We are all the Cosmic-Ray Extremely Distributed Observatory
N. Dhital, P. Homola, J. F. Jarvis, P. Poznanski, K. Almeida, Cheminant, {\L}. Bratek, T. Bretz, D. Gora, P. Jagoda, J. Ja{\l}ocha, K., Kopanski, D. Lemanski, M. Magrys, V. Nazari, J. Niedzwiedzki, M. Nocun, W., Noga, A. Ozieblo, K. Smelcerz, K. Smolek, J. Stasielak, S. Stuglik

TL;DR
CREDO is a global infrastructure designed to detect and analyze super-preshowers, extended cosmic-ray phenomena that could reveal new physics beyond current detection capabilities, impacting astrophysics and fundamental particle physics.
Contribution
This paper introduces CREDO, a novel global network for detecting super-preshowers, exploring an uncharted realm of cosmic-ray phenomena beyond existing observatories.
Findings
Proposes a global cosmic-ray detection network for super-preshowers.
Aims to detect phenomena spanning from air showers to wide-spread particle cascades.
Potential to observe new physics or set limits on large extraterrestrial cascades.
Abstract
The Cosmic-Ray Extremely Distributed Observatory (CREDO) is an infrastructure for global analysis of extremely extended cosmic-ray phenomena, so-called super-preshowers, beyond the capabilities of existing, discrete, detectors and observatories. To date cosmic-ray research has been focused on detecting single air showers, while the search for ensembles of cosmic-ray events induced by super-preshowers is a scientific terra incognita - CREDO explores this uncharted realm. Positive detection of super-preshowers would have an impact on ultra-high energy astrophysics, cosmology and the physics of fundamental particle interactions as they can theoretically be formed within both classical (photon-photon interactions) and exotic (Super Heavy Dark Matter particle decay and interaction) scenarios. Some super-preshowers are predicted to have a significant spatial extent - a unique signature only…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
