activity
19972023
most citedDarkSide-20k: A 20 Tonne Two-Phase LAr TPC for Direct Dark Matter Detection at LNGS

613 citations · 4.4k across the 121 of their papers we have counts for

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Showing 2015Show all

8 papers · 1 filter

astro-ph.CO2015★ 204 cited

Mapping the Galaxy Color-Redshift Relation: Optimal Photometric Redshift Calibration Strategies for Cosmology Surveys

Daniel Masters, Peter Capak, Daniel Stern +17

Calibrating the photometric redshifts of >10^9 galaxies for upcoming weak lensing cosmology experiments is a major challenge for the astrophysics community. The path to obtaining t…

astro-ph.CO2015★ 295 cited

The first and second data releases of the Kilo-Degree Survey

Jelte T. A. de Jong, Gijs A. Verdoes Kleijn, Danny R. Boxhoorn +46

The Kilo-Degree Survey (KiDS) is an optical wide-field imaging survey carried out with the VLT Survey Telescope and the OmegaCAM camera. KiDS will image 1500 square degrees in four…

astro-ph.IM2015★ 49 cited

Machine Learning based photometric redshifts for the KiDS ESO DR2 galaxies

Stefano Cavuoti, Massimo Brescia, Crescenzo Tortora +9

We estimated photometric redshifts (zphot) for more than 1.1 million galaxies of the ESO Public Kilo-Degree Survey (KiDS) Data Release 2. KiDS is an optical wide-field imaging surv…

astro-ph.GA2015★ 2 cited

A new search for variability-selected active galaxies within the VST SUDARE-VOICE survey: the Chandra Deep Field South and the SERVS-SWIRE area

S. Falocco, D. De Cicco, M. Paolillo +19

This work makes use of the VST observations to select variable sources. We use also the IR photometry, SED fitting and X-ray information where available to confirm the nature of th…

astro-ph.GA2015★ 30 cited

SUDARE-VOICE variability-selection of Active Galaxies in the Chandra Deep Field South and the SERVS/SWIRE region

S. Falocco, M. Paolillo, G. Covone +18

One of the most peculiar characteristics of Active Galactic Nuclei (AGN) is their variability over all wavelengths. This property has been used in the past to select AGN samples an…

astro-ph.GA2015★ 53 cited

Automated physical classification in the SDSS DR10. A catalogue of candidate Quasars

Massimo Brescia, Stefano Cavuoti, Giuseppe Longo

We discuss whether modern machine learning methods can be used to characterize the physical nature of the large number of objects sampled by the modern multi-band digital surveys.…