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Register a new userCollision-induced galaxy formation: semi-analytical model and multi-wavelength predictions
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Added by
Julien E. G. Devriendt
Publication date
2002
fields
Physics
and research's language is
English
Authors
Christophe Balland
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A semi-analytic model is proposed that couples the Press-Schechter formalism for the number of galaxies with a prescription for galaxy-galaxy interactions that enables to follow the evolution of galaxy morphologies along the Hubble sequence. Within this framework, we calculate the chemo-spectrophotometric evolution of galaxies to obtain spectral energy distributions. We find that such an approach is very successful in reproducing the statistical properties of galaxies as well as their time evolution. We are able to make predictions as a function of galaxy type: for clarity, we restrict ourselves to two categories of galaxies: early and late types that are identified with ellipticals and disks. In our model, irregulars are simply an early stage of galaxy formation. In particular, we obtain good matches for the galaxy counts and redshift distributions of sources from UV to submm wavelengths. We also reproduce the observed cosmic star formation history and the diffuse background radiation, and make predictions as to the epoch and wavelength at which the dust-shrouded star formation of spheroids begins to dominate over the star formation that occurs more quiescently in disks. A new prediction of our model is a rise in the FIR luminosity density with increasing redshift, peaking at about $zsim 3$, and with a ratio to the local luminosity density $rho_{L, u} (z = z_{peak})/ rho_{L, u} (z = 0)$ about 10 times higher than that in the blue (B-band) which peaks near $zsim 2$.
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In a Universe where AGN feedback regulates star formation in massive galaxies, a strong correlation between these two quantities is expected. If the gas causing star formation is also responsible for feeding the central black hole, then a positive correlation is expected. If powerful AGNs are responsible for the star formation quenching, then a negative correlation is expected. Observations so far have mainly found a mild correlation or no correlation at all (i.e. a flat relation between star formation rate (SFR) and AGN luminosity), raising questions about the whole paradigm of AGN feedback. In this paper, we report the predictions of the GALFORM semi-analytical model, which has a very strong coupling between AGN activity and quenching of star formation. The predicted SFR-AGN luminosity correlation appears negative in the low AGN luminosity regime, where AGN feedback acts, but becomes strongly positive in the regime of the brightest AGN. Our predictions reproduce reasonably well recent observations by Rosario et al., yet there is some discrepancy in the normalisation of the correlation at low luminosities and high redshifts. Though this regime could be strongly influenced by observational biases, we argue that the disagreement could be ascribed to the fact that GALFORM neglects AGN variability effects. Interestingly, the galaxies that dominate the regime where the observations imply a weak correlation are massive early-type galaxies that are subject to AGN feedback. Nevertheless, these galaxies retain high enough molecular hydrogen contents to maintain relatively high star formation rates and strong infrared emission.
We present new results from a multi-wavelength model of galaxy formation, which combines a semi-analytical treatment of the formation of galaxies within the CDM framework with a sophisticated treatment of absorption and emission of radiation by dust. We find that the model, which incorporates a top-heavy IMF in bursts, agrees well with the evolution of the rest-frame far-UV luminosity function over the range z=0-6, with the IR number counts in all bands measured by SPITZER, and with the observed evolution of the mid-IR luminosity function for z=0-2.
(Abridged) This paper predicts self-consistent faint galaxy counts from the UV to the submm wavelength range. The STARDUST spectral energy distributions described in Devriendt et al. (1999) are embedded within the explicit cosmological framework of a simple semi-analytic model of galaxy formation and evolution. We build a class of models which capture the luminosity budget of the universe through faint galaxy counts and redshift distributions in the whole wavelength range spanned by our spectra. In contrast with a rather stable behaviour in the optical and even in the far-IR, the submm counts are dramatically sensitive to variations in the cosmological parameters and changes in the star formation history. Faint submm counts are more easily accommodated within an open universe with a low value of $Omega_0$, or a flat universe with a non-zero cosmological constant. This study illustrates the implementation of multi-wavelength spectra into a semi-analytic model. In spite of its simplicity, it already provides fair fits of the current data of faint counts, and a physically motivated way of interpolating and extrapolating these data to other wavelengths and fainter flux levels.
We present a new version of the GALFORM semi-analytical model of galaxy formation. This brings together several previous developments of GALFORM into a single unified model, including a different initial mass function (IMF) in quiescent star formation and in starbursts, feedback from active galactic nuclei supressing gas cooling in massive halos, and a new empirical star formation law in galaxy disks based on their molecular gas content. In addition, we have updated the cosmology, introduced a more accurate treatment of dynamical friction acting on satellite galaxies, and updated the stellar population model. The new model is able to simultaneously explain both the observed evolution of the K-band luminosity function and stellar mass function, and the number counts and redshift distribution of sub-mm galaxies selected at 850 mu. This was not previously achieved by a single physical model within the LambdaCDM framework, but requires having an IMF in starbursts that is somewhat top-heavy. The new model is tested against a wide variety of observational data covering wavelengths from the far-UV to sub-mm, and redshifts from z=0 to z=6, and is found to be generally successful. These observations include the optical and near-IR luminosity functions, HI mass function, fraction of early type galaxies, Tully-Fisher, metallicity-luminosity and size-luminosity relations at z=0, as well as far-IR number counts, and far-UV luminosity functions at z ~ 3-6. [abridged]
We implement a sample-efficient method for rapid and accurate emulation of semi-analytical galaxy formation models over a wide range of model outputs. We use ensembled deep learning algorithms to produce a fast emulator of an updated version of the GALFORM model from a small number of training examples. We use the emulator to explore the models parameter space, and apply sensitivity analysis techniques to better understand the relative importance of the model parameters. We uncover key tensions between observational datasets by applying a heuristic weighting scheme in a Markov chain Monte Carlo framework and exploring the effects of requiring improved fits to certain datasets relative to others. Furthermore, we demonstrate that this method can be used to successfully calibrate the model parameters to a comprehensive list of observational constraints. In doing so, we re-discover previous GALFORM fits in an automatic and transparent way, and discover an improved fit by applying a heavier weighting to the fit to the metallicities of early-type galaxies. The deep learning emulator requires a fraction of the model evaluations needed in similar emulation approaches, achieving an out-of-sample mean absolute error at the knee of the K-band luminosity function of 0.06 dex with less than 1000 model evaluations. We demonstrate that this is an extremely efficient, inexpensive and transparent way to explore multi-dimensional parameter spaces, and can be applied more widely beyond semi-analytical galaxy formation models.
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