Fourth MODE Workshop on Differentiable Programming for Experiment Design

Session

Muography

24 Sept 2024, 09:00

Valencia (Spain)

Conveners

Muography

• Pablo Martinez Ruiz Del Arbol (Universidad de Cantabria and CSIC (ES))

Muography

• Pablo Martinez Ruiz Del Arbol (Universidad de Cantabria and CSIC (ES))

32. Optimisation of muon tomography scanners for border controls using TomOpt

Zahraa Zaher

24/09/2024, 09:00

Muography

TomOpt is a software package designed to optimize the geometric configuration and specifications of detectors intended for tomography using cosmic-ray muon scattering. Differentiable programming is utilized by the software to model muon interactions with detectors and scanned volumes, infer volume properties, and perform loss minimization in an optimization cycle. We introduce the...

10. Generative Adversarial Neural Networks for muography simulation: image prediction

Pablo Martinez Ruiz Del Arbol (Universidad de Cantabria and CSIC (ES))

24/09/2024, 09:20

Muography

Generative Adversarial Neural Networks (GANN) are used to simulate the multiple scattering of muons crossing matter. In previous works, a GANN was designed and trained, successfully predicting the angular and spatial deviation distributions including their correlations. In this work we show that GANNs can be so good at this task that correct POCA images can be reconstructed from their randomly...

12. Segmentation and anomaly detection on Muon Tomography applied to the inspection of containers

Carlos Diez (Muon Tomography Systems S.L.)

24/09/2024, 09:40

Muography

Muon Cargo is a project funded by the Spanish Port Authority aiming at installing a Muography portal for container inspection in the port of Santander. This talk offers a panoramic of the status of the project focusing on the development of two AI algorithms: a YOLOv8 based system to perform semantic segmentation on POCA-based images, and a Variational Autoencoder to identify unsual,...

18. Muon momentum estimation in scattering tomography

Mr Florian Bury (University of Bristol)

25/09/2024, 09:00

Muography

Muon scattering tomography allows for the imaging of the density of unknown volumes through the measurement of the incoming and outgoing tracks scattering angle. One significant source of imprecision of the technique comes from the dependence of muon momentum on the multiple scattering process that muons undergo in the material. This can be alleviated by including dedicated momentum...

19. Improving Material Identification in Muon Scattering Tomography with Machine Learning.

Angel Bueno Rodriguez (German Aerospace Center (DLR))

25/09/2024, 09:20

Muography

Machine learning holds significant potential for improving Muon Scattering Tomography (MST) material identification. However, the complexity of acquiring sufficient MST data for machine learning applications remains a significant challenge. To circumvent this, there is a growing interest in creating MST synthetic datasets using Geant4, a software that can accurately simulate muon-material...

4. Muographic Image Up-Sampling with Machine Learning for Built Infrastructure Applications

Mr William O'Donnell (University of Glasgow)

25/09/2024, 09:40

Muography

In the civil engineering industry, there is an increasing demand for innovative non-destructive evaluation methods, especially for critical infrastructure such as bridges, as current techniques fall short. Muography, a non-invasive technique, constructs three-dimensional density maps by detecting the interactions of naturally occurring cosmic-ray muons within the scanned volume. Due to their...