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Record W3164563389 · doi:10.1007/jhep08(2021)159

Tau-jet signatures of vectorlike quark decays to heavy charged and neutral Higgs bosons

2021· preprint· en· W3164563389 on OpenAlexafffund
Radovan Dermíšek, Enrico Lunghi, Navin McGinnis, Seodong Shin

Bibliographic record

VenueJournal of High Energy Physics · 2021
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsTRIUMF
FundersArgonne National LaboratoryNational Research FoundationNational Research Foundation of KoreaTRIUMFU.S. Department of Energy
KeywordsPhysicsParticle physicsHiggs bosonQuarkBosonLarge Hadron ColliderNuclear physicsTop quarkTwo-Higgs-doublet modelBottom quarkPhysics beyond the Standard Model

Abstract

fetched live from OpenAlex

Abstract We study 4b+ 2τand 4b+ 1τsignatures of heavy neutral and charged Higgs bosons originating from cascade decays of pair-produced new quarks. Decays of vectorlike quarks through heavy Higgses can easily dominate in the two Higgs doublet model of type-II, and the studied signatures are common to many possible decay chains. We design search strategies for these final states and discuss the mass ranges of heavy Higgs bosons and new quarks that can be explored at the Large Hadron Collider as functions of branching ratios in a model independent way. We further combine the results with a similar study focusing on decays which lead to a 6bfinal state and interpret the sensitivity to charged and neutral Higgs bosons and vectorlike quarks in the type-II two Higgs doublet model. We find that the LHC reach for their masses extends to well above 2 TeV in the case of an SU(2) doublet quark and to at least 1.8 TeV for a bottom-like SU(2) singlet quark in the whole range of tanβbetween 1 and 50.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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 designTheoretical or conceptual
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
Published2021
Admission routes2
Has abstractyes

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