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Cosmic rays interacting with the atmosphere allow for the probing offundamental interactions at ultra-high energies. We thus obtain limits onstrongly coupled new physics models via their imprints on cosmic-ray airshowers. Using the Monte Carlo event generators Herwig and HERBVI, and the airshower simulator CORSIKA, to simulate such processes, we apply machine learningalgorithms to the simulated observables to discriminate the events arising vianew physics from the QCD background. We then use the signal and backgrounddiscrimination performance to set potential limits on the cross sections of thenew physics models.

Constraining strongly coupled new physics from cosmic rays with machine learning techniques