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Register a new userCompact groups from semi-analytical models of galaxy formation -- I: a comparative study of frequency and nature
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Eugenia Diaz-Gimenez
Publication date
2019
fields
Physics
and research's language is
English
Authors
Eugenia Diaz-Gimenez
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Compact groups (CGs) of galaxies are defined as isolated and dense galaxy systems that appear to be a unique site of multiple galaxy interactions. Semi-analytical models of galaxy formation (SAMs) are a prime tool to understand CGs. We investigate how the frequency and the three-dimensional nature of CGs depends on the SAM and its underlying cosmological parameters. Extracting 9 lightcones of galaxies from 5 different SAMs and selecting CGs as in observed samples, we find that the frequency and nature of CGs depends strongly on the cosmological parameters. Moving from the WMAP1 to the WMAP7 and Planck cosmologies (increasing density of the Universe and decreasing normalisation of the power spectrum), the space density of CGs is decreased by a factor 2.5, while the fraction of CGs that are physically dense falls from 50 to 35 percent. The lower $sigma_8$ leads to fewer dense groups, while the higher $Omega_{rm m}$ causes more chance alignments. However, with increased mass and spatial resolution, the fraction of CGs that are physically dense is pushed back up to 50 percent. The intrinsic differences in the SAM recipes also lead to differences in the frequency and nature of CGs, particularly those related to how SAMs treat orphan galaxies. We find no dependence of CG properties on the flux limit of the mock catalogues nor on the waveband in which galaxies are selected. One should thus be cautious when interpreting a particular SAM for the frequency and nature of CGs.
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We study the formation of over 6000 compact groups (CGs) of galaxies identified in mock redshift-space galaxy catalogues built from semi-analytical models of galaxy formation (SAMs) run on the Millennium Simulations. We select CGs of 4 members in our mock SDSS galaxy catalogues and, for each CG, we trace back in time the real-space positions of the most massive progenitors of their 4 galaxies. By analysing the evolution of the distance of the galaxy members to the centre of mass of the group, we identify 4 channels of CG formation. The classification of these assembly channels is performed with an automatic recipe inferred from a preliminary visual inspection and based on the orbit of the galaxy with the fewest number of orbits. Most CGs show late assembly, with the last galaxy arriving on its first or second passage, while only 10-20 per cent form by the gradual contraction of their orbits by dynamical friction, and only a few per cent forming early with little subsequent contraction. However, a SAM from a higher resolution simulation leads to earlier assembly. Assembly histories of CGs also depend on cosmological parameters. At similar resolution, CGs assemble later in SAMs built on parent cosmological simulations of high density parameter. Several observed properties of mock CGs correlate with their assembly history: early-assembling CGs are smaller, with shorter crossing times, and greater magnitude gaps between their brightest two members, and their brightest galaxies have smaller spatial offsets and are more passive.
We compare the mean mass assembly histories of compact and fossil galaxy groups in the Millennium dark matter simulation and an associated semi-analytic galaxy formation model. Tracing the halo mass of compact groups (CGs) from z=0 to z=1 shows that, on average, 55 per cent of the halo mass in compact groups is assembled since z~1, compared to 40 per cent of the halo mass in fossil groups (FGs) in the same time interval, indicating that compared to FGs, CGs are relatively younger galaxy systems. At z=0, for a given halo mass, fossil groups tend to have a larger concentration than compact groups. Investigating the evolution of CGs parameters show that they become more compact with time. CGs at z=0.5 see their magnitude gaps increase exponentially, but it takes ~10 Gyr for them to reach a magnitude gap of 2 magnitudes. The slow growth of the magnitude gap leads to only a minority (~41 per cent) of CGs selected at z=0.5 turning into a FG by z=0. Also, while three-quarters of FGs go through a compact phase, most fail to meet the CG isolation criterion, leaving only ~30 per cent of FGs fully satisfying the CG selection criteria. Therefore, there is no strong link of CGs turning into FGs or FGs originating from CGs. The relation between CGs and FGs is thus more complex, and in most cases, FGs and CGs follow different evolutionary tracks.
By means of our own cosmological-hydrodynamical simulation and semi-analytical model we studied galaxy population properties in clusters and groups, spanning over 10 different bands from UV to NIR, and their evolution since redshift z=2. We compare our results in terms of galaxy red/blue fractions and luminous-to-faint ratio (LFR) on the Red Sequence (RS) with recent observational data reaching beyond z=1.5. Different selection criteria were tested in order to retrieve galaxies belonging to the RS: either by their quiescence degree measured from their specific SFR (Dead Sequence), or by their position in a colour-colour plane which is also a function of sSFR. In both cases, the colour cut and the limiting magnitude threshold were let evolving with redshift, in order to follow the natural shift of the characteristic luminosity in the LF. We find that the Butcher-Oemler effect is wavelength-dependent, with the fraction of blue galaxies increasing steeper in optical colours than in NIR. Besides, only when applying a lower limit in terms of fixed absolute magnitude, a steep BO effect can be reproduced, while the blue fraction results less evolving when selecting samples by stellar mass or an evolving magnitude limit. We then find that also the RS-LFR behaviour, highly debated in the literature, is strongly dependent on the galaxy selection function: in particular its very mild evolution recovered when measured in terms of stellar mass, is in agreement with values reported for some of the highest redshift confirmed (proto)clusters. As to differences through environments, we find that normal groups and (to a lesser extent) cluster outskirts present the highest values of both star forming fraction and LFR at low z, while fossil groups and cluster cores the lowest: this separation among groups begins after z~0.5, while earlier all group star forming properties are undistinguishable.
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.
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.
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