activity
20202026
most citedMeasurement of the cosmic-ray energy spectrum above eV using the Pierre Auger Observatory

213 citations · 1.1k across the 35 of their papers we have counts for

collaborators

42 papers

astro-ph.HE2026

An end-to-end experimental pipeline for automated track identification for paleo-detectors

Claudio Galelli, Alessandro Testi, Lorenzo Caccianiga

Paleo-detectors aim to exploit the damage tracks left in natural minerals by cosmic messengers over geological times to reconstruct past fluxes of energetic particles. For cosmic r…

physics.ins-det2026

Mineral Detection of Neutrinos and Dark Matter 2026 Proceedings

Alexey Elykov, Patrick Stengel, Natsue Abe +81

The fourth "Mineral Detection of Neutrinos and Dark Matter" (MDvDM'26) meeting was held April 14-17, 2026 in Karlsruhe, Germany, hosted by the Institute for Astroparticle Physics (…

astro-ph.HE2026

Investigating past high-energy fluxes with paleo-detectors

Claudio Galelli

Paleo-detectors provide a unique avenue to reconstruct the multi-million-year history of cosmic-ray (CR) flux, preserving signatures of transient high-energy events such as nearby…

astro-ph.HE2025

A volcanic chronosequence as a time-resolved paleo-detector array to study the cosmic-ray flux in the Late Pleistocene and Holocene

Claudio Galelli, Lorenzo Caccianiga, Lorenzo Apollonio +2

We present a phenomenological study demonstrating the feasibility of using olivine xenoliths from the Chaîne des Puys as a time-resolved paleo-detector array to probe the cosmic-ra…

physics.ins-det2025

Mineral Detection of Neutrinos and Dark Matter 2025 Proceedings

Shigenobu Hirose, Patrick Stengel, Natsue Abe +70

The third ``Mineral Detection of Neutrinos and Dark Matter'' (MDDM'25) meeting was held May 20-23, 2025 in Yokohama, Japan, hosted by the Yokohama Institute for Earth Sciences,…

astro-ph.HE2025

gammapy_SyLC: A Package for Simulating and Fitting Variability in High-Energy Light Curves

Claudio Galelli

Characterizing the temporal variability of astrophysical sources is key to understanding the underlying physical processes driving their emissions. This work introduces a gammapy_S…