The PAU Survey: a forward modeling approach for narrow-band imaging

Weak gravitational lensing is a powerful probe of the dark sector, once measurement systematic errors can be controlled. In [1], a calibration method based on forward modeling, called MCCL, was proposed. This relies on fast image simulations (e.g., UFig [2, 3]) that capture the key features of galaxy populations and measurement effects. The MCCL approach has been used in [4] 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 [5]. The image simulation scheme performance is assessed at the image and at the catalogues level. We find good statistical agreement for the distribution of pixel values, for the magnitude-size relation and for the inter-band correlations. We also discuss the small residual differences in the magnitude distributions. A principal component analysis is then performed, in order to derive a global comparison of the narrow-band photometry between the data and the simulations. We use a 'mixing' matrix to quantify the agreement between the observed and simulated sets of Principal Components (PCs). We find good agreement, especially for the first three most significant PCs. We also compare the coefficients of the PCs decomposition. While there are slight differences for some coefficients, we find that the distributions are consistent. Together, our results show that the galaxy population model derived from broad-band photometry is in good overall agreement with the PAUS data. This offers good prospects for incorporating spectral information to the galaxy model by adjusting it to the PAUS narrow-band data using forward modeling.