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Record W2266912531 · doi:10.1007/jhep12(2015)088

OPE for all helicity amplitudes II. Form factors and data analysis

2015· article· en· W2266912531 on OpenAlexafffund
Benjamin Basso, João Caetano, Lucía Córdova, Amit Sever, Pedro Vieira

Bibliographic record

VenueJournal of High Energy Physics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicBlack Holes and Theoretical Physics
Canadian institutionsPerimeter InstituteUniversity of Waterloo
FundersInstitut Périmètre de physique théoriqueICTP South American Institute for Fundamental ResearchIsraeli Centers for Research ExcellenceIsrael Science FoundationFundação para a Ciência e a TecnologiaFundação de Amparo à Pesquisa do Estado de São PauloNatural Sciences and Engineering Research Council of CanadaEuropean CommissionPlanning and Budgeting Committee of the Council for Higher Education of IsraelAbdus Salam International Centre for Theoretical PhysicsGovernment of Canada
KeywordsHelicityAmplitudePhysicsPlanarOperator product expansionProduct (mathematics)Operator (biology)Simple (philosophy)Mathematical physicsQuantum electrodynamicsParticle physicsTheoretical physicsMathematicsQuantum mechanicsComputer scienceGeometryPhilosophyChemistry

Abstract

fetched live from OpenAlex

We present the general flux tube integrand for MHV and non-MHV amplitudes, in planar $$ \mathcal{N}=4 $$ SYM theory, up to a group theoretical rational factor. We find that the MHV and non-MHV cases only differ by simple form factors which we derive. This information allows us to run the operator product expansion program for all sorts of non-MHV amplitudes and to test the recently proposed map with the so called charged pentagons transitions. Perfect agreement is found, on a large sample of non-MHV amplitudes, with the perturbative data available in the literature.

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)0.005
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: none
Teacher disagreement score0.022
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.002

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 head0.039
GPT teacher head0.290
Teacher spread0.251 · 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

Citations61
Published2015
Admission routes2
Has abstractyes

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