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Energy reconstruction of hadronic showers at the CERN PS and SPS using the Semi-Digital Hadronic Calorimeter

2022· article· en· W4221147582 on OpenAlexaff
D. Boumediene, Antoine Pingault, M. Tytgat, Y. W. Baek, DW Kim, S.C. Lee, B.G. Min, S.W. Park, Yuto Deguchi, K. Kawagoe, Yoshio Miura, R. Mori, Izumi Sekiya, Taikan Suehara, T. Yoshioka, L. Caponetto, C. Combaret, Guillaume Garillot, G. Grenier, J.C. Ianigro, T. Kurča, I. B. Laktineh, B. Liu, B. Li, N. Lumb, H. Mathez, L. Mirabito, A. Steen, E. Calvo, M. C. Fouz, Héctor García Cabrera, J. Marín, Jose Javier Navarrete, J. Puerta Pelayo, Anamaria Verdugo, F. Corriveau, L. Emberger, C. Graf, L.M.S de Silva, F. Simon, C.H. Winter, J. Bonis, D. Breton, P. Cornebise, A. Gallas, Jimmy Jeglot, A. Irles Quiles, J. Maalmi, R. Pöschl, A. Thiebault, F. Richard, D. Zerwas, J. Cvach, M. Janata, M. Kovalcuk, J. Kvasnička, I. Polák, J. Smolík, V. Vrba, J. Zálešâk, J. Zuklin, Y. Duan, S. Li, J. Guo, J. F. Hu, F. Lagarde, Qi-Xing Shen, X. Wang, W.H. Wu, H. J. Yang, Y.F. Zhu

Bibliographic record

VenueJournal of Instrumentation · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsMcGill University
FundersCentre National de la Recherche ScientifiqueNational Research Foundation of KoreaNational Natural Science Foundation of ChinaInstitut National de Physique Nucléaire et de Physique des ParticulesAgencia Estatal de InvestigaciónAgence Nationale de la RechercheNational Research FoundationCERN
KeywordsPhysicsCalorimeter (particle physics)Large Hadron ColliderNuclear physicsHadronBeamlineMuonEnergy (signal processing)Resistive touchscreenDetectorParticle physicsBeam (structure)OpticsComputer science

Abstract

fetched live from OpenAlex

Abstract The CALICE Semi-Digital Hadronic CALorimeter (SDHCAL) is the first technological prototype in a family of high-granularity calorimeters developed by the CALICE Collaboration to equip the experiments of future lepton colliders. The SDHCAL is a sampling calorimeter using stainless steel for absorber and Glass Resistive Plate Chambers (GRPC) as a sensitive medium. The GRPC are read out by 1 cm× 1 cm pickup pads combined to a multi-electronics. The prototype was exposed to hadron beams in both the CERN PS and the SPS beamlines in 2015 allowing the test of the SDHCAL in a large energy range from 3 GeV to 80 GeV. After introducing the method used to select the hadrons of our data and reject the muon and electron contamination, we present the energy reconstruction approach that we apply to the data collected from both beamlines and we discuss the response linearity and the energy resolution of the SDHCAL. The results obtained in the two beamlines confirm the excellent SDHCAL performance observed with the data collected with the same prototype in the SPS beamline in 2012. They also show the stability of the SDHCAL in different beam conditions and different time periods.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.241
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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