ANN-based energy reconstruction procedure for TACTIC gamma-ray telescope and its comparison with other conventional methods
V.K.Dhar, A.K.Tickoo, M.K.Koul, R.C.Rannot, K.K.Yadav, P.Chandra,, B.P.Dubey, R.Koul

TL;DR
This paper introduces a novel ANN-based energy reconstruction method for the TACTIC gamma-ray telescope, which improves accuracy by considering zenith angle dependence and outperforms traditional methods in energy estimation.
Contribution
The paper develops and validates a new ANN-based energy reconstruction procedure that incorporates zenith angle effects, demonstrating superior performance over conventional methods.
Findings
ANN method achieves ~26% energy resolution.
ANN method considers zenith angle dependence.
Validated by Crab Nebula energy spectrum measurement.
Abstract
The energy estimation procedures employed by different groups, for determining the energy of the primary -ray using a single atmospheric Cherenkov imaging telescope, include methods like polynomial fitting in SIZE and DISTANCE, general least square fitting and look-up table based interpolation. A novel energy reconstruction procedure, based on the utilization of Artificial Neural Network (ANN), has been developed for the TACTIC atmospheric Cherenkov imaging telescope. The procedure uses a 3:30:1 ANN configuration with resilient backpropagation algorithm to estimate the energy of a -ray like event on the basis of its image SIZE, DISTANCE and zenith angle. The new ANN-based energy reconstruction method, apart from yielding an energy resolution of 26%, which is comparable to that of other single imaging telescopes, has the added advantage that it considers zenith…
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Taxonomy
TopicsAstrophysics and Cosmic Phenomena · Radiation Detection and Scintillator Technologies · Particle Detector Development and Performance
