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2016 IEEE Pacific Visualization Symposium (PacificVis) (2016)
Taipei, Taiwan
April 19, 2016 to April 22, 2016
ISSN: 2165-8773
ISBN: 978-1-5090-1451-4
pp: 48-55
Annie Preston , University of California at Davis
Ramyar Ghods , University of California at Davis
Jinrong Xie , University of California at Davis
Franz Sauer , University of California at Davis
Nick Leaf , University of California at Davis
Kwan-Liu Ma , University of California at Davis
Esteban Rangel , Northwestern University
Eve Kovacs , Argonne National Laboratory
Katrin Heitmann , Argonne National Laboratory
Salman Habib , Argonne National Laboratory
Cosmological simulations produce a multitude of data types whose large scale makes them difficult to thoroughly explore in an interactive setting. One aspect of particular interest to scientists is the evolution of groups of dark matter particles, or "halos," described by merger trees. However, in order to fully understand subtleties in the merger trees, other data types derived from the simulation must be incorporated as well. In this work, we develop a novel interactive linked-view visualization system that focuses on simultaneously exploring dark matter halos, their hierarchical evolution, corresponding particle data, and other quantitative information. We employ a parallel remote renderer and a local merger tree selection tool so that users can analyze large data sets interactively. This allows scientists to assess their simulation code, understand inconsistencies in extracted data, and intuitively understand simulation behavior on all scales. We demonstrate the effectiveness of our system through a set of case studies on large-scale cosmological data from the HACC (Hardware/Hybrid Accelerated Cosmology Code) simulation framework.
J.2 [Physical Sciences and Engineering]: Astronomy, I.6.4 [Simulation and Modeling]: Simulation Output Analysis

A. Preston et al., "An integrated visualization system for interactive analysis of large, heterogeneous cosmology data," 2016 IEEE Pacific Visualization Symposium (PacificVis)(PACIFICVIS), Taipei, Taiwan, 2016, pp. 48-55.
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