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Record W3212954477 · doi:10.1007/jhep03(2022)065

Vacuum structure of Alternative Left-Right Model

2022· article· en· W3212954477 on OpenAlexafffund
Mariana Frank, Chayan Majumdar, P. Poulose, Supriya Senapati, Urjit A. Yajnik

Bibliographic record

VenueJournal of High Energy Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaIndian Institute of Technology Bombay
KeywordsHiggs bosonScalar (mathematics)PhysicsParticle physicsBounded functionScalar potentialCharge (physics)Theoretical physicsMathematicsMathematical physicsGeometryMathematical analysis

Abstract

fetched live from OpenAlex

Abstract We investigate an Alternative Left-Right Model (ALRM) with SU(2)L as well as SU(2)R gauge groups, but unlike the traditional left-right symmetric models (LRSM) is not symmetric under the exchange of the fermion content. Interestingly, it can be embedded in E6, while its low energy Higgs structure resembles the LRSM, involving Higgs doublets χL,R and one Higgs bidoublet Φ. We analyze the scalar potential and the vacuum structure of the theory analytically to ensure the stability of scalar potential via bounded from below (BFB) and copositivity criteria, accompanied by a numerical study. We establish the necessary criteria for electric charge-preserving vacua, yielding constraints on various coupling parameters of the theory. Finally we obtain constraints on the parameters of the model from collider data on the masses of the Higgs scalars.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

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