Crab Analysis and Comparison of RF and CNN method of Reconstruction

Neshat, Rumman (2023) Crab Analysis and Comparison of RF and CNN method of Reconstruction. Masters thesis, Indian Institute of Science Education and Research Kolkata.

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The cosmic ray with the highest energies helps us to understand the composition and evolution of the universe. Because of the Magnetic field, it encounters on its way toward Earth, charged particle gets deflected; thus it’s difficult to trace its origin. However, the Very High Energy gamma-ray photon being neutral doesn’t get deflected and hence is used to study the source from where it is coming. In this thesis I have worked on the analysis of the Crab Nebula and Pulsar using both the MAGIC as well as Fermi-Lat Telescope. MAGIC being the ground-based telescope, could detect up to TeV Energies. With the introduction of Sum Trigger, it could also detect low-energy events up to 25 GeV. I have analyzed the Crab Pulsar using the Sum Trigger and produced the phasogram plot for it. I have also worked on the comparison of the reconstruction method by the MAGIC, which gives direction, energy, hadronness of the events. The two method that is compared uses Random Forest Machine Learning Algorithm and the Convolutional Neural Network(CNN) for reconstruction, respectively. For this, the analysis results for 20 hours of Crab Pulsar data is used. The other telescope that detects these VHE gamma-ray photons is Fermi-Lat which is space-based and measures from 20 MeV to 300 GeV only. I have analyzed the data from 2010-2018 to study the Crab Pulsar flux and to characterize the flares from the Crab Pulsar that were also observed in the years 2011 and 2007.

Item Type: Thesis (Masters)
Additional Information: Supervisor: Prof. Mosè Mariotti, UniPd, Italy; Co-Supervisiors: Dr. Rubén López Coto, IAA-CSIC, Spain and Dr. Alessia Spolon, UniPD, Italy
Uncontrolled Keywords: Crab Nebula; Fermi-Lat Telescope; MAGIC Telescope; Pulsar
Subjects: Q Science > QC Physics
Divisions: Department of Physical Sciences
Depositing User: IISER Kolkata Librarian
Date Deposited: 24 Nov 2023 10:45
Last Modified: 24 Nov 2023 10:45

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