Session S1: Poster Session III (2:00-5:00pm)

2:00 PM–2:00 PM, Monday, April 14, 2008
Hyatt Regency St. Louis Riverfront (formerly Adam's Mark Hotel), Room: Fourth Floor Lobby

Sponsoring Unit: APS

Abstract ID: BAPS.2008.APR.S1.49

Abstract: S1.00049 : Understanding Charged Particle Backgrounds for GLAST

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  Lindsey Perry
    (Ohio State University)

Gamma Ray Bursts (GRBs), are the brightest events in our universe and last anywhere between milliseconds to a few minutes. GRBs are thought to occur when a giant star collapses into a black hole, or when two neutron stars collide. The Gamma-Ray Large Area Space Telescope (GLAST) is a satellite mission which will detect gamma ray photons which come from GRBs as well as other astrophysical phenommena. Although GLAST is designed to detect gamma rays, approximately 90 percent of the events which are downlinked are background events such as protons, electrons, and positrons. A major limitation of GLAST is the limited alloted downlink bandwidth, and so understanding these backgrounds may allow us to improve both the background rejection and gamma-ray purity of the resulting data. This analysis describes a technique for identifying backgrounds in the GLAST data sample, based on Artificial Neural Networks. Understanding the particle composition will help in the identification of true Gamma-rays, therefore impacting all science done with GLAST. GLAST is managed by NASA in partnership with the Department of Energy, and is scheduled to launch in early 2008.

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