| Name: | Mani Khurana |
| Affiliation: | Bhabha Atomic Research Centre |
| Conference ID : | ASI2023_274 |
| Title : | Implementation of Island Image Cleaning Method for the MACE Telescope |
| Authors : | M. Khurana, P. Chandra, C. Borwankar, K. K. Yadav |
| Mode of Presentation: | Poster |
| Abstract Category : | Instrumentation and Techniques |
| Abstract : | Major Atmospheric Cherenkov Experiment (MACE) is a gamma-ray telescope recently installed at Hanle, Ladakh. The telescope plays an important role in the study of very-high-energy (VHE) gamma-ray Universe above 20 GeV. This telescope works on the principle of IACT (Imaging Atmospheric Cherenkov technique), where Cherenkov photons produced by secondary particles in the extensive air shower are collected by a large reflector and recorded using an array of Photo Multiplier tubes. The challenge in this technique is to remove the night sky contribution in the image and huge cosmic-ray backgrounds to retrieve the signal from a gamma ray source. Aiming to reconstruct the complete image of the shower we have developed the algorithm to implement the island image cleaning method. Static Cuts and the Machine Learning algorithm have been implemented to segregate the gamma rays from the cosmic background. A validation of this study has been done by calculating the significance using the Island and the standard cleaning method. The observed superiority of the island method over the standard cleaning method using both simulation and observation data will be presented in this meeting. |
