6 papers
Computational AstroStatistics: Fast and Efficient Tools for Analysing Huge Astronomical Data Sources
R. C. Nichol, S. Chong, A. J. Connolly +10
I present here a review of past and present multi-disciplinary research of the Pittsburgh Computational AstroStatistics (PiCA) group. This group is dedicated to developing fast and…
Fast Clustering Analysis of Inhomogeneous Megapixel CMB maps
I. Szapudi, S. Prunet, S. Colombi
Szapudi et al (2001) introduced the method of estimating angular power spectrum of the CMB sky via heuristically weighted correlation functions. Part of the new technique is that a…
Fast CMB Analyses via Correlation Functions
Istvan Szapudi, Simon Prunet, Dmitry Pogosyan +2
We propose and implement a fast, universally applicable method for extracting the angular power spectrum C_l from CMB temperature maps by first estimating the correlation function…
The Variance of a New Class of N-point Correlation Estimators in Poisson and Binomial Point Processes
Istvan Szapudi, Alexander S. Szalay
We describe a set of new estimators for the N-point correlation functions of point processes. The variance of these estimators is calculated for the Poisson and binomial cases. It…
The Cosmic Distribution of Clustering
S. Colombi, I. Szapudi, the VIRGO consortium
For a given statistic, A, the cosmic distribution function, Upsilon(VA), is the probability of measuring a value VA in a finite galaxy catalog. For statistics related to count-in-c…
A New Class of Estimators for the N-point Correlations
István Szapudi, Alexander S. Szalay
A class of improved estimators is proposed for N-point correlation functions of galaxy clustering, and for discrete spatial random processes in general. In the limit of weak cluste…