ScienceProblem: GalaxyClustering

PrimaryActor:

astronomer


ScienceGoal:

Aim to address the evolution of galaxy populations in clusters. Comparison can then be made with n-body model data.


DataSets:

multicolour optical survey data sets (e.g. DPOSS)


ProblemDescription:

Clusters of galaxies can be used to trace distribution of matter in the universe over large scales. Clusters are typically X-ray (see e.g. XrayGalaxyClusterSurvey) or optically selected. Many optically selected cluster samples have suffered from various selection effects - such as the use of only one colour data (e.g. Dalton et al, 1992).

New techniques (e.g. Gal et al, 2000) select clusters using multicolour data to localise clusters which are predicted to contain an overabundance of red, early type galaxies. Cluster identification using [[VO.OpticalNearIRGalaxyClusterSelection] [Optical and Near-IR data]] uses positional information to select clusters (e.g. Gladders & Yee, 2000)

Cluster distributions can be compared to matter distributions generated by e.g. Lambda CDM models (e.g. Nagamine et al, 2001) or Warm Dark Matter models (e.g. Bode et al, 2001). These models now have sufficient resolution to show dwarf galaxies.


CurrentSolution:

Procedure is to select sources marked as galaxies, select only those in a particular locus of the (g-r) vs (i-r) colour space, and then create density maps (see e.g. Gal et al, 2000).

Redshifts are determined photomterically and spectrscopically. For clusters found, a serach on cluster members would be required cross referenced against possible spectroscopic data on galaxies in those clusters to fix the spectrscopic redshift to the galaxy. This could require searching information contained within e.g. NED


VOSolution:

Application to deeper surveys would allow clusters at higher redshifts to be located. (DPOSS works to z ~ 0.3). Application to surveys with more colours (e.g. Opt+IR) would enable higher precision cluster selection

Large n-body code model outputs will need to be compared with real observed cluster distributiosns. Issues include interfacing to large model data sets, vizualisation of model vs real data - e.g. matter vs clusters at ranges of redshit, statistical correlations etc. .


Iteration Breakdown:


KeyReferences:

Bode et al, 2001, ApJ, 556 93

Dalton et al, 1992, ApJ, 390, 1

Gal et al, 2000, AJ, 119, 12

Gladders & Yee, 2000, AJ, 120, 2148, 'A New Method For Galaxy Cluster Detection. I. The Algorithm'

Nagamine et al, 2001, ApJ, 558, 497, 'Star Formation History and Stellar Metallicity Distribution in a Cold Dark Matter Universe'



GoodStyle: Please add comments below. This area should be used for refinement of the above document. If you want to ask questions or start a dialogue with the author, please use (or create) a topic in the Science Problems Forum. For other ScienceProblems, refer to the ScienceProblemList.
Author: Once the refinements here and comments in the forum die down, perhaps you could rewrite the problem, incorporating the comments and refinements.

This and the Opt/IR case OpticalNearIRGalaxyClusterSelection and the X-ray cluster case VO.XrayGalaxyClusterSurvey will be key AstroGrid drivers.


Links to AVO Science Cases

This case is a useful front end to the Galaxy Clusters case being developed in the context of the AVO 2005 Demo.


-- NicholasWalton - 17 Apr 2002


UseCaseDesign:

GalaxyClusteringSD sequence diagramme


Associated UseCases

See also CommonGroup of use cases

LibraryFunctions needed include: AstrometryBootstrap; Calculate colour; Create density map; Compare results of models using different cosmological parameters; Calculate K correction

Specific use cases

DetermineModel

ComputeNumberDensity

GalaxyMorphologyRecognition

RedshiftDetermination

PhotometrySearch

-- AnitaRichards - 31 Jul 2002 -- NicholasWalton - 24 Jan 2002

Topic revision: r12 - 2004-07-22 - 18:48:50 - NicholasWalton
 
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