Second MODE Workshop on Differentiable Programming for Experiment Design

Session

Applications in Muon Tomography

14 Sept 2022, 11:00

OAC conference center, Kolymbari, Crete, Greece.

Conveners

Applications in Muon Tomography

• Pablo Martinez Ruiz Del Arbol (Universidad de Cantabria and CSIC (ES))
• Tommaso Dorigo (Universita e INFN, Padova (IT))

Applications in Muon Tomography

• Maxime Lagrange (CP3 Universite Catholique de Louvain)

52. TomOpt: Differentiable Optimisation of Muon-Tomography Detectors

Giles Chatham Strong (Universita e INFN, Padova (IT))

14/09/2022, 11:00

Muography

Talk

The recent MODE whitepaper*, proposes an end-to-end differential pipeline for the optimisation of detector designs directly with respect to the end goal of the experiment, rather than intermediate proxy targets. The TomOpt python package is the first concrete endeavour in attempting to realise such a pipeline, and aims to allow the optimisation of detectors for the purpose of muon tomography...

79. Detector optimization in Muon scattering Tomography

Mr Maxime Lagrange (CP3 Universite Catholique de Louvain)

14/09/2022, 11:25

Muography

Talk

Muon Scattering Tomography (MST) has been through a fruitful period of development which led to many applications in various fields such as border controls, nuclear waste characterization, nuclear reactor monitoring and preventive maintenance of industrial facilities. Whatever the use case, MST detector conception aims at reaching the best performance that respects specific constraints,...

61. Detection of material contrast in muon tomography data with machine learning

Dr Konstantin Borozdin (Sandia Research Center)

14/09/2022, 11:50

Muography

Talk

Muon tomography applications often require detection of material contrast. One example of such application is the detection of contraband at the border. Another example is the detection of steel rebars inside reinforced concrete blocks. Sensitivity of material discrimination depends on the detector configuration, exposure time and clutter. We explore how machine learning techniques can be used...

86. NEWCUT: a novel tool for reconstruction of low-energy muon spectra

. OLAH LASZLO

14/09/2022, 12:15

Talk

High-precision muographic imaging of targets with thicknesses up to a
few meters requires the accurate measurement of the angular and energy
dependent flux of cosmic-ray muons in the low-energy regime (up to a few
GeV). We designed a muon spectrometer, called NEWCUT [1]. It is a
six-meter-length tracking system consists of nineteen Multi-wire
Proportional Chambers (MWPCs) and lead plates....

90. Scattering Tomography with the EM Algorithm

Anna Bordignon

14/09/2022, 12:40

Talk

We investigate the problem of distinguishing materials by scattering tomography with an R implementation of the EM (Expectation Maximization) algorithm and we compare the results with those from the PoCA (Point of Closest Approach) method.

68. Deep neural networks applied to muon tomography scattering angular distributions

Carlos Diez (Muon Tomography Systems S.L.)

14/09/2022, 15:50

Muography

Talk

Several applications of scattering muon tomography require the estimation of a limited number of key parameters associated to a given sample. In this presentation we explore the use of the quantiles of the angular and spatial deviation distributions as the input to Deep Neural Networks regressing on the parameters of interest. We provide examples related to the measurement of the position of...

65. Ultra-fast muon tomography simulations using Adversarial Neural Networks

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

14/09/2022, 16:15

Muography

Talk

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...