37 citations · 71 across the 3 of their papers we have counts for
14 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: Ly intensity mapping forecast
Pablo Renard, Enrique Gaztanaga, Rupert Croft +9
In this work, we explore the application of intensity mapping to detect extended Ly emission from the IGM via cross-correlation of PAUS images with Ly forest data from eBOSS…
The PAU Survey: Photometric redshifts using transfer learning from simulations
M. Eriksen, A. Alarcon, L. Cabayol +15
In this paper we introduce the \textsc{Deepz} deep learning photometric redshift (photo-) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS fie…
CosmoHub: Interactive exploration and distribution of astronomical data on Hadoop
Pau Tallada, Jorge Carretero, Jordi Casals +13
We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmol…