activity
20152017
most citedPhysical properties of 15 quasars at

318 citations · 1.1k across the 9 of their papers we have counts for

collaborators

13 papers

astro-ph.GA2017318 cited

Physical properties of 15 quasars at

C. Mazzucchelli, E. Bañados, B. P. Venemans +21

Quasars are galaxies hosting accreting supermassive black holes; due to their brightness, they are unique probes of the early universe. To date, only few quasars have been reported…

astro-ph.SR201778 cited

Supernovae 2016bdu and 2005gl, and their link with SN 2009ip-like transients: another piece of the puzzle

A. Pastorello, C. S. Kochanek, M. Fraser +52

Supernova (SN) 2016bdu is an unusual transient resembling SN 2009ip. SN 2009ip-like events are characterized by a long-lasting phase of erratic variability which ends with two lumi…

astro-ph.HE201752 cited

Observations of the GRB afterglow ATLAS17aeu and its possible association with GW170104

B. Stalder, J. Tonry, S. J. Smartt +26

We report the discovery and multi-wavelength data analysis of the peculiar optical transient, ATLAS17aeu. This transient was identified in the skymap of the LIGO gravitational wave…

astro-ph.GA2016

A Multi-Wavelength Photometric Census of AGN and Star Formation Activity in the Brightest Cluster Galaxies of X-ray Selected Clusters

T. S. Green, A. C. Edge, J. P. Stott +8

Despite their reputation as being "red and dead", the unique environment inhabited by Brightest Cluster Galaxies (BCGs) can often lead to a self-regulated feedback cycle between ra…

astro-ph.SR2016

Brown Dwarfs in Young Moving Groups from Pan-STARRS1. I. AB Doradus

Kimberly M. Aller, Michael C. Liu, Eugene A. Magnier +11

Substellar members of young (150 Myr) moving groups are valuable benchmarks to empirically define brown dwarf evolution with age and to study the low-mass end of the init…

astro-ph.IM2016

Of Genes and Machines: application of a combination of machine learning tools to astronomy datasets

S. Heinis, S. Kumar, S. Gezari +8

We apply a combination of a Genetic Algorithms (GA) and Support Vector Machines (SVM) machine learning algorithm to solve two important problems faced by the astronomical community…