J/other/NewA/27.41  Velocity distributions in galaxy clusters   (Sampaio+, 2014)

Velocity distributions in galaxy clusters. How to combine different normality tests. Sampaio F.S., Ribeiro A.L.B. <New Astron., 27, 41-55 (2014)> =2014NewA...27...41S 2014NewA...27...41S
ADC_Keywords: Clusters, galaxy ; Velocity dispersion Keywords: Galaxy clusters Abstract: We study 416 galaxy systems with more than 7 members selected from the 2MASS catalog. We applied five well known normality tests to the velocity distributions of these systems to distinguish Gaussian and non-Gaussian clusters. Using controlled samples, we estimated type I and II errors for each test. We verified that individual tests minimize the chances of classifying a Gaussian system as non-Gaussian, while the Fisher's meta-analysis method, a procedure to combine p-values from several statistical tests, minimizes the chances of classifying a non-Gaussian system as Gaussian. Taking the positive elements of each method and also including a modality analysis of the velocity distribution, we defined objective criteria to split up the sample into Gaussian and non-Gaussian clusters. Our analysis indicates that 50-58% of groups have Gaussian distribution, a lower fraction than that we found using individual normality tests, 71-87%. We also found that some properties of galaxy clusters are significantly different between Gaussian and non-Gaussian systems. For instance, non-Gaussian clusters have larger radii and contain more galaxies than Gaussian clusters. Finally, we discussed the importance of choosing the adequate methodology to classify galaxy systems from their velocity distributions and also the dependence of the results on the criteria used to identify clusters in galaxy surveys. Description: We study 416 galaxy systems selected from the 2MASS (Two Micron All Sky Survey Extended Source Catalog - Crook et al. (2007, Cat. J/ApJ/655/790)). We used just groups with more than 7 members to avoid severe sample size effects File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file appena.dat 49 416 Complete results for the classification of Gaussian and non-Gaussian groups taking galaxies within R200 -------------------------------------------------------------------------------- See also: J/ApJ/655/790 : Groups of galaxies in 2MASS survey (Crook+, 2007) Byte-by-byte Description of file: appena.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 3 A3 --- Group [LDC HDC] Low or High Density Contrast group 5- 8 I4 --- ID [6/1260] Group number (1) 10- 12 I3 --- N200 [8/300] Number of galaxies within R200 14- 19 F6.2 km/s sigma [43/950] Velocity dispersion σ 21- 25 F5.3 Mpc R200 [0.1/3] Virial radius, R200 27- 31 F5.2 [Msun] logM200 [11.2/15.3] Mass of galaxies within R200 33- 37 F5.2 mag m12 [-4.3/0] Magnitude difference between the first and second brightest galaxies 39- 43 F5.3 Mpc-3 v200 [0.6/4.2] Number density of galaxies (in N200*Mpc-3 unit) 45 I1 --- DP [0/1] Gaussian (0) or non-Gaussian (1) group according to the DP test 47 I1 --- MA [0/1] Gaussian (0) or non-Gaussian (1) group according to the metanalysis 49 I1 --- mod [0/1] Gaussian (0) or non-Gaussian (1) group according to the modality analysis -------------------------------------------------------------------------------- Note (1): Identification number in the Crook et al. 2007 (J/ApJ/655/790) table; <[CHM2007] LDC NNNN> or <[CHM2007] HDC NNNN> in Simbad -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Patricia Vannier [CDS] 23-Mar-2015
The document above follows the rules of the Standard Description for Astronomical Catalogues; from this documentation it is possible to generate f77 program to load files into arrays or line by line