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Record W2586591042 · doi:10.1007/jhep05(2017)015

Resonant slepton production and right sneutrino dark matter in left-right supersymmetry

2017· article· en· W2586591042 on OpenAlexafffund

Bibliographic record

VenueJournal of High Energy Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsConcordia University
FundersAgence Nationale de la RechercheNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework ProgrammeDepartment of Atomic Energy, Government of IndiaHarish-Chandra Research Institute
KeywordsLightest Supersymmetric ParticleNeutralinoSupersymmetryDark matterMinimal Supersymmetric Standard ModelSuperpartnerLarge Hadron ColliderAnnihilation

Abstract

fetched live from OpenAlex

Right-handed sneutrinos are natural components of left-right symmetric supersymmetric models where the gauge sector is extended to include right-handed weak interactions. Unlike in other models where right-handed sneutrinos are gauge singlets, here the right sneutrino is part of a doublet and could be a dark matter candidate whose annihilation proceeds via gauge interactions. We investigate this possibility, and find that relic density, low-energy observable and direct supersymmetry search constraints can be satisfied when the lightest supersymmetric particle is a right-handed sneutrino. We introduce benchmarks for left-right supersymmetric realizations where either a sneutrino or a neutralino is the lightest superpartner. We then study the LHC signals arising through resonant right-handed slepton production via a W R gauge-boson exchange that lead to final states enriched in leptons, additionally containing a large amount of missing transverse momentum, and featuring a low jet multiplicity. We find that such a resonant production would boost the chances of discovering these weakly interacting supersymmetric particles for a mass range extending beyond 1 TeV already with a luminosity of 100 fb−1. Finally, we compare sneutrino versus neutralino scenarios, and comment on differences with other sneutrino dark matter models.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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

Citations14
Published2017
Admission routes2
Has abstractyes

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