14 citations · 58 across the 12 of their papers we have counts for
16 papers
The Super Fine-Grained Detector for the T2K neutrino oscillation experiment
S. Abe, H. Alarakia-Charles, I. Alekseev +169
The magnetised near detector ND280 of the long-baseline neutrino experiment T2K has been upgraded to improve its detection performance and, consequently, enhance our understanding…
Introducing a Markov Chain-Based Time Calibration Procedure for Multi-Channel Particle Detectors: Application to the SuperFGD and ToF Detectors of the T2K Experiment
S. Abe, H. Alarakia-Charles, I. Alekseev +190
Inter-channel mis-synchronisation can be a limiting factor to the time resolution of high performance timing detectors with multiple readout channels and independent electronics un…
The ILD Detector: A Versatile Detector for an Electron-Positron Collider at Energies up to 1 TeV
H. Abramowicz, D. Ahmadi, J. Alcaraz +276
The International Large Detector, ILD, is a detector concept for an experiment at a future high energy lepton collider. The detector has been optimised for precision physics in a r…
Input to the ESPPU: The LUXE Experiment
H. Abramowicz, M. Almanza Soto, M. Altarelli +130
This document presents an overview of LUXE (Laser Und XFEL Experiment), an experiment that will combine the high-quality and high-energy electron beam of the European XFEL with a h…
Shower Separation in Five Dimensions for Highly Granular Calorimeters using Machine Learning
S. Lai, J. Utehs, A. Wilhahn +48
To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to se…
Software Compensation for Highly Granular Calorimeters using Machine Learning
S. Lai, J. Utehs, A. Wilhahn +61
A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event in…