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Record W4405654183 · doi:10.17181/f7yev-pd160

Expected Tracking Performance of the ATLAS Inner Tracker at the High-Luminosity LHC

2024· preprint· en· W4405654183 on OpenAlexfundno aff

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaInstitut National de Physique Nucléaire et de Physique des ParticulesAgencia Nacional de Promoción Científica y TecnológicaScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaAgencia Nacional de Investigación y DesarrolloNational Science and Technology CouncilCentre National pour la Recherche Scientifique et TechniqueU.S. Department of EnergyNational Natural Science Foundation of ChinaVetenskapsrådetMax-Planck-GesellschaftKnut och Alice Wallenbergs StiftelseBundesministerium für Wissenschaft, Forschung und WirtschaftMinistry of Education, Culture, Sports, Science and TechnologyNederlandse Organisatie voor Wetenschappelijk OnderzoekAustrian Science FundMinisterstvo Školství, Mládeže a TělovýchovyBundesministerium für Bildung und ForschungCentre National de la Recherche ScientifiqueJapan Society for the Promotion of ScienceConselho Nacional de Desenvolvimento Científico e TecnológicoTürkiye Enerji, Nükleer ve Maden Araştırma KurumuDanmarks GrundforskningsfondMinisterstwo Edukacji i NaukiCERNLeverhulme TrustUK Research and InnovationNational Science FoundationTRIUMFFundação de Amparo à Pesquisa do Estado de São PauloAgencia Estatal de InvestigaciónSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsAtlas (anatomy)Large Hadron ColliderTracking (education)DetectorLuminosityATLAS experimentAtlas detectorSoftwareComputer sciencePhysicsParticle physicsOperating systemOpticsAstronomy

Abstract

fetched live from OpenAlex

Following the discovery of the Higgs boson, the precise measurement of its properties and their consistency with Standard Model (SM) predictions remains a central goal of the physics program at the Large Hadron Collider (LHC). While current measurements align with the SM predictions, unanswered questions suggest the potential for new physics beyond the SM (BSM). The first part of this thesis presents the first ATLAS search for Higgs boson pair production ($HH$) associated with top quarks ($t\bar{t}HH$), a rare process that provides direct access to BSM physics through the quartic top-Higgs coupling, offering unique opportunities to probe the Higgs sector of the SM and the electroweak symmetry breaking (EWSB) mechanism. This thesis establishes observed (expected) 95% confidence level upper limits on the SM $t\bar{t}HH$ production cross-sections of 30.8 (24.6) times the SM in leptonic final states, using the full Run 2 and partial Run 3 datasets, corresponding to integrated luminosities of 140 and 59 fb$^{-1}$, respectively. No significant excess in data above the SM expectations is seen. Additionally, the results are interpreted within the framework of Effective Field Theories by establishing limits on the top-Higgs quartic interaction. The second part of this dissertation also discusses the experimental challenges and opportunities presented by the High-Luminosity LHC (HL-LHC). The increased luminosity will enable precision measurements of the Higgs self-coupling and provide enhanced sensitivity to BSM physics. Key detector upgrades, such as the Inner Tracker (ITk) and improved $b$-jet tagging, photon reconstruction, and tau identification, are crucial for maximising the sensitivity of $HH$ searches, including $t\bar{t}HH$.This thesis describes ongoing efforts to address the computational challenges of Phase-II tracking at the HL-LHC. The expected Phase-II ITk tracking physics and computational performance is evaluated. It details improvements in the A Common Tracking Software (ACTS) framework, focusing on the implementation and optimization of the ITk seeding algorithm. Finally, the current expected tracking performance of the ACTS algorithms are presented together with a discussion on CPU optimisation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.736

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 science0.0010.001
Research integrity0.0000.001
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 head0.039
GPT teacher head0.178
Teacher spread0.139 · 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 designObservational
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

Citations0
Published2024
Admission routes1
Has abstractyes

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