Ended on 10th Oct'22 03:30 PM (Coordinated Universal Time)
Data Sprint 92 - Telescope Spectrum Classification
Classify high energy Gamma particles in atmosphere
74
Easy
Challenge Starts
07 Oct 03:30 pm
Registration Ends
10 Oct 03:30 pm
Challenge Ends
10 Oct 03:30 pm
The data set was generated by a Monte Carlo program, Corsika to simulate registration of high energy gamma particles in a ground-based atmospheric Cherenkov gamma telescope using the imaging technique. Cherenkov gamma telescope observes high energy gamma rays,
taking advantage of the radiation emitted by charged particles produced
inside the electromagnetic showers initiated by the gammas, and developing in the
atmosphere. This Cherenkov radiation (of visible to UV wavelengths) leaks
through the atmosphere and gets recorded in the detector, allowing reconstruction
of the shower parameters. The available information consists of pulses left by
the incoming Cherenkov photons on the photomultiplier tubes, arranged in a
plane, the camera. Depending on the energy of the primary gamma, a total of
few hundreds to some 10000 Cherenkov photons get collected, in patterns
(called the shower image), allowing to discriminate statistically those
caused by primary gammas (signal) from the images of hadronic showers
initiated by cosmic rays in the upper atmosphere (background).
Your Task is to make use of Machine Learning models to
classify high energy Gamma particles in atmosphere based on the features provided