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Summary: Sunfall: a collaborative visual analytics system for astrophysics
Cecilia R. Aragon, Stephen J. Bailey, Sarah Poon, Karl Runge, and Rollin C. Thomas
Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720
E-mail: CRAragon@lbl.gov
Abstract. Computational and experimental sciences produce and collect ever-larger and
complex datasets, often in large-scale, multi-institution projects. The inability to gain insight
into complex scientific phenomena using current software tools is a bottleneck facing virtually
all endeavors of science. In this paper, we introduce Sunfall, a collaborative visual analytics
system developed for the Nearby Supernova Factory, an international astrophysics experiment
and the largest data volume supernova search currently in operation. Sunfall utilizes novel
interactive visualization and analysis techniques to facilitate deeper scientific insight into
complex, noisy, high-dimensional, high-volume, time-critical data. The system combines
novel image processing algorithms, statistical analysis, and machine learning with highly
interactive visual interfaces to enable collaborative, user-driven scientific exploration of
supernova image and spectral data. Sunfall is currently in operation at the Nearby Supernova
Factory; it is the first visual analytics system in production use at a major astrophysics project.
1. Introduction
Many of today's important scientific breakthroughs are being made by large, interdisciplinary
collaborations of scientists working in geographically widely distributed locations, producing and
collecting vast and complex datasets. These large-scale science projects require software tools that
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