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A Statistical Semi-Empirical Model: Satellite galaxies in Groups and Clusters

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 Added by Philip Grylls
 Publication date 2018
  fields Physics
and research's language is English
 Authors P. J. Grylls




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We present STEEL a STatistical sEmi-Empirical modeL designed to probe the distribution of satellite galaxies in groups and clusters. Our fast statistical methodology relies on tracing the abundances of central and satellite haloes via their mass functions at all cosmic epochs with virtually no limitation on cosmic volume and mass resolution. From mean halo accretion histories and subhalo mass functions the satellite mass function is progressively built in time via abundance matching techniques constrained by number densities of centrals in the local Universe. By enforcing dynamical merging timescales as predicted by high-resolution N-body simulations, we obtain satellite distributions as a function of stellar mass and halo mass consistent with current data. We show that stellar stripping, star formation, and quenching play all a secondary role in setting the number densities of massive satellites above $M_*gtrsim 3times 10^{10}, M_{odot}$. We further show that observed star formation rates used in our empirical model over predict low-mass satellites below $M_*lesssim 3times 10^{10}, M_{odot}$, whereas, star formation rates derived from a continuity equation approach yield the correct abundances similar to previous results for centrals.

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244 - J. Vennik , U. Hopp 2015
We analyse distribution, kinematics and star-formation (SF) properties of satellite galaxies in three different samples of nearby groups. We find that studied groups are generally well approximated by low-concentration NFW model, show a variety of LOS velocity dispersion profiles and signs of SF quenching in outskirts of dwarf satellite galaxies.
264 - Andreea S. Font 2008
Current models of galaxy formation predict satellite galaxies in groups and clusters that are redder than observed. We investigate the effect on the colours of satellite galaxies produced by the ram pressure stripping of their hot gaseous atmospheres as the satellites orbit within their parent halo. We incorporate a model of the stripping process based on detailed hydrodynamic simulations within the Durham semi-analytic model of galaxy formation. The simulations show that the environment in groups and clusters is less aggressive than previously assumed. The main uncertainty in the model is the treatment of gas expelled by supernovae. With reasonable assumptions for the stripping of this material, we find that satellite galaxies are able to retain a significant fraction of their hot gas for several Gigayears, thereby replenishing their reservoirs of cold, star forming gas and remaining blue for a relatively long period of time. A bimodal distribution of galaxy colours, similar to that observed in SDSS data, is established and the colours of the satellite galaxies are in good agreement with the data. In addition, our model naturally accounts for the observed dependence of satellite colours on environment, from small groups to high mass clusters.
Observational systematics complicate comparisons with theoretical models limiting understanding of galaxy evolution. In particular, different empirical determinations of the stellar mass function imply distinct mappings between the galaxy and halo masses, leading to diverse galaxy evolutionary tracks. Using our state-of-the-art STatistical sEmi-Empirical modeL, STEEL, we show fully self-consistent models capable of generating galaxy growth histories that simultaneously and closely agree with the latest data on satellite richness and star-formation rates at multiple redshifts and environments. Central galaxy histories are generated using the central halo mass tracks from state-of-the-art statistical dark matter accretion histories coupled to abundance matching routines. We show that too flat high-mass slopes in the input stellar-mass-halo-mass relations as predicted by previous works, imply non-physical stellar mass growth histories weaker than those implied by satellite accretion alone. Our best-fit models reproduce the satellite distributions at the largest masses and highest redshifts probed, the latest data on star formation rates and its bi-modality in the local Universe, and the correct fraction of ellipticals. Our results are important to predict robust and self-consistent stellar-mass-halo-mass relations and to generate reliable galaxy mock catalogues for the next generations of extra-galactic surveys such as Euclid and LSST.
We introduce a new physical recipe into the De Lucia and Blaizot version of the Munich semi-analytic model built upon the Millennium dark matter simulation: the tidal stripping of stellar material from satellite galaxies during mergers. To test the significance of the new physical process we apply a Monte Carlo Markov Chain parameter estimation technique constraining the model with the $K$-band luminosity function, $B-V$ colours and the black hole-bulge mass relation. The differences in parameter correlations, and in the allowed regions in likelihood space, reveal the impact of the new physics on the basic ingredients of the model, such as the star-formation laws, feedback recipes and the black hole growth model. With satellite disruption in place, we get a model likelihood four times higher than in the original model, indicating that the new process seems to be favoured by observations. This is achieved mainly due to a reduction in black hole growth that produces a better agreement between the properties of central black holes and host galaxies. Compared to the best-fit model without disruption, the new model removes the excess of dwarf galaxies in the original recipe with a more modest supernova heating. The new model is now consistent with the three observational data sets used to constrain it, while significantly improving the agreement with observations for the distribution of metals in stars. Moreover, the model now follows the build up of intra-cluster light.
We combine orbital information from N-body simulations with an analytic model for star formation quenching and SDSS observations to infer the differential effect of the group/cluster environment on star formation in satellite galaxies. We also consider a model for gas stripping, using the same input supplemented with HI fluxes from the ALFALFA survey. The models are motivated by and tested on the Hydrangea cosmological hydrodynamical simulation suite. We recover the characteristic times when satellite galaxies are stripped and quenched. Stripping in massive ($M_mathrm{ vir}sim 10^{14.5},mathrm{M}_odot$) clusters typically occurs at or just before the first pericentric passage. Lower mass ($sim10^{13.5},mathrm{M}_odot$) groups strip their satellites on a significantly longer (by $sim3,mathrm{Gyr}$) timescale. Quenching occurs later: Balmer emission lines typically fade $sim3.5,mathrm{Gyr}$ ($5.5,mathrm{Gyr}$) after first pericentre in clusters (groups), followed a few hundred $mathrm{Myr}$ later by reddenning in $(g-r)$ colour. These `delay timescales are remarkably constant across the entire satellite stellar mass range probed ($sim10^{9.5}-10^{11},mathrm{M}_odot$), a feature closely tied to our treatment of `group pre-processing. The lowest mass groups in our sample ($sim10^{12.5},mathrm{M}_odot$) strip and quench their satellites extremely inefficiently: typical timescales may approach the age of the Universe. Our measurements are qualitatively consistent with the `delayed-then-rapid quenching scenario advocated for by several other studies, but we find significantly longer delay times. Our combination of a homogeneous analysis and input catalogues yields new insight into the sequence of events leading to quenching across wide intervals in host and satellite mass.
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