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The Use of Neural Network Techniques in Very High Energy Gamma-Ray Astronomy with HAWC


Speaker:Mr. Tomás Capistrán Rojas
Affiliation:INAOE, Mexico
Date:May 26, 2017 (Friday)
Time:2:30 p.m.
Venue:Room 522, 5/F, Chong Yuet Ming Physics Building, HKU

Abstract
 

The High Altitude Water-Cherenkov (HAWC) telescope is atypical in that it is able to detect high-energy particles (from 100 GeV to 100 TeV). HAWC is operating at 4,100 meters above level sea on the slopes of the Sierra Negra Volcano, Mexico and covers an area of 22,000m2.  It works almost continuously (duty cycle > 90% ) and observes ~2/3 of the sky every day. With a year and half of HAWC data, a sky map has resulted in the detection of ~40 sources, including the Crab nebula, Markarian 421 and Markarian 501. Unfortunately, an overwhelming majority of the events that arrive at the Earth, are triggered by cosmic rays; background noise suppression plays an important role in the data process. Thus, neural networks can be used for improving the separation between gamma rays and cosmic rays and get a better sensitivity. Finally, I will discuss a new extension of the HAWC detector, known as outriggers. These additional detectors are in the process of being installed around the HAWC array and should also lead to an improvement in sensitivity of the instrument.

Coffee and tea will be served 20 minutes prior to the seminar.

Anyone interested is welcome to attend.