The measurement of the mass composition of ultra-high energy cosmic rays constitutes a prime challenge in astroparticle physics. Most detailed information on the composition can be obtained from measurements of the depth of maximum of air showers, Xmax, with the use of fluorescence telescopes, which can be operated only during clear and moonless nights. Using deep neural networks, it is now possible for the first time to perform an event-by-event reconstruction of Xmax with the Surface Detector (SD) of the Pierre Auger Observatory. Therefore, previously recorded data can be analyzed for information on Xmax, and thus, the cosmic-ray composition. Since the SD operates with a duty cycle of almost 100% and its event selection is less strict tha...
This paper shows that the artificial neural networks (ANN) can be used for determining the type of p...
To understand the origin and nature of Ultra High Energy Cosmic Rays their mass composition must be ...
We introduce a novel method for identifying the mass composition of ultra-high-energy cosmic rays us...
The measurement of the mass composition of ultra-high energy cosmic rays constitutes a prime challen...
The atmospheric depth of the air shower maximum Xmax is an observable commonly used for the determin...
The atmospheric depth of the air shower maximum Xmax is an observable commonly used for the determin...
Ultra-high energy cosmic rays (UHECRs) are the most energetic particles found in nature. The search ...
International audienceThe atmospheric depth of the air shower maximum X max is an observable commonl...
To probe physics beyond the scales of human-made accelerators with cosmic rays demands an accurate k...
The composition of cosmic ray primaries at the highest energies is one of the biggest open question...
The Fluorescence Detector of the Pierre Auger Observatory measures the atmospheric depth, $X_{max}$,...
With data on the depth of maximum Xmax collected during more than a decade of operation of the Pier...
This paper shows that the artificial neural networks (ANN) can be used for determining the type of p...
To understand the origin and nature of Ultra High Energy Cosmic Rays their mass composition must be ...
We introduce a novel method for identifying the mass composition of ultra-high-energy cosmic rays us...
The measurement of the mass composition of ultra-high energy cosmic rays constitutes a prime challen...
The atmospheric depth of the air shower maximum Xmax is an observable commonly used for the determin...
The atmospheric depth of the air shower maximum Xmax is an observable commonly used for the determin...
Ultra-high energy cosmic rays (UHECRs) are the most energetic particles found in nature. The search ...
International audienceThe atmospheric depth of the air shower maximum X max is an observable commonl...
To probe physics beyond the scales of human-made accelerators with cosmic rays demands an accurate k...
The composition of cosmic ray primaries at the highest energies is one of the biggest open question...
The Fluorescence Detector of the Pierre Auger Observatory measures the atmospheric depth, $X_{max}$,...
With data on the depth of maximum Xmax collected during more than a decade of operation of the Pier...
This paper shows that the artificial neural networks (ANN) can be used for determining the type of p...
To understand the origin and nature of Ultra High Energy Cosmic Rays their mass composition must be ...
We introduce a novel method for identifying the mass composition of ultra-high-energy cosmic rays us...