37 citations · 84 across the 3 of their papers we have counts for
10 papers
The PAU Survey: narrowband photometric redshifts using Gaussian processes
John Y. H. Soo, Benjamin Joachimi, Martin Eriksen +16
We study the performance of the hybrid template-machine-learning photometric redshift (photo-) algorithm Delight, which uses Gaussian processes, on a subset of the early data re…
The PAU Survey: Intrinsic alignments and clustering of narrow-band photometric galaxies
Harry Johnston, Benjamin Joachimi, Peder Norberg +20
We present the first measurements of the projected clustering and intrinsic alignments (IA) of galaxies observed by the Physics of the Accelerating Universe Survey (PAUS). With pho…
The PAU Survey: An improved photo- sample in the COSMOS field
Alex Alarcon, Enrique Gaztanaga, Martin Eriksen +21
We present -- and make publicly available -- accurate and precise photometric redshifts in the ACS footprint from the COSMOS field for objects with . The re…
The PAU Survey: Background light estimation with deep learning techniques
Laura Cabayol-Garcia, Martin B. Eriksen, Àlex Alarcón +17
In any imaging survey, measuring accurately the astronomical background light is crucial to obtain good photometry. This paper introduces BKGnet, a deep neural network to predict t…
The Physics of the Accelerating Universe Camera
Cristobal Padilla, Francisco J. Castander, Alex Alarcon +30
The PAU (Physics of the Accelerating Universe) Survey goal is to obtain photometric redshifts (photo-z) and Spectral Energy Distribution (SED) of astronomical objects with a resolu…
Superluminous Supernovae from the Dark Energy Survey
C. R. Angus, M. Smith, M. Sullivan +72
We present a sample of 21 hydrogen-free superluminous supernovae (SLSNe-I), and one hydrogen-rich SLSN (SLSN-II) detected during the five-year Dark Energy Survey (DES). These SNe,…