Do you want to publish a course? Click here

The environmental dependence of clustering in hierarchical models

90   0   0.0 ( 0 )
 Added by Ummi Abbas
 Publication date 2005
  fields Physics
and research's language is English
 Authors Ummi Abbas




Ask ChatGPT about the research

In hierarchical models, density fluctuations on different scales are correlated. This induces correlations between dark halo masses, their formation histories, and their larger-scale environments. In turn, this produces a correlation between galaxy properties and environment. This correlation is entirely statistical in nature. We show how the observed clustering of galaxies can be used to quantify the importance of this statistical correlation relative to other physical effects which may also give rise to correlations between the properties of galaxies and their surroundings. We also develop a halo model description of this environmental dependence of clustering.



rate research

Read More

The main ingredients of recent semi-analytic models of galaxy formation are summarised. We present predictions for the galaxy clustering properties of a well specified LCDM model whose parameters are constrained by observed local galaxy properties. We present preliminary predictions for evolution of clustering that can be probed with deep pencil beam surveys.
307 - Ummi Abbas 2006
A generic prediction of hierarchical clustering models is that the mass function of dark haloes in dense regions in the Universe should be top-heavy. We provide a novel test of this prediction using a sample of galaxies drawn from the Sloan Digital Sky Survey. To perform the test, we compare measurements of galaxy clustering in dense and underdense regions. We find that galaxies in dense regions cluster significantly more strongly than those in less dense regions. This is true over the entire 0.1--30 Mpc pair separation range for which we can make accurate measurements. We make similar measurements in realistic mock catalogs in which the only environmental effects are those which arise from the predicted correlation between halo mass and environment. We also provide an analytic halo-model based calculation of the effect. Both the mock catalogs and the analytic calculation provide rather good descriptions of the SDSS measurements. Thus, our results provide strong support for hierarchical models. They suggest that, unless care is taken to study galaxies at fixed mass, correlations between galaxy properties and the surrounding environment are almost entirely due to more fundamental correlations between galaxy properties and host halo mass, and between halo mass and environment.
We compare state-of-the-art semi-analytic models of galaxy formation as well as advanced sub-halo abundance matching models with a large sample of early-type galaxies from SDSS at z < 0.3. We focus our attention on the dependence of median sizes of central galaxies on host halo mass. The data do not show any difference in the structural properties of early-type galaxies with environment, at fixed stellar mass. All hierarchical models considered in this work instead tend to predict a moderate to strong environmental dependence, with the median size increasing by a factor of about 1.5-3 when moving from low to high mass host haloes. At face value the discrepancy with the data is highly significant, especially at the cluster scale, for haloes above log Mhalo > 14. The convolution with (correlated) observational errors reduces some of the tension. Despite the observational uncertainties, the data tend to disfavour hierarchical models characterized by a relevant contribution of disc instabilities to the formation of spheroids, strong gas dissipation in (major) mergers, short dynamical friction timescales, and very short quenching timescales in infalling satellites. We also discuss a variety of additional related issues, such as the slope and scatter in the local size-stellar mass relation, the fraction of gas in local early-type galaxies, and the general predictions on satellite galaxies.
64 - Josefa Perez 2005
We investigate the star formation activity in galaxy pairs in chemical hydrodynamical simulations consistent with a Lambda-CDM scenario. A statistical analysis of the effects of galaxy interactions on the star formation activity as a function of orbital parameters shows that close encounters (r < 30 kpc/h) can be effectively correlated with an enhancement of star formation activity with respect to galaxies without a close companion. Our results suggest that the stability properties of systems are also relevant in this process. We found that the passive star forming galaxies pairs tend to have deeper potential wells, older stellar populations, and less leftover gas than active star forming ones. In order to assess the effects that projection and interlopers could introduce in observational samples, we have also constructed and analysed projected simulated catalogs of galaxy pairs. In good agreement with observations, our results show a threshold (rp < 25 kpc/h) for interactions to enhance the star formation activity with respect to galaxies without a close companion. Finally, analysing the environmental effect, we detect the expected SFR-local density relation for both pairs and isolated galaxy samples, although the density dependence is stronger for galaxies in pairs suggesting a relevant role for interactions in driving this relation.
Recently, Hierarchical Clustering (HC) has been considered through the lens of optimization. In particular, two maximization objectives have been defined. Moseley and Wang defined the emph{Revenue} objective to handle similarity information given by a weighted graph on the data points (w.l.o.g., $[0,1]$ weights), while Cohen-Addad et al. defined the emph{Dissimilarity} objective to handle dissimilarity information. In this paper, we prove structural lemmas for both objectives allowing us to convert any HC tree to a tree with constant number of internal nodes while incurring an arbitrarily small loss in each objective. Although the best-known approximations are 0.585 and 0.667 respectively, using our lemmas we obtain approximations arbitrarily close to 1, if not all weights are small (i.e., there exist constants $epsilon, delta$ such that the fraction of weights smaller than $delta$, is at most $1 - epsilon$); such instances encompass many metric-based similarity instances, thereby improving upon prior work. Finally, we introduce Hierarchical Correlation Clustering (HCC) to handle instances that contain similarity and dissimilarity information simultaneously. For HCC, we provide an approximation of 0.4767 and for complementary similarity/dissimilarity weights (analogous to $+/-$ correlation clustering), we again present nearly-optimal approximations.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا