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Register a new userFast radiative transfer of dust reprocessing in semi-analytic models with artificial neural networks
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Laura Silva
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A serious concern for semi-analytical galaxy formation models, aiming to simulate multi-wavelength surveys and to thoroughly explore the model parameter space, is the extremely time consuming numerical solution of the radiative transfer of stellar radiation through dusty media. To overcome this problem, we have implemented an artificial neural network algorithm in the radiative transfer code GRASIL, in order to significantly speed up the computation of the infrared SED. The ANN we have implemented is of general use, in that its input neurons are defined as those quantities effectively determining the shape of the IR SED. Therefore, the training of the ANN can be performed with any model and then applied to other models. We made a blind test to check the algorithm, by applying a net trained with a standard chemical evolution model (i.e. CHE_EVO) to a mock catalogue extracted from the SAM MORGANA, and compared galaxy counts and evolution of the luminosity functions in several near-IR to sub-mm bands, and also the spectral differences for a large subset of randomly extracted models. The ANN is able to excellently approximate the full computation, but with a gain in CPU time by $sim 2$ orders of magnitude. It is only advisable that the training covers reasonably well the range of values of the input neurons in the application. Indeed in the sub-mm at high redshift, a tiny fraction of models with some sensible input neurons out of the range of the trained net cause wrong answer by the ANN. These are extreme starbursting models with high optical depths, favorably selected by sub-mm observations, and difficult to predict a priori.
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The sterile neutrino is a viable dark matter candidate that can be produced in the early Universe via non-equilibrium processes, and would therefore possess a highly non-thermal spectrum of primordial velocities. In this paper we analyse the process of structure formation with this class of dark matter particles. To this end we construct primordial dark matter power spectra as a function of the lepton asymmetry, $L_6$, that is present in the primordial plasma and leads to resonant sterile neutrino production. We compare these power spectra with those of thermally produced dark matter particles and show that resonantly produced sterile neutrinos are much colder than their thermal relic counterparts. We also demonstrate that the shape of these power spectra is not determined by the free-streaming scale alone. We then use the power spectra as an input for semi-analytic models of galaxy formation in order to predict the number of luminous satellite galaxies in a Milky Way-like halo. By assuming that the mass of the Milky Way halo must be no more than $2times10^{12}M_{odot}$ (the adopted upper bound based on current astronomical observations) we are able to constrain the value of $L_6$ for $M_sle 8$~keV. We also show that the range of $L_6$ that is in best agreement with the 3.5~keV line (if produced by decays of 7~keV sterile neutrino) requires that the Milky Way halo has a mass no smaller than $1.5times10^{12}M_{odot}$. Finally, we compare the power spectra obtained by direct integration of the Boltzmann equations for a non-resonantly produced sterile neutrino with the fitting formula of Viel~et~al. and find that the latter significantly underestimates the power amplitude on scales relevant to satellite galaxies.
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