A new fast parallel statistical measurement technique for computational cosmology. (2nd May 2007)

• Record Type: Journal Article
• Authors: Thacker, Robert J.; Couchman, H.M.P.
• Is Part Of: International journal of high performance computing and networking. Volume 4:Number 5/6(2006)
• Page Start: 303
• Page End: 310
• Publication Date: 2007-05-02
• Subjects: computational cosmology -- statistics -- filtering -- parallel programming -- simulation -- high performance computing -- skew -- kurtosis -- shared memory -- random sampling; High performance computing -- Periodicals; Computer networks -- Periodicals; High performance computing; Periodicals; 004.05
• Languages: English
• ISSNs: 1740-0562

Abstract

Higher order cumulants of point processes require significant computational effort to calculate, particularly when evaluated using standard methods such as counts-in-cells. While newer techniques based on tree algorithms are more efficient, they still suffer from shot noise problems in homogeneous systems. We present a new algorithm for calculating higher order moments using Fourier methods. A filtering technique is used to suppress noise, and this approach allows us to calculate skew and kurtosis even when the point process is highly homogeneous. The algorithm can be implemented efficiently in a shared memory parallel environment provided a data-local random sampling technique is used.