HELP: modelling the spectral energy distributions of Herschel detected galaxies in the ELAIS N1 field

TL;DR

This paper presents a comprehensive method for fitting spectral energy distributions of over 42,000 Herschel-detected galaxies in the ELAIS N1 field, assessing the impact of different dust attenuation laws on derived physical parameters.

Contribution

It introduces a multi-criteria SED fitting approach using CIGALE, testing three dust attenuation laws, and identifying peculiar and lensed galaxy candidates in a large IR galaxy sample.

Findings

Attenuation law significantly affects stellar mass estimates, causing disparities up to a factor of two.

The method successfully identifies peculiar galaxies and potential lensed candidates.

Different attenuation laws lead to systematic variations in derived galaxy properties.

Abstract

The HELP project focuses on the data from ESA's Herschel mission, which covered over 1300$deg^2$ and is preparing to publish a multi-wavelength catalogue of millions of objects. Our main goal is to find the best approach to simultaneously fitting SEDs of millions of galaxies across a wide redshift range to obtain homogeneous estimates of the main physical parameters of detected IR galaxies. We perform SED fitting on the UV/NIR to FIR emission of 42 047 galaxies from the pilot HELP field: ELAIS N1. We use the latest release of CIGALE, a galaxy SED fitting code relying on energy balance, to deliver the main physical parameters such as $M_{star}$, SFR, and $L_{dust}$. We implement additional quality criteria to the fits by calculating $\chi^2$ values for the stellar and dust part of the spectra independently. These criteria allow us to identify the best fits and to identify peculiar galaxies. We perform the SED fitting by assuming three different dust attenuation laws separately allowing us to test the impact of the assumed law on estimated physical parameters. We implemented two additional quality value checks for the SED fitting method based on $M_{star}$ estimation and energy budget. This method allows us to identify possible objects with incorrect matching in the catalogue and peculiar galaxies; we found 351 possible candidates of lensed galaxies using two complementary $\chi^2$s criteria (stellar and IR) and $z_{phot}$ calculated for the IR part of the spectrum only. We find that the attenuation law has an important impact on the $M_{star}$ estimate (on average leading to disparities of a factor of two). We derive the relation between $M_{star}$ estimates obtained by different attenuation laws and we find the best recipe for our sample. We also make independent estimates of the total $L_{dust}$ parameter from stellar emission by fitting the galaxies with and without IR data separately.