Sampling, Analysis, and Visualization of Particle Data Sets

• Activity Number: 672
• Type: Contributed
• Date/Time: Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistical Graphics
• Author(s): Joanne Wendelberger*+ and Jeannette Figg and Jonathon Woodring and James Ahrens
• Companies: Los Alamos National Laboratory and Los Alamos National Laboratory and Los Alamos National Laboratory and Los Alamos National Laboratory
• Keywords: sampling ; analysis ; visualization ; distribution comparisons ; particle data

Abstract

Visualization and analysis methods are required to investigate massive data sets being collected or generated by simulations. For example, because cosmology particle data sets generated from both sky surveys and simulations have increased exponentially in size in the last decade, scalable methods to visualize and store these massive particle data sets are becoming increasingly important. Sampling the data to scale down the size of a data set presents a potentially scalable method to handle ever-increasing amounts of information. In addition to reducing the computational burden of a data set, sampling has the added advantage of retaining the original data points, whereas other methods often rely on compression or averaging. Here we describe some techniques we have investigated to evaluate different sampling algorithms for spatial point data. Both visualization and quantitative techniques are described as a basis for comparing the spatial distributions of samples generated from the different sampling methods.