Fast Algorithms and Efficient Statistics: N-point Correlation Functions
摘要
We present here a new algorithm for the fast computation of N-point correlation functions in large astronomical data sets. The algorithm is based on kdtrees which are decorated with cached sufficient statistics thus allowing for orders of magnitude speed-ups over the naive non-tree-based implementation of correlation functions. We further discuss the use of controlled approximations within the computation which allows for further acceleration. In summary, our algorithm now makes it possible to compute exact, all-pairs, measurements of the 2, 3 and 4-point correlation functions for cosmological data sets like the Sloan Digital Sky Survey (SDSS; York et al. 2000) and the next generation of Cosmic Microwave Background experiments (see Szapudi et al. 2000).
引用
@article{arxiv.astro-ph/0012333,
title = {Fast Algorithms and Efficient Statistics: N-point Correlation Functions},
author = {Andrew Moore and Andy Connolly and Chris Genovese and Alex Gray and Larry Grone and Nick Kanidoris and Robert Nichol and Jeff Schneider and Alex Szalay and Istvan Szapudi and Larry Wasserman},
journal= {arXiv preprint arXiv:astro-ph/0012333},
year = {2009}
}
备注
To appear in Proceedings of MPA/MPE/ESO Conference "Mining the Sky", July 31 - August 4, 2000, Garching, Germany