20 citations · 22 across the 7 of their papers we have counts for
10 papers
An investigation of fast simulation techniques for pion showers using kernel density estimators with the CALICE AHCAL Technological Prototype
CALICE Collaboration, A. Wilhahn, J. Utehs +29
In this article, the development and investigation of fast hadron shower simulation methods is presented. A test beam dataset has been recorded in 2018 at CERN with the AHCAL Techn…
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…
Status of the International Linear Collider
Y. Abe, S. Arai, S. Araki +149
This paper is not a proposal for a CERN future project but provides information on the International Linear Collider (ILC) considered for Japan in order to facilitate the European…
ECFA Higgs, electroweak, and top Factory Study
H. Abidi, J. A. Aguilar-Saavedra, S. Airen +373
The ECFA Higgs, electroweak, and top Factory Study ran between 2021 and 2025 as a broad effort across the experimental and theoretical particle physics communities, bringing togeth…
European Strategy for Particle Physics Update -- PIONEER: a next generation rare pion decay experiment
PIONEER Collaboration, A. Adelmann, W. Altmannshofer +76
PIONEER is a rapidly developing effort aimed to perform a pristine test of lepton flavour universality (LFU) and of the unitarity of the first row of the CKM matrix by significantl…
The Linear Collider Facility (LCF) at CERN
H. Abramowicz, E. Adli, F. Alharthi +406
In this paper we outline a proposal for a Linear Collider Facility as the next flagship project for CERN. It offers the opportunity for a timely, cost-effective and staged construc…
A Linear Collider Vision for the Future of Particle Physics
H. Abramowicz, E. Adli, F. Alharthi +446
In this paper we review the physics opportunities at linear colliders with a special focus on high centre-of-mass energies and beam polarisation, take a fresh look at the…
High Level Reconstruction with Deep Learning using ILD Full Simulation
Taikan Suehara, Risako Tagami, Lai Gui +4
Deep learning can give a significant impact on physics performance of electron-positron Higgs factories such as ILC and FCCee. We are working on two topics on event reconstruction…
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…