of a Boolean grain model with boundary correction

email: buchert@obs.univ-lyon1.fr

Minkowski functionals are discussed in all the references below. The computational method for a Boolean grain model without boundary conditions is discussed in [1,2]. The computational method for boundaries is a generalization of this method [4,5]. The deconvolution of the boundaries is discussed in [4,5,6]. We used this program to calculate the Minkowski functionals of Abell/ACO clusters as shown in [6]. Related applications may be found in [3,7,8,9].

get a list of options and the actual (default) values of the parameters.

boxmin -n 100 -T -l 10 -o box.res

calculate the Minkowskifunctionals of 10 realization of a Poisson process with 100 points within a cube of sidelength 1, the corresponding theoretical values for a Poisson process, and save both in the file box.res

clustermin -n600 -icdm -l1 -r0.0 -R0.12 -d0.005 -H1 -s99.2857143 -T -ocdm_n.res

calculate the Minkowskifunctionals of a mock cluster catalogue.

-n600 :

to get enough memory for 600 clusters (well somehow a feature)

-icdm :

use file cdm.1

-l1 :

use only one file (no variance)

-r0.0 -R0.12 -d0.005 :

perform the calculation starting with radius 0.0 up to radius 0.12 with stepsize 0.005

-H1 :

calculate for northern hemisphere

-s99.2857143 :

use only 99.3% of the cluster (to get the correct number density of the Abell/ACO)

-T :

calculate the theoretical results for poisson process with same number density -ocdm_n.res :

save the results in cdm_n.res

- The input procedure for the cluster data used in reference [6] is in the file cluster.c .

- There is a lot of documentation in the source code.

- The Program calculates the volume densities v of the V-measures.

- If several realizations are drawn, the program computes the mean and the standard error of the v-measures.

- The file minkowski.sm includes SuperMongo plotting routines.

[2] Thomas Buchert (1996): `Robust morphological measures for large-scale structure', in:

[3] M. Platzöder, T. Buchert (1995): `Application of Minkowski functionals to the statistical analysis of dark matter models', in:

[4] Jens Schmalzing, Martin Kerscher and Thomas Buchert (1996): `Minkowski functionals in Cosmology', in:

[5] Martin Kerscher, Jens Schmalzing and Thomas Buchert (1996): `Analyzing Galaxy Catalogues with Minkowski Functionals', in:

[6] Martin Kerscher, Jens Schmalzing, J&oumrg Retzlaff, Stefano Borgani, Thomas Buchert, Stephan Gottlöber, Volker Müller, Manolis Plionis and Herbert Wagner (1997): `Minkowski Functionals of Abell/ACO clusters',

[7] Martin Kerscher, Jens Schmalzing, Thomas Buchert and Herbert Wagner (1998): `Fluctuations in the IRAS 1.2 Jy catalogue',

[8] Martin Kerscher, Klaus R. Mecke, Jens Schmalzing, Claus Beisbart, Thomas Buchert and Herbert Wagner (2001): `Morphological fluctuations of large-scale structure: The PSCz survey',

[9] C. Hikage, J. Schmalzing, T. Buchert, Y. Suto, I. Kayo, A. Taruya, Michael S. Vogeley, F. Hoyle, J.R. Gott III and J. Brinkmann (2003): `Minkowski Functionals of SDSS Galaxies I : Analysis of Excursion Sets',