activity
20192021
most citedGalaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks

60 citations · 60 across the 1 of their papers we have counts for

collaborators

5 papers

astro-ph.GA202160 cited

Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks

Ting-Yun Cheng, Christopher J. Conselice, Alfonso Aragón-Salamanca +57

We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million of galaxies, using the Dark Energy Survey (DES) Year 3…

astro-ph.CO2020

Dark Energy Survey Year 1 Results: Constraining Baryonic Physics in the Universe

Hung-Jin Huang, Tim Eifler, Rachel Mandelbaum +74

Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the f…

astro-ph.GA2020

Is diffuse intracluster light a good tracer of the galaxy cluster matter distribution?

H. Sampaio-Santos, Y. Zhang, R. L. C. Ogando +64

We explore the relation between diffuse intracluster light (central galaxy included) and the galaxy cluster (baryonic and dark) matter distribution using a sample of 528 clusters a…

astro-ph.CO2019

Probabilistic cosmic web classification using fast-generated training data

Brandon Buncher, Matias Carrasco Kind

We present a novel method of robust probabilistic cosmic web particle classification in three dimensions using a supervised machine learning algorithm. Training data was generated…

astro-ph.SR2019

Brown dwarf census with the Dark Energy Survey year 3 data and the thin disk scale height of early L types

A. Carnero Rosell, B. Santiago, M. dal Ponte +44

In this paper we present a catalogue of 11,745 brown dwarfs with spectral types ranging from L0 to T9, photometrically classified using data from the Dark Energy Survey (DES) year…