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Machine Learning-Assisted Measurement of Lepton-Jet Azimuthal Angular Asymmetries in Deep-Inelastic Scattering at HERA / H1 Collaboration
In deep-inelastic positron-proton scattering, the lepton-jet azimuthal angular asymmetry is measured using data collected with the H1 detector at HERA. [...]
arXiv:2412.14092 ; DESY24-200. - 15.
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Review of particle physics / Particle Data Group Collaboration
The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,717 new measurements from 869 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons [...]
2024 - 2382 p. - Published in : Phys. Rev. D 110 (2024) 030001 Fulltext: PDF;

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Shower Separation in Five Dimensions for Highly Granular Calorimeters using Machine Learning / CALICE Collaboration
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 separate energy deposits from charged and neutral particles. Three published neural network-based shower separation models were applied to simulation and experimental data to measure the performance of the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL) technological prototype in distinguishing the energy deposited by a single charged and single neutral hadron for Particle Flow. [...]
arXiv:2407.00178.- 2024-10-24 - 29 p. - Published in : JINST 19 (2024) P10027 Fulltext: 2407.00178 - PDF; document - PDF;

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Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter / CMS HGCAL Collaboration
A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. [...]
arXiv:2406.11937.- 2024-11-28 - 27 p. - Published in : JINST 19 (2024) P11025 Fulltext: 2406.11937 - PDF; b5503c82fab7782294f84cb336b7e20a - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server

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Observation and differential cross section measurement of neutral current DIS events with an empty hemisphere in the Breit frame / H1 Collaboration
The Breit frame provides a natural frame to analyze lepton-proton scattering events. In this reference frame, the parton model hard interactions between a quark and an exchanged boson defines the coordinate system such that the struck quark is back-scattered along the virtual photon momentum direction. [...]
arXiv:2403.08982; DESY-24-034.- 2024-07-22 - 13 p. - Published in : Eur. Phys. J. C 84 (2024) 720 Fulltext: 2403.08982 - PDF; document - PDF;

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Measurement of groomed event shape observables in deep-inelastic electron-proton scattering at HERA / H1 Collaboration
The H1 Collaboration at HERA reports the first measurement of groomed event shape observables in deep inelastic electron-proton scattering (DIS) at $\sqrt{s}=319$ GeV, using data recorded between the years 2003 and 2007 with an integrated luminosity of $351$ pb$^{-1}$. Event shapes provide incisive probes of perturbative and non-perturbative QCD. [...]
arXiv:2403.10134; DESY-24-036.- 2024-07-22 - 32 p. - Published in : Eur. Phys. J. C 84 (2024) 718 Fulltext: 2403.10134 - PDF; document - PDF;

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Measurement of the 1-jettiness event shape observable in deep-inelastic electron-proton scattering at HERA / H1 Collaboration
The H1 Collaboration reports the first measurement of the 1-jettiness event shape observable $\tau_1^b$ in neutral-current deep-inelastic electron-proton scattering (DIS). The observable $\tau_1^b$ is equivalent to a thrust observable defined in the Breit frame. [...]
arXiv:2403.10109; DESY-24-035.- 2024-08-07 - 45 p. - Published in : Eur. Phys. J. C 84 (2024) 785 Fulltext: 2403.10109 - PDF; document - PDF;

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Software Compensation for Highly Granular Calorimeters using Machine Learning / CALICE Collaboration
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 information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. [...]
arXiv:2403.04632.- 2024-04 - 27 p. - Published in : JINST 19 (2024) P04037 Fulltext: 2403.04632 - PDF; Publication - PDF;

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Focus topics for the ECFA study on Higgs / Top / EW factories / de Blas, Jorge (Granada U.) ; Koppenburg, Patrick (Nikhef, Amsterdam) ; List, Jenny (DESY) ; Maltoni, Fabio (Louvain U.) ; Maestre, Juan Alcaraz (Madrid, CIEMAT) ; Alimena, Juliette (DESY) ; Alison, John (Carnegie Mellon U.) ; Azzi, Patrizia (INFN, Padua) ; Azzurri, Paolo (INFN, Pisa) ; Bagnaschi, Emanuele (CERN ; INFN, Italy) et al.
In order to stimulate new engagement and trigger some concrete studies in areas where further work would be beneficial towards fully understanding the physics potential of an $e^+e^-$ Higgs / Top / Electroweak factory, we propose to define a set of focus topics. [...]
arXiv:2401.07564. - 65.
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10.

Timing Performance of the CMS High Granularity Calorimeter Prototype / CMS HGCAL Collaboration
This paper describes the experience with the calibration, reconstruction and evaluation of the timing capabilities of the CMS HGCAL prototype in the beam tests in 2018. The calibration procedure includes multiple steps and corrections ranging from tens of nanoseconds to a few hundred picoseconds. [...]
arXiv:2312.14622.- 2024-04-11 - 22 p. - Published in : JINST 19 (2024) P04015 Fulltext: PDF; Fulltext from Publisher: PDF;

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190	Sefkow, F.
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