Search for TeV $gamma$--ray emission from blazar 1ES1218+304 with TACTIC telescope during March-April 2013

In this paper, we present results of TeV $gamma$--ray observations of the high synchrotron peaked BL Lac object 1ES 1218+304 (z=0.182) with the $TACTIC$ (TeV Atmospheric Cherenkov Telescope with Imaging Camera). The observations are primarily motivated by the unusually hard GeV-TeV spectrum of the source despite its relatively large redshift. The source is observed in the TeV energy range with the $TACTIC$ from March 1, 2013 to April 15, 2013 (MJD 56352--56397) for a total observation time of 39.62 h and no evidence of TeV $gamma$--ray activity is found from the source. The corresponding 99$%$ confidence level upper limit on the integral flux above a threshold energy of 1.1 TeV is estimated to be 3.41 $times10^{-12}$ photons cm$^{-2}$ s$^{-1}$ (i.e $<23%$ Crab Nebula flux) assuming a power law differential energy spectrum with photon index 3.0, as previously observed by the $MAGIC$ and $VERITAS$ telescopes. For the study of multi-wavelength emission from the source, we use nearly simultaneous optical, UV and and X--ray data collected by the UVOT and XRT instruments on board the emph{Swift} satellite and high energy $gamma$--ray data collected by the Large Area Telescope on board the emph{Fermi} satellite. We also use radio data at 15 GHz from OVRO 40 m telescope in the same period. No significant increase of activity is detected from radio to TeV $gamma$--rays from 1ES1218+304 during the period from March 1, 2013 to April 15, 2013.

Artificial Neural Network based gamma-hadron segregation methodology for TACTIC telescope

The sensitivity of a Cherenkov imaging telescope is strongly dependent on the rejection of the cosmic-ray background events. The methods which have been used to achieve the segregation between the gamma-rays from the source and the background cosmic-rays, include methods like Supercuts/Dynamic Supercuts, Maximum likelihood classifier, Kernel methods, Fractals, Wavelets and random forest. While the segregation potential of the neural network classifier has been investigated in the past with modest results, the main purpose of this paper is to study the gamma / hadron segregation potential of various ANN algorithms, some of which are supposed to be more powerful in terms of better convergence and lower error compared to the commonly used Backpropagation algorithm. The results obtained suggest that Levenberg-Marquardt method outperforms all other methods in the ANN domain. Applying this ANN algorithm to $sim$ 101.44 h of Crab Nebula data collected by the TACTIC telescope, during Nov. 10, 2005 - Jan. 30, 2006, yields an excess of $sim$ (1141$pm$106) with a statistical significance of $sim$ 11.07$sigma$, as against an excess of $sim$ (928$pm$100) with a statistical significance of $sim$ 9.40$sigma$ obtained with Dynamic Supercuts selection methodology. The main advantage accruing from the ANN methodology is that it is more effective at higher energies and this has allowed us to re-determine the Crab Nebula energy spectrum in the energy range $sim$ 1-24 TeV.