
Macaulay et al. (2019), MNRAS, 486, 2184: First cosmological results using Type Ia supernovae from the Dark Energy Survey: measurement of the Hubble constant [92]
Martínez-Vázquez et al. (2019), MNRAS, 490, 2183: Search for RR Lyrae stars in DES ultra-faint systems: Grus I, Kim 2, Phoenix II, and Grus II [93]
McClintock et al. (2019), MNRAS, 482, 1352: Dark Energy Survey Year 1 results: weak lensing mass calibration of redMaPPer galaxy clusters [94]
Morgan et al. (2019), ApJ, 883, 125: A DECam Search for Explosive Optical Transients Associated with IceCube Neutrino Alerts [95]
Omori et al. (2019), Physics Review D, 100, 043517: Dark Energy Survey Year 1 Results: Cross-correlation between Dark Energy Survey Y1 galaxy weak lensing and South Pole Telescope+P l a n c k CMB weak lensing [96]
Omori et al. (2019), Physics Review D, 100, 043501: Dark Energy Survey Year 1 Results: Tomographic cross-correlations between Dark Energy Survey galaxies and CMB lensing from South Pole Telescope +Planck [97]
Pandey et al. (2019), Physics Review D, 100, 063519: Constraints on the redshift evolution of astrophysical feedback with Sunyaev-Zel'dovich effect cross-correlations [98]
Pollina et al. (2019), MNRAS, 487, 2836: On the relative bias of void tracers in the Dark Energy Survey [99]
Pratt et al. (2019), MNRAS, 487, 1363: Cosmological lensing ratios with DES Y1, SPT, and Planck [100]
Raghunathan et al. (2019), ApJ, 872, 170: Mass Calibration of Optically Selected DES Clusters Using a Measurement of CMB-cluster Lensing with SPTpol Data [101]
Raghunathan et al. (2019), Physics Review Letters, 123, 181301: Detection of CMB-Cluster Lensing using Polarization Data from SPTpol [102]
Reed et al. (2019), MNRAS, 487, 1874: Three new VHS-DES quasars at 6.7 < z < 6.9 and emission line properties at z > 6.5 [103]
Salvador et al. (2019), MNRAS, 482, 1435: Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data [104]
Samuroff et al. (2019), MNRAS, in press: Dark Energy Survey Year 1 Results: Constraints on Intrinsic Alignments and their Colour Dependence from Galaxy Clustering and Weak Lensing [105]
Shin et al. (2019), MNRAS, 487, 2900: Measurement of the splashback feature around SZ-selected Galaxy clusters with DES, SPT, and ACT [106]
Sluse et al. (2019), MNRAS, in press: H0LiCOW X. Spectroscopic/imaging survey and galaxy-group identification around the strong gravitational lens system WFI 2033-4723 [107]
Soares-Santos et al. (2019), ApJL, 876, L7: First Measurement of the Hubble Constant from a Dark Standard Siren using the Dark Energy Survey Galaxies and the LIGO/Virgo Binary–Black-hole Merger GW170814 [108]
Stern et al. (2019), MNRAS, 485, 69: Weak-lensing analysis of SPT-selected galaxy clusters using Dark Energy Survey Science Verification data [109]
Stringer et al. (2019), AJ, 158, 16: Identification of RR Lyrae Stars in Multiband, Sparsely Sampled Data from the Dark Energy Survey Using Template Fitting and Random Forest Classification [110]
Varga et al. (2019), MNRAS, 489, 2511: Dark Energy Survey Year 1 results: validation of weak lensing cluster member contamination estimates from P(z) decomposition [111]
Wang et al. (2019), ApJL, 875, L13: Rediscovery of the Sixth Star Cluster in the Fornax Dwarf Spheroidal Galaxy [112]
Wang et al. (2019), ApJ, 881, 118: The Morphology and Structure of Stellar Populations in the Fornax Dwarf Spheroidal Galaxy from Dark Energy Survey Data [113]
Zhang et al. (2019), MNRAS, 488, 1: Galaxies in X-ray selected clusters and groups in Dark Energy Survey data - II. Hierarchical Bayesian modelling of the red-sequence galaxy luminosity function [114]
Zhang et al. (2019), ApJ, 874, 165: Dark Energy Survey Year 1 Results: Detection of Intracluster Light at Redshift 0.25 [115]
Zhang et al. (2019), MNRAS, 487, 2578: Dark Energy Surveyed Year 1 results: calibration of cluster mis-centring in the redMaPPer catalogues [116]

Links
[1] http://www.ctio.noao.edu/noao/content/publications-based-decam-data-2019
[2] https://ui.adsabs.harvard.edu/abs/2019ApJ...881L..16A/abstract
[3] http://adsabs.harvard.edu/abs/2019MNRAS.485..428B
[4] https://ui.adsabs.harvard.edu//#abs/2019ApJ...870L..24B/abstract
[5] https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.3200B/abstract
[6] https://ui.adsabs.harvard.edu/abs/2019A%26A...629A..68B/abstract
[7] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.5862B/abstract
[8] https://ui.adsabs.harvard.edu/abs/2019ApJ...881L..37B/abstract
[9] https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.3952B/abstract
[10] https://ui.adsabs.harvard.edu/abs/2019PASP..131j8006C/abstract
[11] https://ui.adsabs.harvard.edu/abs/2019MNRAS.484..431C/abstract
[12] https://ui.adsabs.harvard.edu/#abs/2019MNRAS.482.3696C
[13] https://ui.adsabs.harvard.edu/#abs/2019MNRAS.482..490C
[14] http://adsabs.harvard.edu/doi/10.1093/mnras/stz398
[15] http://adsabs.harvard.edu/abs/2019AJ....157..168D
[16] http://adsabs.harvard.edu/abs/2019ApJ...870L...1D
[17] https://ui.adsabs.harvard.edu/abs/2019ApJ...887L..13D/abstract
[18] https://ui.adsabs.harvard.edu//#abs/2019MNRAS.483.5409D/abstract
[19] https://ui.adsabs.harvard.edu/abs/2019MNRAS.490L...6D/abstract
[20] https://ui.adsabs.harvard.edu/abs/2019ApJ...887...74F/abstract
[21] https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.5723F/abstract
[22] https://ui.adsabs.harvard.edu/abs/2019ApJ...881L...7G/abstract
[23] https://ui.adsabs.harvard.edu/abs/2019AJ....158..232H/abstract
[24] https://ui.adsabs.harvard.edu/abs/2019ApJ...880L...4H/abstract
[25] https://ui.adsabs.harvard.edu/abs/2019ApJ...886...90H/abstract
[26] https://ui.adsabs.harvard.edu/abs/2019AJ....157...54J/abstract
[27] https://ui.adsabs.harvard.edu/abs/2019A%26A...632A..78J/abstract
[28] https://ui.adsabs.harvard.edu/abs/2019ApJ...887..266J/abstract
[29] https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.5352K/abstract
[30] http://adsabs.harvard.edu/abs/2019MNRAS.485.4726K
[31] https://ui.adsabs.harvard.edu/abs/2019ApJ...881...80L/abstract
[32] https://ui.adsabs.harvard.edu//#abs/2019ApJ...870...12L/abstract
[33] https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.3508L/abstract
[34] https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.3403M/abstract
[35] http://adsabs.harvard.edu/abs/2019ApJ...875..154M
[36] http://adsabs.harvard.edu/abs/2019MNRAS.484.5049M
[37] https://ui.adsabs.harvard.edu/abs/2019A%26A...629A..18M/abstract
[38] http://adsabs.harvard.edu/abs/2019ApJ...874..118N
[39] https://ui.adsabs.harvard.edu/abs/2019ApJ...887...19P/abstract
[40] https://ui.adsabs.harvard.edu/#abs/2019MNRAS.482.2750R/abstract
[41] https://ui.adsabs.harvard.edu//#abs/2019MNRAS.482.3591R
[42] https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.5551R/abstract
[43] http://adsabs.harvard.edu/abs/2019ApJ...874...30S
[44] https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.3492S/abstract
[45] https://ui.adsabs.harvard.edu/abs/2019AJ....157..139S/abstract
[46] https://ui.adsabs.harvard.edu/abs/2019ApJ...885....3S/abstract
[47] https://ui.adsabs.harvard.edu/abs/2019MNRAS.tmp.2145S/abstract
[48] https://ui.adsabs.harvard.edu/abs/2019MNRAS.485.3042S/abstract
[49] https://ui.adsabs.harvard.edu/abs/2019MNRAS.486.1718S/abstract
[50] https://ui.adsabs.harvard.edu//#abs/2019MNRAS.tmp...91T/abstract
[51] https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.2743T/abstract
[52] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.2296T/abstract
[53] https://ui.adsabs.harvard.edu/abs/2019MNRAS.486.1192T/abstract
[54] https://ui.adsabs.harvard.edu//#abs/2019AJ....157...35V/abstract
[55] https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.4121W/abstract
[56] http://adsabs.harvard.edu/abs/2019AJ....157..119W
[57] https://ui.adsabs.harvard.edu//#abs/2019ApJS..240....5W/abstract
[58] https://ui.adsabs.harvard.edu/abs/2019A%26A...629A..91Y/abstract
[59] https://ui.adsabs.harvard.edu//#abs/2019ApJS..240....1Z/abstract
[60] https://ui.adsabs.harvard.edu/abs/2019PASP..131g4502Z/abstract
[61] https://ui.adsabs.harvard.edu/abs/2019ApJ...879..125Z/abstract
[62] http://adsabs.harvard.edu/abs/2019MNRAS.483.4866A
[63] http://adsabs.harvard.edu/abs/2019ApJ...872L..30A
[64] https://ui.adsabs.harvard.edu/abs/2019PhRvD..99l3505A/abstract
[65] https://ui.adsabs.harvard.edu/abs/2019PhRvD.100b3541A/abstract
[66] https://ui.adsabs.harvard.edu/abs/2019PhRvL.122q1301A/abstract
[67] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.2215A/abstract
[68] http://adsabs.harvard.edu/abs/2019AJ....157..120B
[69] https://ui.adsabs.harvard.edu//#abs/2019PhRvD..99b3508B/abstract
[70] http://adsabs.harvard.edu/abs/2019ApJ...874..150B
[71] http://adsabs.harvard.edu/abs/2019ApJ...874..106B
[72] https://ui.adsabs.harvard.edu/abs/2019MNRAS.tmp.2106B/abstract
[73] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.3870C/abstract
[74] https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.5301C/abstract
[75] https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.4779C/abstract
[76] https://ui.adsabs.harvard.edu/#abs/2019MNRAS.482.2807C/abstract
[77] http://adsabs.harvard.edu/abs/2019ApJ...873L..24D
[78] https://ui.adsabs.harvard.edu//#abs/2019MNRAS.484...93D/abstract
[79] https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.3573F/abstract
[80] https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.3341F/abstract
[81] https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.4389G/abstract
[82] https://ui.adsabs.harvard.edu//#abs/2019MNRAS.483.3060G/abstract
[83] http://adsabs.harvard.edu/abs/2019ApJ...876...15H
[84] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.3650H/abstract
[85] http://adsabs.harvard.edu/abs/2019MNRAS.484.5330J
[86] http://adsabs.harvard.edu/abs/2019MNRAS.485.1171K
[87] https://ui.adsabs.harvard.edu/abs/2019MNRAS.488..739K/abstract
[88] http://adsabs.harvard.edu/abs/2019MNRAS.484.5267K
[89] http://adsabs.harvard.edu/abs/2019MNRAS.485.5329L
[90] https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.2887L/abstract
[91] https://ui.adsabs.harvard.edu/#abs/2019Icar..321..426L/abstract
[92] http://adsabs.harvard.edu/abs/2019MNRAS.486.2184M
[93] https://ui.adsabs.harvard.edu/abs/2019MNRAS.tmp.2259M/abstract
[94] https://ui.adsabs.harvard.edu//#abs/2019MNRAS.482.1352M/abstract
[95] https://ui.adsabs.harvard.edu/abs/2019ApJ...883..125M/abstract
[96] https://ui.adsabs.harvard.edu/abs/2019PhRvD.100d3517O/abstract
[97] https://ui.adsabs.harvard.edu/abs/2019PhRvD.100d3501O/abstract
[98] https://ui.adsabs.harvard.edu/abs/2019PhRvD.100f3519P/abstract
[99] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.2836P/abstract
[100] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.1363P/abstract
[101] http://adsabs.harvard.edu/abs/2019ApJ...872..170R
[102] https://ui.adsabs.harvard.edu/abs/2019PhRvL.123r1301R/abstract
[103] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.1874R/abstract
[104] https://ui.adsabs.harvard.edu/#abs/2019MNRAS.482.1435S/abstract
[105] https://ui.adsabs.harvard.edu/abs/2019MNRAS.tmp.2187S/abstract
[106] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.2900S/abstract
[107] https://ui.adsabs.harvard.edu/abs/2019MNRAS.tmp.2136S/abstract
[108] http://adsabs.harvard.edu/abs/2019ApJ...876L...7S
[109] http://adsabs.harvard.edu/abs/2019MNRAS.485...69S
[110] https://ui.adsabs.harvard.edu/abs/2019AJ....158...16S/abstract
[111] https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.2511V/abstract
[112] http://adsabs.harvard.edu/abs/2019ApJ...875L..13W
[113] https://ui.adsabs.harvard.edu/abs/2019ApJ...881..118W/abstract
[114] https://ui.adsabs.harvard.edu/abs/2019MNRAS.488....1Z/abstract
[115] http://adsabs.harvard.edu/abs/2019ApJ...874..165Z
[116] https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.2578Z/abstract