On Shadow of the Moon in Extensive Air Shower Data

TL;DR

This paper introduces a novel method to detect the moon's shadow in extensive air shower data by comparing event counts in error circles centered on the moon versus random sky locations, using a theoretical model to interpret the shadow.

Contribution

It presents a new technique and theoretical model for analyzing the moon's shadow in extensive air shower data, applied to a large dataset from Alborz observatory.

Findings

Detected the moon's shadow in extensive air shower data.

Quantified the shadow's physical parameters.

Validated the technique with 1.7×10^5 events.

Abstract

A new technique has been devised for the analysis of extensive air shower data in observing the effect of the moon on this data. In this technique the number of EAS events with arrival directions falling in error circles centered about the moving moon is compared to the mean number of events falling in error circles with centers randomly chosen in the sky. For any assumed angular radius of the error circle the deficit in EAS event count in the direction of moon i.e., Nsky-Nmoon which is a moon-related effect is interpreted as the shadow of the moon. A simple theoretical model has been developed to relate Nsky to the angular radius of the error circle and has been applied to the counts from the moon's direction in order to extract the physical parameters of the shadow of the moon. The technique and the theoretical model has been used on 1.7 *10^5 EAS events recorded at Alborz observatory.