Muon event localisation with AI

Publication Name

Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment


Low-cost muon detectors utilising cheap plastic scintillators and a limited number of individual silicon photomultipliers (SiPMs) offer a compelling approach to cheap experimental designs, provided the event localisation of a traversing particle can be accurately determined. In this theoretical work, we use Geant4 to simulate a diverse range of detector configurations, shapes and SiPM photosensors, predicting the light intensity received at a given SiPM. Testing a range of methods to localise muon events we determine that machine learning techniques outperform analytic models, and of these, a simple gradient boosted framework is the most reliably accurate localisation technique for our simulated scintillators. We find that a simple square scintillator outperforms other geometries and that AI performs, when applied to this shape, with a linear relationship between the positional accuracy of the event recovery and the average distance between photosensors around the detector perimeter.

Open Access Status

This publication is not available as open access



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Funding Number


Funding Sponsor

National Computational Infrastructure



Link to publisher version (DOI)