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M. Karthik

Publications and source records attributed to M. Karthik.

2 recordsLinked to original sources

Monitoring the upper atmospheric temperature and interplanetary magnetic field with the GRAPES-3 muon telescope

We study the influence of variations in the upper atmospheric temperature and interplanetary magnetic field on the cosmic ray induced atmospheric muon flux measured by the GRAPES-3 experiment over 22 years (2001--2022) of data; spanning three solar cycles: the declining phase of Solar Cycle 23, the full Cycle 24, and the rising and maximum phases of Cycle 25. Located in Ooty- India, the GRAPES-3 large area (560\,$m^2$) muon telescope detects $\sim$4 billion muons daily above 1\,GeV, with an angular resolution of $\sim$4$^\circ$, enabling a statistical precision $<$0.01\% on the hourly muon rate. After accounting for the effect of atmospheric pressure variations, we compare this data with the upper atmospheric temperature inferred from NASA's MERRA-2 dataset as well as magnetic field data from the ACE and WIND spacecraft at Lagrange point L1. A simultaneous iterative fitting method employing Fast Fourier Transforms and a narrow band-pass filter reveals the temperature and magnetic field coefficients to be $\alpha_T=-\,0.2241\,\pm\,0.04\, (stat.)\,\pm\,0.0220\, (syst.)\,\%\,K^{-1}$ and $\gamma_{M}=-\,0.574\,\pm\,0.027\, (stat.)\,\pm\,0.011\, (syst.)\,\%\,\text{nT}^{-1}$, respectively, for an assumed hadronic attenuation length $\lambda$=120 g cm$^{-2}$, underscoring the potential of the GRAPES-3 muon telescope to serve as a real time monitor of the upper atmospheric temperature or interplanetary magnetic field.

astro-ph.HE

An automated algorithmic method to mitigate long-term variations in the efficiency of the GRAPES-3 muon telescope

The GRAPES-3 large area muon telescope with its sixteen independent modules records the high energy (>1 GeV) muons continuously over 2.3 sr of the sky. However, the recorded muon rates are contaminated by instrumental effects and instabilities spanning both short- and long-timescales, such as variations in the efficiency of the detector. We present an automated, algorithmic method, which employs Bayesian blocks to discretize the data stream into periods and exploits the correlations among the sixteen independent modules of the muon telescope to separate the impact of these instrumental problems from those originating in physical effects of interest, allowing the Savitzky-Golay filter to be employed to mitigate the former. Compared to legacy methods, this method is less dependent on subjective input from experimental operators and provides a data stream free of all known instrumental effects over calendar years. The muon rate obtained with the new method shows a fairly better correlation with neutron monitor data, than that obtained with the legacy method.

astro-ph.IM