Ponente
Descripción
Astrophysical flares are among the prime candidates for the production of ultra-high-energy (UHE, E > 10¹⁷ eV) cosmic rays. The trajectory of UHE neutral particles, such as photons, is not deflected in the presence of cosmic magnetic fields, in contrast with that of UHE charged particles, leading to a predictable clustering of events observed on Earth, correlated temporally and directionally. Identification of sources of such UHE neutral particles will help us probe extreme-energy particle acceleration and the non-thermal universe.
We present two unbinned likelihood-based direction-time clustering algorithms: One approach focuses on the examination of multiplets (multiple consecutive events), whereas the other one utilizes the stacking method, which examines selected doublets (pairs of consecutive events). These algorithms process events representing extensive air showers detected by cosmic ray observatories. We also incorporate an additional discriminating factor, termed the photon tag, which distinguishes between signal (photon-initiated events) and background (hadron-initiated events) based on their respective probability distribution functions.
We demonstrate the effectiveness of the stacking method supplemented with the photon tag in correctly identifying the number of flares and their durations within the given data. We also highlight the robustness of this method in identifying a flare, as it requires only a few events. This method can further enhance UHE source detection by either identifying candidate flares or improving the detection limits of UHE photon fluxes.
