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Record W3185772506 · doi:10.1103/physrevd.104.115032

Renormalizable models of flavor-specific scalars

2021· preprint· en· W3185772506 on OpenAlexafffund
Brian Batell, A. Freitas, Ahmed Ismail, David McKeen, Mudit Rai

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2021
Typepreprint
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsTRIUMF
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaTRIUMFU.S. Department of EnergyNational Science Foundation
KeywordsParticle physicsPhysicsElectroweak interactionHiggs bosonPhysics beyond the Standard ModelPhenomenology (philosophy)Scalar (mathematics)QuarkFlavorObservableNaturalnessLarge Hadron ColliderLittle HiggsTheoretical physicsHiggs fieldQuantum mechanics

Abstract

fetched live from OpenAlex

New light singlet scalars with flavor-specific couplings represent a phenomenologically distinctive and flavor-safe alternative to the well-studied possibility of Higgs-portal scalars. However, in contrast to the Higgs portal, flavor-specific couplings require an ultraviolet completion involving new heavy states charged under the Standard Model gauge symmetries, leading to a host of additional novel phenomena. Focusing for concreteness on a scenario with up-quark-specific couplings, we investigate two simple renormalizable completions, one with an additional vectorlike quark and another featuring an extra scalar doublet. We consider the implications of naturalness, flavor- and $CP$ violation, electroweak precision observables, and direct searches for the new states at the LHC. These bounds, while being model dependent, are shown to probe interesting regions in the parameter space of the scalar mass and its low-energy effective coupling, complementing the essential phenomenology of the low-energy effective theory at a variety of low and medium energy experiments.

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)0.002
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.035
GPT teacher head0.409
Teacher spread0.374 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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