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Record W2211867685 · doi:10.1007/jhep04(2016)084

Effective interpretations of a diphoton excess

2016· article· en· W2211867685 on OpenAlexafffund
Laure Berthier, James M. Cline, William Shepherd, Michael Trott

Bibliographic record

VenueJournal of High Energy Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaVillum Fonden
KeywordsPhysicsParticle physicsHiggs bosonPseudoscalarPhenomenology (philosophy)Scalar (mathematics)Physics beyond the Standard ModelBosonScalar bosonQuark

Abstract

fetched live from OpenAlex

We discuss some consistency tests that must be passed for a successful explanation of a diphoton excess at larger mass scales, generated by a scalar or pseudoscalar state, possibly of a composite nature, decaying to two photons. Scalar states at mass scales above the electroweak scale decaying significantly into photon final states generically lead to modifications of Standard Model Higgs phenomenology. We characterise this effect using the formalism of Effective Field Theory (EFT) and study the modification of the effective couplings to photons and gluons of the Higgs. The modification of Higgs phenomenology comes about in a variety of ways. For scalar 0+ states, a component of the Higgs and the heavy boson can mix. Lower energy phenomenology gives a limit on the mixing angle, which gets generated at one loop in any theory explaining the diphoton excess. Even if the mixing angle is set to zero, we demonstrate that a relation exists between lower energy Higgs data and a massive scalar decaying to diphoton final states. If the new boson is a pseudoscalar, we note that if it is composite, it is generic to have an excited scalar partner that can mix with a component of the Higgs, which has a stronger coupling to photons. In the case of a pseudoscalar, we also characterize how lower energy Higgs phenomenology is directly modified using EFT, even without assuming a scalar partner of the pseudoscalar state. We find that naturalness concerns can be accommodated, and that pseudoscalar models are more protected from lower energy constraints.

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)0.002
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.006
Scholarly communication0.0040.007
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.005
GPT teacher head0.241
Teacher spread0.236 · 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
GenreOther

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

Citations72
Published2016
Admission routes2
Has abstractyes

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