Contact
Name
Aitor Orio

Position
Postdoc

Email
aitor.orio@muon.systems

Address
Centre for Cosmology, Particle Physics and Phenomenology - CP3
Université catholique de Louvain
2, Chemin du Cyclotron - Box L7.01.05
B-1348 Louvain-la-Neuve
Belgium

Office
E.166

Personal homepage
https://www.linkedin.com/in/aitororioalonso/
Projects
Research directions:
Data analysis in HEP, astroparticle and GW experiments
Research and development of new detectors
Technology Transfer

Experiments and collaborations:
MODE
MURAVES

Active projects
Imaging with cosmic-ray muons
Hamid Basiri, Alice Biolchini, Eduardo Cortina Gil, Pavel Demin, Khalil El Achi, Andrea Giammanco, Sumaira Ikram, Gábor Nyitrai, Aitor Orio, Nicolas Szilasi, Ayman Youssef, Zahraa Zaher

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 have contributed the EU projects SilentBorder / SilentBorder2, aiming 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, and of KINETIKA where our task is to apply muography to cultural heritage preservation.

External collaborators: EU projects INTENSE, SilentBorder/SilentBorder2, KINETIKA.
Machine-learning Optimized Design of Experiments
Luigi Favaro, Andrea Giammanco, Aitor Orio, Zahraa Zaher

We are among the founders of MODE (Machine-learning Optimized Design of Experiments, https://mode-collaboration.github.io/), a multi-disciplinary consortium of European and American physicists and computer scientists who target the use of differentiable programming in design optimization of detectors for particle physics applications, extending from fundamental research at accelerators, in space, and in nuclear physics and neutrino facilities, to industrial applications employing the technology of radiation detection.
We also participate to the very closely related activities of the "Codesign" work package in the EUCAIF network.
We aim to develop a modular, customizable, and scalable, fully differentiable pipeline for the end-to-end optimization of articulated objective functions that model in full the true goals of experimental particle physics endeavours, to ensure optimal detector performance, analysis potential, and cost-effectiveness.
The main goal of our activities is to develop an architecture that can be adapted to the above use cases but will also be customizable to any other experimental endeavour employing particle detection at its core. We welcome suggestions, as well as interest in joining our effort, by researchers focusing on use cases for which this technology can be of benefit.

External collaborators: See updated list here: https://mode-collaboration.github.io/ For EUCAIF, see: https://eucaif.org/.
Publications in IRMP
All my publications on Inspire

Number of publications as IRMP member: 2

2024

IRMP-CP3-24-37: Optimisation of muon portals for border controls using TomOpt
Z. Daher, M. Lagrange, S. Alvarez, G. C. Strong, F. Bury, T. Dorigo, A. Giammanco, A. Orio, P. Vischia, H. Zaraket

[Full text]
Proceedings of the MARESEC workshop. Public on Zenodo.
Contribution to proceedings. November 25.

2023

IRMP-CP3-23-51: TomOpt: Differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography
Strong, Giles C. and others

[Abstract] [PDF] [Journal] [Dial] [Full text]
Giles C Strong et al., Mach. Learn.: Sci. Technol. 5 (2024) 035002
Refereed paper. September 26.