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Record W2336879965 · doi:10.1007/jhep08(2016)052

Shedding light on neutrino masses with dark forces

2016· article· en· W2336879965 on OpenAlexaff

Bibliographic record

VenueJournal of High Energy Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsUniversity of VictoriaPerimeter Institute
Fundersnot available
KeywordsNeutrinoBeam dumpStandard Model (mathematical formulation)Dark matterLarge Hadron ColliderSensitivity (control systems)Gauge bosonPhysics beyond the Standard Model

Abstract

fetched live from OpenAlex

Heavy right-handed neutrinos, N , provide the simplest explanation for the origin of light neutrino masses and mixings. If M N is at or below the weak scale, direct experimental discovery of these states is possible at accelerator experiments such as the LHC or new dedicated beam dump experiments; in these experiments, N decays after traversing a macroscopic distance from the collision point. The experimental sensitivity to right-handed neutrinos is significantly enhanced if there is a new “dark” gauge force connecting them to the Standard Model (SM), and detection of N can be the primary discovery mode for the new dark force itself. We take the well-motivated example of a B − L gauge symmetry and analyze the sensitivity to displaced decays of N produced via the new gauge interaction in two experiments: the LHC and the proposed SHiP beam dump experiment. In the most favorable case in which the mediator can be produced on-shell and decays to right handed neutrinos (pp → X + V B−L → X + N N ), the sensitivity reach is controlled by the square of the B − L gauge coupling. We demonstrate that these experiments could access neutrino parameters responsible for the observed SM neutrino masses and mixings in the most straightforward implementation of the see-saw mechanism.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.808
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.254
Teacher spread0.244 · 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 teacher head, 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

Citations74
Published2016
Admission routes1
Has abstractyes

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