Reconstructing non-repeating radio pulses with Information Field Theory. Issue 4 (27th April 2021)

• Record Type: Journal Article
• Authors: Welling, C.; Frank, P.; Enßlin, T.; Nelles, A.
• Is Part Of: Journal of cosmology and astroparticle physics. Volume 2021:Issue 4(2021)
• Publication Date: 2021-04-27
• Subjects: cosmic rays detectors -- neutrino detectors -- ultra high energy cosmic rays -- ultra high energy photons and neutrinos; Cosmology -- Periodicals; Astrophysics -- Periodicals; 523.0105
• DOI: 10.1088/1475-7516/2021/04/071
• Languages: English
• ISSNs: 1475-7516

Abstract

Abstract: Particle showers in dielectric media produce radio signals which are used for the detection of both ultra-high energy cosmic rays and neutrinos with energies above a few PeV. The amplitude, polarization, and spectrum of these short, broadband radio pulses allow us to draw conclusions about the primary particles that caused them, as well as the mechanics of shower development and radio emission. However, confidently reconstructing the radio signals can pose a challenge, as they are often obscured by background noise. Information Field Theory offers a robust approach to this challenge by using Bayesian inference to calculate the most likely radio signal, given the recorded data. In this paper, we describe the application of Information Field Theory to radio signals from particle showers in both air and ice and demonstrate how accurately pulse parameters can be obtained from noisy data.