Speaker
Description
High-energy cosmic rays enter Earth's atmosphere where they interact with atmospheric particles to generate charged mesons that subsequently decay into muons. As the atmosphere warms, the density decreases, increasing the mean free path of pions and kaons and therefore the probability that they decay into cosmic ray muons before undergoing a secondary interaction. This leads to a measurable positive correlation between effective atmospheric temperature and muon flux that is dependent on energy and thus depth. This behavior has been observed in many underground neutrino experiments. The Daya Bay Reactor Neutrino experiment is well suited to observe this behavior due to its three experimental halls with different level of rock overburden. In this study, we analyze the full Daya Bay dataset to extract correlation coefficients for each hall by relating the measured muon rate to the effective atmospheric temperature. We investigate multiple analysis techniques and evaluate both their advantages and limitations. In this poster, I will present our latest results and compare them to the theoretical model prediction as well as to the published results of other experiments.