Документ взят из кэша поисковой машины. Адрес оригинального документа : http://www.eso.org/~evkampen/Research.pdf
Дата изменения: Tue Nov 17 14:11:37 2009
Дата индексирования: Mon Oct 1 22:28:43 2012
Кодировка:

Поисковые слова: http news.cosmoport.com 2005 04 22 1.htm
OVERVIEW OF CURRENT INDEPENDENT RESEARCH Dr. Eelco van Kampen
Overview There are many op en questions in the research fields that I work on, and a great deal of activity worldwide, but I have b een able to make significant contributions, in particular relating to the following op en science questions: (1) the ep och of galaxy formation and their star formation history (2) the effect of environmental processes on star formation in galaxies (3) the enrichment of the intra-cluster medium from stripp ed galaxies (4) the imp ortance of dusty starbursts in the formation and evolution of galaxies High-redshift sub-mm galaxies Modelling the formation and evolution of galaxies is inherently difficult due to the complex interplay of the multitude of physical processes that play a r^le. I use a phenomenological model in order to o study large p opulations of galaxies, which is not currently p ossible using detailed hydrodynamical models. I have added various new ingredients to make the modelling as realistic as p ossible, which help ed resolving the problem of solving b oth the luminosity function as well as the Tully-Fisher relation that plagues attempts by many other groups.

Figure 1: An example of a 30'в30' simulated sub-mm map, containing a proto-cluster at z=2.5, as wil l be observed with SCUBA-2 on the JCMT. ALMA wil l be the instrument of choice to resolve the cluster galaxies.


Nevertheless, my resolution of the Tully-Fisher / luminosity function discrepancy may well not b e unique; the way forward to resolve any worries ab out degeneracies in the cosmological / physical parameter space will b e to include data at high redshifts. Most of the bright sources found in sub-mm maps are dust-enshrouded starburst galaxies at intermediate or high redshifts, so this typ e of sources are ideal for this purp ose. This requires an extensive effort to include realistic modelling of dust-enshrouded star-burst galaxies, including their sub-mm, infrared, and optical luminosities, and their clustering prop erties, which is what I have b een doing with Daniel Clarke (Innsbruck), Jim Dunlop (Edinburgh), Gian Luigi Granato (Padova) and Laura Silva (Trieste). The dust production dep ends on the star formation rate, which follows directly from the phenomenological galaxy formation model, so at all times we know how much dust is forming. However, one still needs to understand what happ ens to this dust. It is clear that dust formed during a star bursting event will at least temp orarily obscure the star bursting region, a situation that directly applies to the brightest sources seen in sub-mm maps. Thus, knowing the amount of dust alone gives much insight into how much star formation might be hidden from view. In order to test my models for the sub-mm p opulation, I joined various consortia that are or will b e acquiring large samples in this waveband. These consortia are listed separately as part of this application. For all these consortia I am mostly involved in producing simulations; an example of a mock SCUBA-2 survey of a proto-cluster at z 2.5 is shown in Figure 1. However, in order to truely understand the intricacies of taking data in these bands nothing b eats doing a few observing runs yourself, hence I did two runs for the SHADES consortium in Novemb er 2003 and Novemb er 2004. Two of the most interesting predictions that can b e tested observationally are the clustering prop erties of high-redshift sub-mm sources, and their intrinsic redshift distributions. Due to the nature of these sources, most likely b eing dust-enshrouded starburst galaxies, clustering is exp ected to b e strong, and can well b e observed. Indeed, after all data for the SHADES pro ject (http://www.roe.ac.uk/ifa/shades) was taken and reduced, I did detect clustering (pap er in preparation) in the angular correlation function w( ), as shown in Fig. 2. I will p erform a similar analysis for the much larger Herschel-ATLAS sample, which will b ecome available during 2010.

Figure 2: Angular clustering w( ) for SHADES, for > 6 mJy sources from both SHADES fields combined. Stars show the sky-averaged correlation function. The dashed line is a fit to this function, whereas the solid line is a fit to w( ) itself, which is indicated by the large dots (incl. error bars).


Star bursting, ram-pressure stripping, and other environmental processes Dep ending on environment, physical processes like induced starbursts and ram-pressure stripping may play an imp ortant role in controlling the amount and distribution of cold gas available for star formation, and therefore the evolution of galaxies, including morphological transformation. For the highest density environments, galaxy clusters, there exists a large volume of optical, radio, and X-ray data, so modelling these processes in cluster environments in detail can provide p owerful constraints on the models. However, such constraints are only b elievable if the modelling is sufficiently realistic. For this reason I have combined my galaxy formation recip e with sophisticated hydrodynamical simulations, in collab oration with researchers in Innsbruck and Edinburgh. Mo ck galaxy clusters, sup erclusters, and surveys My galaxy formation model produces a sample of haloes that each contain a numb er of galaxies ab ove a certain luminosity threshold, which is called the galaxy `occupation numb er'. This numb er and its variation with mass are the main ingredients that determine the quantitative degree of bias in the galaxy distribution. Once understood, one can apply it to produce mock galaxy surveys, and compare these to observed surveys to test theories of structure formation. I am currently involved in GAMA (for details, see http://www.eso.org/jliske/gama/) for this purp ose, where I also take part in the observational efforts. An idealized nearby galaxy survey would b e limited by luminosity alone; however, an equally imp ortant practical limitation is the minimum surface brightness of a galaxy. Thus, an obstacle for the interpretation of galaxy survey data is that the consequences of the surface brightness limit needs to b e understood. My galaxy formation model does predict surface brightness, so I am in an excellent p osition to do this. I use the COMBO-17 and the Millenium Galaxy Catalogue, and again the GAMA survey, for this purp ose. A useful method to build a model of a sp ecific observed large-scale overdensity is an iterative one: changing constrained initial constraints after each run so that the next run compares b etter to that cluster. Once we have a good model for the sp ecific cluster in terms of a set of initial constraints, we assess the likelihood of forming that cluster as a function of cosmological parameters, b ecause the probability distributions of these initial constraints are known. I currently apply this technique to a whole range of clusters, and also to sup erclusters, including the A901/A902 sup ercluster pro ject called STAGES, led by Meghan Gray (Nottingham). The latter, STAGES (for details, see http://www.nottingham.ac.uk/ppzmeg/stages), has b een very successful so far, resulting in a large multi-wavelength dataset and the highest-resolution weaklensing map ever produced. I have produced the first mocks for this survey, and we are now in the process of comparing these to the observations.