Cosmic star-formation history from a non-parametric inversion of infrared galaxy counts
Damien Le Borgne (1, 2), David Elbaz (1), Pierre Ocvirk (3) and, Christophe Pichon (2) ((1) CEA/Saclay, DSM/IRFU/SAp, Gif-sur-Yvette, France,, (2) Institut d'Astrophysique de Paris, UMR7095, UPMC, Paris, France, (3), Astrophysikalisches Institut Potsdam, Potsdam, Germany)

TL;DR
This study uses a non-parametric inversion method on infrared galaxy counts to constrain the cosmic star-formation history without relying on redshift data, aligning well with existing measurements.
Contribution
It introduces a novel non-parametric approach to derive the cosmic star-formation history directly from multi-wavelength infrared counts and CIRB data.
Findings
Star-formation rate density peaks around redshift 2.
Infrared counts and CIRB alone can recover star-formation history.
Model consistency with stellar mass density evolution.
Abstract
[Abridged] This paper aims at providing new conservative constraints to the cosmic star-formation history from the empirical modeling of mid- and far-infrared data. We perform a non-parametric inversion of galaxy counts at 15, 24, 70, 160, and 850 microns simultaneously. It is a "blind" search (no redshift information is required) of all possible evolutions of the infrared luminosity function of galaxies, from which the evolution of the star-formation rate density and its uncertainties are derived. The cosmic infrared background (CIRB) measurements are used a posteriori to tighten the range of solutions. The inversion relies only on two hypotheses: (1) the luminosity function remains smooth both in redshift and luminosity, (2) a set of infrared spectral energy distributions (SEDs) of galaxies must be assumed. The range of star-formation histories that we derive is well constrained and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
