47 citations · 66 across the 10 of their papers we have counts for
13 papers
Constraints on a Long-Lived X17 Vector Boson with FASER
FASER Collaboration, Roshan Mammen Abraham, Xiaocong Ai +133
The ATOMKI anomalies motivate the possibility of a new particle, the X17, with a mass of 17 MeV and weak couplings to nuclei and electrons. Such a particle may be produced at the L…
Event-by-event track imaging of charged particles with an ultrafast plenoptic camera
Till Dieminger, Marco Barbieri, Vincenzo Berardi +8
Modern elementary particle detectors often require high-resolution three-dimensional particle tracking in large dense active volumes, which is difficult to achieve in standard devi…
Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training
Saúl Alonso-Monsalve, Fabio Cufino, Umut Kose +2
Accelerator-based neutrino physics is entering an energy-frontier regime in which interactions reach the TeV scale and produce exceptionally dense, overlapping detector signatures.…
An ultrafast plenoptic-camera system for high-resolution 3D particle tracking in unsegmented scintillators
Till Dieminger, Saúl Alonso-Monsalve, Christoph Alt +7
Neutrino detectors, particle calorimeters and some dark matter detectors require dense and massive active materials. An extremely fine segmentation is desirable to achieve precise…
Submanifold Sparse Convolutional Networks for Automated 3D Segmentation of Kidneys and Kidney Tumours in Computed Tomography
Saúl Alonso-Monsalve, Leigh H. Whitehead, Adam Aurisano +1
Accurate delineation of kidney tumours in Computed Tomography (CT) is essential for downstream quantitative analysis and precision oncology, but manual segmentation is a specialise…
Prospects and Opportunities with an upgraded FASER Neutrino Detector during the HL-LHC era: Input to the EPPSU
FASER Collaboration, Roshan Mammen Abraham, Xiaocong Ai +115
The FASER experiment at CERN has opened a new window in collider neutrino physics by detecting TeV-energy neutrinos produced in the forward direction at the LHC. Building on this s…
Contrastive Learning for Robust Representations of Neutrino Data
Alex Wilkinson, Radi Radev, Saul Alonso-Monsalve
In neutrino physics, analyses often depend on large simulated datasets, making it essential for models to generalise effectively to real-world detector data. Contrastive learning,…
AI-based particle track identification in scintillating fibres read out with imaging sensors
Noemi Bührer, Saúl Alonso-Monsalve, Matthew Franks +2
This paper presents the development and application of an AI-based method for particle track identification using scintillating fibres read out with imaging sensors. We propose a v…
Deep-learning-based decomposition of overlapping-sparse images: application at the vertex of neutrino interactions
Saúl Alonso-Monsalve, Davide Sgalaberna, Xingyu Zhao +3
Image decomposition plays a crucial role in various computer vision tasks, enabling the analysis and manipulation of visual content at a fundamental level. Overlapping images, whic…
Automated Segmentation of Computed Tomography Images with Submanifold Sparse Convolutional Networks
Saúl Alonso-Monsalve, Leigh H. Whitehead, Adam Aurisano +1
Quantitative cancer image analysis relies on the accurate delineation of tumours, a very specialised and time-consuming task. For this reason, methods for automated segmentation of…
Artificial intelligence for improved fitting of trajectories of elementary particles in inhomogeneous dense materials immersed in a magnetic field
Saúl Alonso-Monsalve, Davide Sgalaberna, Xingyu Zhao +2
In this article, we use artificial intelligence algorithms to show how to enhance the resolution of the elementary particle track fitting in inhomogeneous dense detectors, such as…
Graph neural network for 3D classification of ambiguities and optical crosstalk in scintillator-based neutrino detectors
Saúl Alonso-Monsalve, Dana Douqa, César Jesús-Valls +5
Deep learning tools are being used extensively in high energy physics and are becoming central in the reconstruction of neutrino interactions in particle detectors. In this work, w…
Image-based model parameter optimization using Model-Assisted Generative Adversarial Networks
Saúl Alonso-Monsalve, Leigh H. Whitehead
We propose and demonstrate the use of a model-assisted generative adversarial network (GAN) to produce fake images that accurately match true images through the variation of the pa…