📝 SummarXiv

Abstract

The Askaryan Radio Array (ARA), located near the South Pole, is among the first experiments there designed to detect ultra-high energy neutrinos through the Askaryan effect. When such neutrinos interact in dense media like ice, they initiate particle cascades that generate coherent radio pulses. Operating in the 150-850 MHz band, ARA is deployed 80-200 meters deep in Antarctic ice, where the radio background is exceptionally low. Despite this, experiments such as ARA must still account for continuous wave (CW) signals, which can originate from anthropogenic sources, instrumental noise, and other environmental factors. These CW signals can obscure faint neutrino-induced pulses, complicating data analysis and event identification. Over the years, ARA has developed and refined techniques for CW filtering and identification, including spectral analysis, notch filtering, and phase-variance methods. These approaches exploit CW characteristics such as their narrowband nature and persistence to separate contamination from genuine impulsive events. We review the main CW identification and filtering techniques developed within the ARA collaboration and present recent improvements in adaptive, multi-stage filtering pipelines. These advances have led to faster processing, simpler operation, and more accurate CW suppression, improving data analysis quality. Their efficacy is demonstrated across all ARA stations, underscoring their role in reducing event misclassification and enhancing performance. By refining these techniques, this work not only improves the sensitivity of ARA but also highlights the importance of robust CW filtering for current and future neutrino radio detection experiments.