Topology of the Galaxy Distribution in the Hubble Deep Fields

2001 ◽  
Vol 553 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Changbom Park ◽  
J. Richard Gott III ◽  
Y. J. Choi
2001 ◽  
Vol 204 ◽  
pp. 71-85 ◽  
Author(s):  
Lucia Pozzetti ◽  
Piero Madau

We discuss the ultraviolet to near-IR galaxy counts from the deepest imaging surveys, including the northern and southern Hubble Deep Fields. The logarithmic slope of the galaxy number-magnitude relation is flatter than 0.4 in all seven UBVIJHK optical passbands at faint magnitudes, i.e. the light from resolved galaxies has converged from the UV to the near-IR. Most of the galaxy contribution to the extragalactic background light (BEL) comes from relatively bright, low-redshift objects (50% at VAB ≲ 21 and 90% at VAB ≲ 25.5). We find a lower limit to the surface brightness of the optical EBL of about 15 nW m−2 sr−1, comparable to the intensity of the far-IR background from COBE data. Diffuse light, lost because of surface brightness selection effects, may add substantially to the EBL.


2002 ◽  
Author(s):  
Philippe Querre ◽  
Jean-Luc Starck ◽  
Vicent J. Martinez

2020 ◽  
Vol 497 (4) ◽  
pp. 4077-4090 ◽  
Author(s):  
Suman Sarkar ◽  
Biswajit Pandey

ABSTRACT A non-zero mutual information between morphology of a galaxy and its large-scale environment is known to exist in Sloan Digital Sky Survey (SDSS) upto a few tens of Mpc. It is important to test the statistical significance of these mutual information if any. We propose three different methods to test the statistical significance of these non-zero mutual information and apply them to SDSS and Millennium run simulation. We randomize the morphological information of SDSS galaxies without affecting their spatial distribution and compare the mutual information in the original and randomized data sets. We also divide the galaxy distribution into smaller subcubes and randomly shuffle them many times keeping the morphological information of galaxies intact. We compare the mutual information in the original SDSS data and its shuffled realizations for different shuffling lengths. Using a t-test, we find that a small but statistically significant (at $99.9{{\ \rm per\ cent}}$ confidence level) mutual information between morphology and environment exists upto the entire length-scale probed. We also conduct another experiment using mock data sets from a semi-analytic galaxy catalogue where we assign morphology to galaxies in a controlled manner based on the density at their locations. The experiment clearly demonstrates that mutual information can effectively capture the physical correlations between morphology and environment. Our analysis suggests that physical association between morphology and environment may extend to much larger length-scales than currently believed, and the information theoretic framework presented here can serve as a sensitive and useful probe of the assembly bias and large-scale environmental dependence of galaxy properties.


1983 ◽  
Vol 104 ◽  
pp. 265-271 ◽  
Author(s):  
J. Einasto ◽  
A. Klypin ◽  
S. Shandarin

So far the galaxy correlation analysis was the only quantitative method used to describe the distribution of galaxies in space. Here we consider other numerical methods to treat impersonally various aspects of the galaxy distribution.


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