CIGALE: a python Code Investigating GALaxy Emission

Abstract

Context. Measuring how the physical properties of galaxies change across cosmic times is essential to understand galaxy formation and evolution. With the advent of numerous ground-based and space-borne instruments launched over the past few decades we now have exquisite multi-wavelength observations of galaxies from the far-ultraviolet (FUV) to the radio domain. To tap into this mine of data and obtain new insight into the formation and evolution of galaxies, it is essential that we are able to extract information from their spectral energy distribution (SED). Aims. We present a completely new implementation of Code Investigating GALaxy Emission (CIGALE). Written in python, its main aims are to easily and efficiently model the FUV to radio spectrum of galaxies and estimate their physical properties such as star formation rate, attenuation, dust luminosity, stellar mass, and many other physical quantities. Methods. To compute the spectral models, CIGALE builds composite stellar populations from simple stellar populations combined with highly flexible star formation histories, calculates the emission from gas ionised by massive stars, and attenuates both the stars and the ionised gas with a highly flexible attenuation curve. Based on an energy balance principle, the absorbed energy is then reemitted by the dust in the mid-and far-infrared domains while thermal and non-thermal components are also included, extending the spectrum far into the radio range. A large grid of models is then fitted to the data and the physical properties are estimated through the analysis of the likelihood distribution. Results. CIGALE is a versatile and easy-to-use tool that makes full use of the architecture of multi-core computers, building grids of millions of models and analysing samples of thousands of galaxies, both at high speed. Beyond fitting the SEDs of galaxies and parameter estimations, it can also be used as a model-generation tool or serve as a library to build new applications.

Probing the size and charge of polycyclic aromatic hydrocarbons

“…For M82, we calculated the average UV photon energy from its modeled spectral energy distribution (SED). The M82 SED decomposition and fitting was performed with the SED-fitting code cigale (Boquien et al 2019) and was obtained from the DustPedia (Davies et al 2017) archive 7 . cigale, being an energy balance principle based code (i.e.…”

Constraining the recent star formation history of galaxies: an approximate Bayesian computation approach

“…To perform their study, they took advantage of the versatility of the SED modeling code CIGALE 1 (Boquien et al 2019). CIGALE is a SED modeling software package that has two functions: a modeling function to create SEDs from a set of given parameters and a SED fitting function to derive the physical properties of galaxies from observations.…”

ALMA CO Observations of the Host Galaxies of Long-duration Gamma-Ray Bursts. I. Molecular Gas Scaling Relations

“…In order to estimate the SFR and stellar mass of the targets in a common way, we conduct SED analysis with available photometry from UV to radio including our ALMA photometry. We adopt a SED modeling code of Code Investigating GALaxy Emission (CIGALE 3 ; Burgarella et al 2005;Noll et al 2009;Boquien et al 2019). CIGALE is based on an energy balance principle, where the energy absorbed by dust in the UV-near-IR range is re-emitted self-consistently in the mid-and far-IR range.…”