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Record W2889066136 · doi:10.1142/s0217751x19400128

New physics implication of Higgs precision measurements

2019· article· en· W2889066136 on OpenAlexaff

Bibliographic record

VenueInternational Journal of Modern Physics A · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsHiggs bosonLarge Hadron ColliderPhysics beyond the Standard ModelColliderStandard Model (mathematical formulation)Minimal Supersymmetric Standard ModelHiggs mechanismHiggs field

Abstract

fetched live from OpenAlex

Studying the properties of the Higgs boson can be an important window to explore the physics beyond the Standard Model (SM). In this work, we present studies on the implications of the Higgs precision measurements at future Higgs Factories. We perform a global fit to various Higgs search channels to obtain the 95% C.L. constraints on the model parameter spaces of two-Higgs Doublet Model (2HDM) and Minimal Supersymmetric Standard Model (MSSM). In the 2HDM, we analyze tree-level effects as well as one-loop contributions from the heavy Higgs bosons. The strong constraints on [Formula: see text], heavy Higgs masses and their mass splitting are complementary to direct search of the LHC as well as possible future [Formula: see text] pole precision measurements. For the MSSM, we study both the Higgs couplings and mass precisions. The constraints on the CP-odd Higgs mass [Formula: see text] and stop mass scale [Formula: see text] can be complementary to the direct search of HL-LHC. We also compare the sensitivity of various future Higgs factories, namely, Circular Electron Positron Collider (CEPC), Future Circular Collider (FCC)-ee and International Linear Collider (ILC).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.409

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 science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.307
Teacher spread0.279 · 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 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

Citations7
Published2019
Admission routes1
Has abstractyes

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