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Record W2254567012 · doi:10.1007/jhep12(2015)165

QCD corrections to pair production of Type III Seesaw leptons at hadron colliders

2015· article· en· W2254567012 on OpenAlexaff

Bibliographic record

VenueJournal of High Energy Physics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsInstitute of Particle Physics
FundersUniversity of Pittsburgh
KeywordsLeptonSeesaw molecular geometryPair productionResummationQuantum chromodynamicsHadronContext (archaeology)Muon

Abstract

fetched live from OpenAlex

If kinematically accessible, hadron collider experiments provide an ideal laboratory for the direct production of heavy lepton partners in Seesaw models. In the context of the Type III Seesaw Mechanism, the $$ \mathcal{O}\left({\alpha}_s\right) $$ rate and shape corrections are presented for the pair production of hypothetical, heavy SU(2) L triplet leptons in pp collisions at $$ \sqrt{s} $$ = 13, 14 and 100TeV. The next-to-leading order (NLO) K-factors span, approximately, K NLO = 1.1 − 1.4 for both charged current and neutral current processes over a triplet mass range m T = 100 GeV − 2 TeV. Total production cross sections exhibit a − 6 % + 5 % scale dependence at 14 TeV and ±1% at 100 TeV. The NLO differential K-factors for heavy lepton kinematics are largely flat, suggesting that na¨ıve scaling by the total K NLO is reasonably justified. The resummed transverse momentum distribution of the dilepton system is presented at leading logarithmic (LL) accuracy. The effects of resummation are large in TeV-scale dilepton systems. Discovery potential to heavy lepton pairs at 14 and 100 TeV is briefly explored: at the High-Luminosity LHC, we estimate a 4.8 − 6.3σ discovery potential maximally for m T = 1.5 − 1.6 TeV after 3000 fb−1. With 300 (3000) fb−1, there is 2σ sensitivity up to m T = 1.3 − 1.4 TeV (1.7 − 1.8 TeV) in the individual channels. At 100 TeV and with 10 fb−1, a 5σ discovery can be achieved for m T = 1.4 − 1.6 TeV. Due to the factorization properties of Drell-Yan-type systems, the fixed order and resummed calculations reduce to convolutions over tree-level quantities.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.255
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
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

Citations38
Published2015
Admission routes1
Has abstractyes

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