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Record W2994989454 · doi:10.1007/jhep03(2020)117

The radiation valley and exotic resonances in Wγ production at the LHC

2020· article· en· W2994989454 on OpenAlexaff

Bibliographic record

VenueJournal of High Energy Physics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of TorontoPerimeter Institute
Fundersnot available
KeywordsElectroweak interactionLarge Hadron ColliderResonance (particle physics)AmplitudeLuminosityRadiationSpin (aerodynamics)Standard Model (mathematical formulation)Range (aeronautics)

Abstract

fetched live from OpenAlex

Abstract The tree-level partonic angular distribution of Standard Model Wγ production possesses a feature known as the Radiation Amplitude Zero (RAZ) where destructive interference causes the cross section to vanish. At the proton level the exact cancellation disappears, however, one can find a dip in the central region of the angular distributions, here called the Radiation Valley (RV). In this paper, we show how the sensitivity for W(ℓv)γ resonances can be significantly improved if one focuses on events in the RV region. Using this technique, we find that the LHC could probe a larger range of resonance masses, equivalent to increasing the luminosity by a factor of 2–3 over conventional searches. The exact increase depends on the spin of the Wγ resonance and exactly how it couples to electroweak gauge bosons.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.225
Teacher spread0.211 · 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 designSimulation or modeling
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

Citations12
Published2020
Admission routes1
Has abstractyes

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