Muography : detector optimization and cultural heritage applications
(2025)
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Muography_detector_optimisation_and_cultural_heritage_applications_Maxime_Lagrange.pdf
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- Authors
- Supervisors
- Giammanco, Andrea
- Abstract
- Particle physics explores the Universe’s building blocks, forces, and evolution. Though often seen as abstract, its technologies—such as accelerators and detectors—have profoundly shaped medicine, industry, and communication. The Large Hadron Collider at CERN exemplifies the scale and sophistication of this instrumentation, while many spin-offs, from synchrotron radiation to imaging tools like CT, PET, MRI, and proton therapy, have entered daily life. Muography is a more recent technique that leverages naturally occurring cosmic-ray muons instead of artificial radiation sources to create radiographic images. Since its first success in 1955, it has advanced through better detectors, simulations, and reconstruction methods. By exploiting how muons are absorbed or deflected when traversing matter, muography enables non-invasive imaging of large and dense structures inaccessible to traditional methods. This capability has unlocked applications in volcanology, archaeology, civil engineering, nuclear waste monitoring, and security screening, and is increasingly explored as a complementary tool to conventional imaging. This thesis advances muography toward greater reliability and broader use. It addresses detector optimization, systematic benchmarking of reconstruction algorithms, improved methods for inferring muon momentum, and the extension of muography to new domains. The overarching aim is to reduce the gap with established modalities such as X-ray or CT imaging, which benefit from standardized practices and commercial deployment. By contributing a more unified framework, this work aspires to help establish muography as a mature, widely adopted imaging technique for science and industry.
- Affiliations
Citations
Lagrange, M. (2025). Muography : detector optimization and cultural heritage applications.