Searcharxiv⌕ Search

arXiv subjects

Amy L. Connolly

Publications and source records attributed to Amy L. Connolly.

4 recordsLinked to original sources
arXiv2024

ARA-Next: a new DAQ and trigger architecture for the Askaryan Radio Array

The Askaryan Radio Array (ARA) experiment aims to detect ultra-high-energy cosmic neutrinos (>10 PeV) using radio detection techniques. To enhance ARA's capabilities, a new RFSoC-based DAQ, ARA-Next, is in the early stages of development. This advanced system will facilitate the creation of sophisticated triggers, including a novel multi-trigger approach, similar to those used in collider experiments. Our approach involves crafting and implementing innovative triggers for ARA's new DAQ, such as identifying double pulses from potential in-ice neutrino interactions, utilizing templates for atmospheric cosmic ray signals, optimizing triggers for astrophysical neutrino sources, correlating special events between ARA and IceCube, and discerning anthropogenic events using directional information. These trigger designs aim to lower thresholds and enhance ARA's detector sensitivity. Overall, this upgrade will not only enhance ARA's capabilities but also contribute to the technological advancements necessary for future experiments of this nature.

astro-ph.HE↗
arXiv2023

Discussion about a Standard Definition of the Signal-to-Noise Ratio (SNR) for Radio Signals of ultra-high-energy Particles (ARENA2022)

Signal-to-noise ratios are a widely used concept for astroparticle radio detectors, such as air-shower radio arrays for cosmic-ray measurements or detectors searching for radio signals induced by neutrino interactions in ice. Nonetheless, no common standards or methods are established for the determination of the signal-to-noise ratio: values cannot be compared between experiments, and for the same signal and noise, various methods differ by large factors on the signal-to-noise ratio. This was the motivation to discuss a community-specific standardization at the ARENA conference 2022. No agreement on a common method to calculate signal-to-noise ratios was reached, however, awareness was raised that signal-to-noise ratios need to be well defined in any publications. This includes providing sufficient information on the procedure used to determine the signal-to-noise ratio, in addition to simply stating the formula. Even when using the same definition of the signal-to-noise ratio, there is still a significant dependence on the procedure of calculation, e.g., the signal-to-noise ratio of waveforms containing only background can vary significantly depending on the size of the time interval used as signal search window. To facilitate the interpretation of any signal-to-noise ratios in a specific study, the recommendation is to also state the mean value of the signal-to-noise ratio that the used method yields when applied to noise used in the study, e.g., the radio background measured by the corresponding experiment.

astro-ph.IM↗
arXiv2017

Complex Analysis of Askaryan Radiation: A Fully Analytic Treatment including the LPM effect and Cascade Form Factor

The Askaryan effect describes coherent electromagnetic radiation from high-energy cascades in dense media with a collective charge. We present an analytic model of Askaryan radiation that accounts simultaneously for the three- dimensional form factor of the cascade, and quantum mechanical cascade elongation via the Landau-Pomeranchuk- Migdal effect. These calculations, and the associated open-source code, allow the user to avoid computationally intensive Monte Carlo cascade simulations. Searches for cosmogenic neutrinos in Askaryan-based detectors benefit from computational speed, because scans of Askaryan parameter-space are required to match neutrino signals. The Askaryan field is derived from cascade equations verified with Geant4 simulations, and compared with prior numerical and semi-analytic calculations. Finally, instructive cases of the model are transformed from the Fourier domain to the time-domain. Next-generation in situ detectors like ARA and ARIANNA can use analytic time- domain signal models to search for correlations with event candidates.

astro-ph.HE↗