Marwa Al Moussawi, Samip Basnet, Luigi Cimmino, Eduardo Cortina Gil, Ishan Darshana, Antoine Deblaere, Pavel Demin, Andrea Giammanco, Raveendrababu Karnam, Maxime Lagrange, Hikaru Sato

The general goal of this project is to develop muon-based radiography or tomography (“muography”), an innovative multidisciplinary approach to study large-scale natural or man-made structures, establishing a strong synergy between particle physics and other disciplines, such as geology and archaeology.
Muography is an imaging technique that relies on the measurement of the absorption of muons produced by the interactions of cosmic rays with the atmosphere.
Applications span from geophysics (the study of the interior of mountains and the remote quasi-online monitoring of active volcanoes) to archaeology and mining.

We are using the local facilities at CP3 for the development of high-resolution portable detectors based on Resistive Plate Chambers.

We also participate to the MURAVES collaboration through simulations (including the coordination of the Monte Carlo group), data-analysis developments (an example of the latter is the implementation and in-situ calibration of time-of-flight capabilities), and development of a new database.

We are part of the H2020-RIA project SilentBorder, which aims at developing new muon scanners at border controls. Our role in this project is to develop a parametric simulation and a ML-based detector optimization procedure.

We are also part of the H2020-MSCA-RISE network INTENSE where we coordinate the Muography work package, which brings together particle physicists, geophysicists, archaeologists, civil engineers and private companies for the development and exploitation of this imaging method.

External collaborators: UGent; Kyushu University; INTENSE Research & Innovation Staff Exchange network (Japan, Switzerland, Italy, France, Hungary); SilentBorder network (Estonia, Germany, Finland, Turkey, Italy, UK); MURAVES Collaboration including INFN, INGV, universities of Florence and Federico II Naples, UGent.