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Record W2013302396 · doi:10.1007/jhep03(2013)106

Reconstruction of Higgs bosons in the di-tau channel via 3-prong decay

2013· article· en· W2013302396 on OpenAlexfundno aff
Ben Gripaios, Keiko Nagao, Mihoko M. Nojiri, Kazuki Sakurai, B.R. Webber

Bibliographic record

VenueJournal of High Energy Physics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsnot available
FundersInstitut Périmètre de physique théoriqueScience and Technology Facilities CouncilUniversität ZürichMinistry of Education, Culture, Sports, Science and TechnologyKing's College LondonCERNYork UniversityLeverhulme Trust
KeywordsPhysicsParticle physicsHiggs bosonBranching fractionLeptonBosonNuclear physicsVertex (graph theory)Particle decayStandard Model (mathematical formulation)GraphElectronCombinatoricsMathematics

Abstract

fetched live from OpenAlex

Abstract We propose a method for reconstructing the mass of a particle, such as the Higgs boson, decaying into a pair of τ leptons, of which one subsequently undergoes a 3-prong decay. The kinematics is solved using information from the visible decay products, the missing transverse momentum, and the 3-prong τ decay vertex, with the detector resolution taken into account using a likelihood method. The method is shown to give good discrimination between a 125 GeV Higgs boson signal and the dominant backgrounds, such as Z 0 decays to ττ and W ± plus jets production. As a result, we find an improvement, compared to existing methods for this channel, in the discovery potential, as well as in measurements of the Higgs boson mass and production cross section times branching ratio.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2013
Admission routes1
Has abstractyes

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