Computer Science – Learning
Scientific paper
Jan 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21733417d&link_type=abstract
American Astronomical Society, AAS Meeting #217, #334.17; Bulletin of the American Astronomical Society, Vol. 43, 2011
Computer Science
Learning
Scientific paper
The Catalina Real-time Transient Survey (CRTS) is an open optical transient survey that covers 3/4 of the entire sky in a search of transient astrophysical phenomena occurring on timescales of minutes to years. Observational data is derived from the three telescopes of the Catalina Sky Survey which cover up to 2,500 square degrees of sky each night. CRTS has so far discovered more that 2000 transient sources including 600 supernovae, 500 dwarf novae and more than 100 Blazars and UV Ceti variables. All data is processed within minutes of observation and discoveries are openly distributed using SkyAlert and VOEvent technologies as well as iPhone, html tables, RSS and Twitter feeds. Events are classified utilizing data from virtual observatory enabled archives, machine learning, and collaborative Citizen science.
Beshore Edward
Catelan Márcio
Christensen Erik
Djorgovski Stanislav G.
Donalek Ciro
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