Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userCompact groups from semi-analytical models of galaxy formation -- II: Different assembly channels
148
0
0.0
(
0
)
Added by
Eugenia Diaz-Gimenez
Publication date
2021
fields
Physics
and research's language is
English
Authors
Eugenia Diaz-Gimenez
Ask ChatGPT about the research
No Arabic abstract
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.
rate research
Read More
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.
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.
The formation of ultra-compact dwarf galaxies (UCDs) is believed to be interaction driven, and UCDs are abundant in the cores of galaxy clusters, environments that mark the end-point of galaxy evolution. Nothing is known about the properties of UCDs in compact groups of galaxies, environments where most of galaxy evolution and interaction is believed to occur and where UCDs in intermediate state of evolution may be expected. The main goal of this study is to detect and characterize, for the first time, the UCD population of compact groups. For that, 2 groups in different evolutionary stages, HCG 22 and HCG 90, were targeted with VLT/FORS2/MXU. We detect 16 and 5 objects belonging to HCG 22 and HCG 90, respectively, covering the magnitude range -10.0 > M_R > -11.5 mag. Their colours are consistent with old ages covering a broad range in metallicities. Photometric mass estimates put 4 objects in HCG 90 and 9 in HCG 22 in the mass range of UCDs (>2x10^6 M_Sun) for an assumed age of 12 Gyr. These UCDs are on average 2-3 times larger than typical Galactic GCs, covering a range of 2 >~ r_h >~ 21 pc. The UCDs in HCG 22 are more concentrated around the central galaxy than in HCG 90, at the 99% confidence level. They cover a broad range in [alpha/Fe] abundances from sub- to super-solar. The spectra of 3 UCDs show tentative evidence for intermediate age stellar populations. We calculate the specific frequency (S_N) of UCDs for both groups, finding that HCG 22 has about three times higher S_N than HCG 90. The ensemble properties of the detected UCDs supports 2 co-existing formation channels: a star cluster origin and an origin as tidally stripped dwarf nuclei. Our results imply that the UCDs detected in both groups do not, in their majority, originate from relatively recent galaxy interactions. Most of the detected UCDs have likely been brought into the group with their host galaxies.[abridged]
Cosmic rays (CRs) with ~GeV energies can contribute significantly to the energy and pressure budget in the interstellar, circumgalactic, and intergalactic medium (ISM, CGM, IGM). Recent cosmological simulations have begun to explore these effects, but almost all studies have been restricted to simplified models with constant CR diffusivity and/or streaming speeds. Physical models of CR propagation/scattering via extrinsic turbulence and self-excited waves predict transport coefficients which are complicated functions of local plasma properties. In a companion paper, we consider a wide range of observational constraints to identify proposed physically-motivated cosmic-ray propagation scalings which satisfy both detailed Milky Way (MW) and extra-galactic $gamma$-ray constraints. Here, we compare the effects of these models relative to simpler diffusion+streaming models on galaxy and CGM properties at dwarf through MW mass scales. The physical models predict large local variations in CR diffusivity, with median diffusivity increasing with galacto-centric radii and decreasing with galaxy mass and redshift. These effects lead to a more rapid dropoff of CR energy density in the CGM (compared to simpler models), in turn producing weaker effects of CRs on galaxy star formation rates (SFRs), CGM absorption profiles and galactic outflows. The predictions of the more physical CR models tend to lie in between models which ignore CRs entirely and models which treat CRs with constant diffusivity.
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.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
