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Register a new userCIGALE: a python Code Investigating GALaxy Emission
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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 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 SED. Aims. We present a completely new implementation of 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 re-emitted 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.
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Photometric data of galaxies covering the rest-frame wavelength range from far-UV to far-IR make it possible to derive galaxy properties with a high reliability by fitting the attenuated stellar emission and the related dust emission at the same time. For this purpose we wrote the code CIGALE (Code Investigating GALaxy Emission) that uses model spectra composed of the Maraston (or PEGASE) stellar population models, synthetic attenuation functions based on a modified Calzetti law, spectral line templates, the Dale & Helou dust emission models, and optional spectral templates of obscured AGN. Depending on the input redshifts, filter fluxes are computed for the model set and compared to the galaxy photometry by carrying out a Bayesian-like analysis. CIGALE was tested by analysing 39 nearby galaxies selected from SINGS. The reliability of the different model parameters was evaluated by studying the resulting expectation values and their standard deviations in relation to the input model grid. Moreover, the influence of the filter set and the quality of photometric data on the code results was estimated. For up to 17 filters between 0.15 and 160 mum, we find robust results for the mass, star formation rate, effective age of the stellar population at 4000 A, bolometric luminosity, luminosity absorbed by dust, and attenuation in the far-UV. A study of the mutual relations between the reliable properties confirms the dependence of star formation activity on morphology in the local Universe and indicates a significant drop in this activity at about 10^11 M_sol towards higher total stellar masses. The dustiest sample galaxies are present in the same mass range. [abridged]
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