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Record W4387176955 · doi:10.22323/1.445.0038

The PIONEER experiment to explore lepton universality using rare pion decays

2023· article· en· W4387176955 on OpenAlexaboutno aff
T. Iwamoto

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsnot available
FundersJapan Society for the Promotion of SciencePaul Scherrer Institut
KeywordsPhysicsUniversality (dynamical systems)PionLeptonParticle physicsMesonNuclear physicsUnitarityPhysics beyond the Standard ModelQuantum mechanicsElectron

Abstract

fetched live from OpenAlex

Recently, several measurement results suggesting a violation of lepton universality in $B$ meson decays have been published, attracting attention as possible evidence of new physics. In the PIONEER experiment, the charged pion decay $\pi^{+} \to e^{+}\nu$ will precisely be measured to obtain the decay ratio R$_{e/\mu}$ = B($\pi^{+} \to e^{+}\nu$)/B($\pi^{+} \to \mu^{+}\nu$) with a precision of 0.01\%, which is an order of magnitude better than the previous measurements, to verify lepton universality to the limit of theoretical sensitivity. This corresponds to the search for new particles with PeV-scale masses through quantum effects. In the second stage of the PIONEER experiment, we will also perform a precise measurement of the beta decay $\pi^{+} \to \pi^{0}e^{+}\nu$ of charged pions to verify the CKM unitarity. The excellent measurement accuracy required for the experiment will be achieved by making full use of the liquid xenon total absorption calorimeter technology developed for the MEG experiment at the University of Tokyo and KEK. In addition, the development of an active target using the latest LGAD technology is underway internationally in order to accurately suppress the reaction near the decay point. The proposal for the PIONEER experiment was approved by the Paul Scherrer Institute (PSI) in Switzerland in 2022, and is being developed and prepared in international collaboration with Japan, the United States, Canada, Switzerland, Germany, and other countries.

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 score0.444
Threshold uncertainty score0.568

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 communication0.0000.000
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 head0.107
GPT teacher head0.366
Teacher spread0.259 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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