A Statistical Approach to Recognizing Source Classes for Unassociated Sources in the Second Fermi-LAT Catalog.

Details A Statistical Approach to Recognizing Source Classes for Unassociated Sources in the Second Fermi-LAT Catalog. A Statistical Approach to Recognizing Source Classes for Unassociated Sources in the Second Fermi-LAT Catalog.

Jan 2012

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012aas...21921308m&link_type=abstract

American Astronomical Society, AAS Meeting #219, #213.08

Mathematics

Probability

Scientific paper

We have developed a new and innovative technique to classify Fermi sources based solely on their observed gamma-ray properties. Our technique, based on Classification Trees, uses the properties of known objects to build a classification analysis which provides the probability for an unidentified source to belong to a given astronomical class (Pulsar, AGN,...).
We have applied this technique to the second Fermi-LAT source catalog (2FGL), and computed a classification probability for each unidentified source. This provides a clearer picture of the unidentified source population and extends the number of interesting candidate objects, thus helping the community in scheduling multiwavelength observations.

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