Speaker
Description
The Radio Neutrino Observatory in Greenland (RNO-G) aims to detect ultra-high-energy neutrinos via Askaryan radiation, yet in-ice cosmic-ray (CR) air shower cores produce similar radio signatures that represent a significant background. While the FAERIE framework allows for high-precision modeling of these signals, its default computational requirements, which often require beyond 3,000 CPU hours per 100 PeV shower, hinder the production of the large-scale datasets necessary for deep CR studies. This work presents an optimized simulation production that implements efficient particle-handling strategies to drastically reduce computing time. By addressing computational bottlenecks, we compress processing timelines that would have spanned years into days, turning tasks that previously required years of CPU time into a matter of hours while maintaining the integrity of the radio signal’s timing, polarization, and amplitude footprint. Validations against full-scale simulations confirm that the fundamental features of the Askaryan emission, such as the Cherenkov ring structure, remain preserved within acceptable tolerances. Ultimately, this work shows how deep cosmic ray events look like with RNO-G.