Related papers: Reconstructing non-repeating radio pulses with Inf…
Measurements of cosmic ray particles at energies above E = 5 x 10^{14} eV are performed by large area ground based air shower experiments. Only they provide the collection power required for obtaining sufficient statistics at the low flux…
We discuss methods for performing weak lensing using radio observations to recover information about the intrinsic structural properties of the source galaxies. Radio surveys provide unique information that can benefit weak lensing studies,…
We develop two algorithms, based on maximum likelihood (ML) inference, for estimating the parameters of polarized radio sources which emit at a single rotation measure (RM), e.g., pulsars. These algorithms incorporate the flux density…
Measurements of radio signals induced by an astroparticle generating a cascade present a challenge because they are always superposed with an irreducible noise contribution. Quantifying these signals constitutes a non-trivial task,…
In 1965 it was discovered that cosmic ray air showers emit impulsive radio signals at frequencies below 100 MHz. After a period of intense research in the 1960s and 1970s, however, interest in the detection technique faded almost…
Pulsar radio emission may be generated in pair discharges which fill the pulsar magnetosphere with plasma as an accelerating electric field is screened by freshly created pairs. In this Letter we develop a simplified analytic theory for the…
The extremely regular, periodic radio emission from millisecond pulsars makes them useful tools for studying neutron star astrophysics, general relativity, and low-frequency gravitational waves. These studies require that the observed pulse…
Recursive Bayesian inference, in which posterior beliefs are updated in light of accumulating data, is a tool for implementing Bayesian models in applications with streaming and/or very large data sets. As the posterior of one iteration…
The detection of extensive air showers (EAS) induced by cosmic rays via radio signals has undergone significant advancements in the last two decades. Numerous ultra-high energy cosmic ray experiments routinely capture radio pulses in the…
The Giant Radio Array for Neutrino Detection (GRAND) aims to detect radio signals from extensive air showers (EAS) caused by ultra-high-energy (UHE) cosmic particles. Galactic, hardware-like, and anthropogenic noise are expected to…
We discuss the possibilities of measuring ultra-high energy cosmic rays and neutrinos with radio techniques. We review a few of the properties of radio emission from cosmic ray air showers and show how these properties can be explained by…
The IceCube Neutrino Observatory relies on an array of photomultiplier tubes to detect Cherenkov light produced by charged particles in the South Pole ice. IceCube data analyses depend on an in-depth characterization of the glacial ice, and…
In this paper we derive information theoretic performance bounds to sensing and reconstruction of sparse phenomena from noisy projections. We consider two settings: output noise models where the noise enters after the projection and input…
We present a macroscopic calculation of coherent electro-magnetic radiation from air showers initiated by ultra-high energy cosmic rays, based on currents obtained from Monte Carlo simulations of air showers in a realistic geo-magnetic…
Digital radio arrays have become an effective tool to measure air showers at energies around and above 100 PeV. Compared to optical techniques, the radio technique is not restricted to clear nights. Thanks to recent progress on…
Spherical radial-basis-based kernel interpolation abounds in image sciences including geophysical image reconstruction, climate trends description and image rendering due to its excellent spatial localization property and perfect…
A new generation of neutrino observatories will search for PeV-EeV neutrinos interacting in the ice by detecting radio pulses. Extended air showers propagating into the ice will form an important background and could be a valuable…
The paper discusses the reconstruction of potentials for quantum systems at finite temperatures from observational data. A nonparametric approach is developed, based on the framework of Bayesian statistics, to solve such inverse problems.…
Radio detection of extensive air showers initiated in the Earth's atmosphere has made tremendous progress in the last decade. Today, radio detection is routinely used in several cosmic-ray observatories. The physics of the radio emission in…
Temperature field reconstruction is essential for analyzing satellite heat reliability. As a representative machine learning model, the deep convolutional neural network (DCNN) is a powerful tool for reconstructing the satellite temperature…