Improved Models for Cosmic Infrared Background Anisotropies: New Constraints on the IR Galaxy Population

TL;DR

This paper introduces an improved model linking star-forming galaxies to dark matter halos to better understand cosmic infrared background anisotropies, providing new constraints on galaxy populations and star formation history.

Contribution

The authors develop a flexible, parameterized model that fits Planck CIB anisotropy data and offers insights into galaxy evolution and star formation efficiency.

Findings

Star formation efficiency peaks at halo mass ~5x10^12 solar masses.

Infrared luminosity per unit mass increases rapidly with redshift.

CIB is dominated by long-lived quiescent star formation.

Abstract

The power spectrum of cosmic infrared background (CIB) anisotropies is sensitive to the connection between star formation and dark matter halos over the entire cosmic star formation history. Here we develop a model that associates star-forming galaxies with dark matter halos and their subhalos. The model is based on a parameterized relation between the dust-processed infrared luminosity and (sub)halo mass. By adjusting 3 free parameters, we attempt to simultaneously fit the 4 frequency bands of the Planck measurement of the CIB anisotropy power spectrum. To fit the data, we find that the star-formation efficiency must peak on a halo mass scale of ~ 5x10^12 solar mass and the infrared luminosity per unit mass must increase rapidly with redshift. By comparing our predictions with a well-calibrated phenomenological model for shot noise, and with a direct observation of source counts, we show that the mean duty cycle of the underlying infrared sources must be near unity, indicating that the CIB is dominated by long-lived quiescent star formation, rather than intermittent short "star bursts". Despite the improved flexibility of our model, the best simultaneous fit to all four Planck channels remains relatively poor. We discuss possible further extensions to alleviate the remaining tension with the data. Our model presents a theoretical framework for a future joint analysis of both background anisotropy and source count measurements.