2003/10/31 by H. K. Eriksen, P. B. Lilje, A. J. Banday +1
Engineering · Environmental Science · Mathematics · Physics and Astronomy · #Computation #Initialization #Monte Carlo method #Morphological variations and asymmetry #Multiplet #Remote Sensing in Agriculture #Satellite Image Processing and Photogrammetry #Set (abstract data type) #Sky #astro-ph
paper · pdf · doi:10.1086/381740
published as Astrophys.J.Suppl. 151 (2004) 1-11 · 11 pages, 8 figures, accepted for publication in ApJS; textual improvements, references updated
arxiv created 2004/01/23 · openalex publication_date 2004/02/25 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
We develop, implement and test a set of algorithms for estimating N -point correlation functions from pixelized sky maps. These algorithms are slow, in the sense that they do not break the ( N ) barrier, and yet, they are fast enough for efficient analysis of data sets up to several hundred thousand pixels. The typical application of these methods is Monte Carlo analysis using several thousand realizations, and therefore we organize our programs so that the initialization cost is paid only once. The effective cost is then reduced to a few additions per pixel multiplet (pair, triplet, etc.). Further, the algorithms waste no CPU time on computing undesired geometric configurations, and, finally, the computations are naturally divided into independent parts, allowing for trivial (i.e., optimal) parallelization.