The PAU Survey: A Forward Modeling Approach for Narrow-band Imaging
Luca Tortorelli, Lorenza Della Bruna, J\"org Herbel, Adam Amara,, Alexandre Refregier, Alex Alarcon, Francisco J. Castander, Juan De Vicente,, Martin Eriksen, Enrique Fernandez, Juan Garc\'ia-Bellido, Enrique Gaztanaga,, Ramon Miquel, Cristobal Padilla, Eusebio Sanchez

TL;DR
This paper validates a galaxy population model derived from broad-band photometry by forward modeling the PAU Survey's narrow-band data, demonstrating good agreement and potential for spectral information integration.
Contribution
It applies and tests a forward modeling approach to narrow-band photometry, confirming the model's validity for the PAUS data and enabling spectral information incorporation.
Findings
Good agreement in pixel value distributions and magnitudes
Successful principal component analysis comparison
Model effectively reproduces PAUS narrow-band data
Abstract
Weak gravitational lensing is a powerful probe of the dark sector, once measurement systematic errors can be controlled. In Refregier & Amara (2014), a calibration method based on forward modeling, called MCCL, was proposed. This relies on fast image simulations (e.g., UFig; Berge et al. 2013) that capture the key features of galaxy populations and measurement effects. The MCCL approach has been used in Herbel et al. (2017) to determine the redshift distribution of cosmological galaxy samples and, in the process, the authors derived a model for the galaxy population mainly based on broad-band photometry. Here, we test this model by forward modeling the 40 narrow-band photometry given by the novel PAU Survey (PAUS). For this purpose, we apply the same forced photometric pipeline on data and simulations using Source Extractor (Bertin & Arnouts 1996). The image simulation scheme…
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