Second MODE Workshop on Differentiable Programming for Experiment Design

Session

Wine Tasting and Poster Session

14 Sept 2022, 19:00

OAC conference center, Kolymbari, Crete, Greece.

66. (Poster) Muon identification and gamma/hadron discrimination using compact single-layered water Cherenkov detectors powered by Machine Learning techniques

BS González (LIP/IST)

14/09/2022, 19:00

Astrophysics and Cosmology

Poster

The muon tagging is an essential tool to distinguish between gamma and hadron-induced showers in wide field-of-view gamma-ray observatories. In this work, it is shown that an efficient muon tagging (and counting) can be achieved using a water Cherenkov detector with a reduced water volume and multiple PMTs, provided that the PMT signal spatial and time patterns are interpreted by an analysis...

67. Decrypting hadronic showers for studies of particle ID with Deep Learning

Rumman Neshat (Indian Institute Of Science Education and Research(IISER) kolkata), Tommaso Dorigo (Universita e INFN, Padova (IT))

14/09/2022, 19:00

Particle Physics

Poster

As the first step in a wide-ranging study to determine the capabilities of
fine-grained calorimeters to identify different hadrons within dense showers, we show how to extract all the information about all intermediate processes taking place within the development of complex hadron showers produced by simulation in GEANT4.

39. Differentiable Preisach Modeling for Characterization and Optimization of Particle Accelerator Systems with Hysteresis

Ryan Roussel

14/09/2022, 19:00

Particle Physics

Poster

Future improvements in particle accelerator performance are predicated on increasingly accurate online modeling of accelerators. Hysteresis effects in magnetic, mechanical, and material components of accelerators are often neglected in online accelerator models used to inform control algorithms, even though reproducibility errors from systems exhibiting hysteresis are not negligible in high...

69. Muon momentum measurement in Muon Scattering Tomography

Mr Maxime Lagrange (CP3 Universite Catholique de Louvain)

14/09/2022, 19:00

Muography

Poster

The recent MODE whitepaper*, proposes an end-to-end differential pipeline for the optimization 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 step in attempting to realize such a pipeline, and aims to allow the optimisation of detectors for the purpose of muon tomography with...

76. A flexible and efficient machine learning approach for data quality monitoring

Dr Marco Letizia

14/09/2022, 19:05

Particle Physics

Poster

We present a machine learning approach for real-time detector monitoring. The corresponding core algorithm is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. The model evaluates the compatibility between incoming batches of experimental data and a reference data sample, by...

75. Automatic Optimization of Derivatives with Polyhedral Compiler

Alexander Demin (Max Planck Institute for Informatics)

14/09/2022, 19:10

Computer Science

Poster

Derivatives, mainly in the form of gradients and Hessians, are ubiquitous in machine learning and Bayesian inference. Automatic differentiation (AD) techniques transform a program into a derivative (adjoint) program, which is run to compute the gradient.

Traditionally, most AD systems have been high level, and unable to extract good performance on scalar code or loops modifying memory....

73. Concept of measuring (Multi-)Strange Hadron Yields in the CBM Experiment using Machine Learning Techniques

Axel Puntke (WWU Münster)

14/09/2022, 19:10

Astrophysics and Cosmology

Poster

The Compressed Baryonic Matter (CBM) experiment at FAIR will investigate the
QCD phase diagram at high net-baryon density (μB > 500 MeV) with heavy-ion
collisions in the energy range of √sNN = 2.7−4.9 GeV. Precise determination of dense
baryonic matter properties requires multi-differential measurements of strange
hadron yields, both for the most copiously produced K0s and Λ as well as for...

74. Reconstruction techniques for nuclear reactions measured with ACtive TARget TPC

Lorenzo Domenichetti (INFN LNL, University of Padua)

14/09/2022, 19:10

Nuclear Physics

Poster

ACTAR is an active-target TPC optimized for the study of nuclear reactions produced by low-intensity beams, such as radioactive beams. In this detector, the gas used to track charged particles within the chamber is at the same time used as a target for the incoming beam. Reconstructing the tracks left by ions is a challenging task, and two different reconstruction algorithms are compared in...