Second MODE Workshop on Differentiable Programming for Experiment Design

Ultra-fast muon tomography simulations using Adversarial Neural Networks

14 Sept 2022, 16:15

20m

OAC conference center, Kolymbari, Crete, Greece.

Talk Muography Applications in Muon Tomography

Speaker

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

Description

This presentation explores the possibility of using Generative Adversarial Neural Networks (GANN) in order to simulate the propagation of muons through material without using a complete simulation of the physical processes. In order to achieve this goal, Generative Adversarial Neural Networks have been used to simulate muon tomography data applied to the measurement of the thicknes of isolated pipes. The GANNs have shown an excellent ability to reproduce the scattering distributions, even when the thickness of the pipe is provided as a conditional parameter to the network. Studies on the interpolation ability of the network have been also conducted, being very successfull.

Presentation materials

PresentationMODEWorkshop.pdf