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Precision Measurement of the Electron’s Electric Dipole Moment Using Trapped Molecular Ions

2017· article· en· W2599625058 on OpenAlexfundno aff
William B. Cairncross, Daniel Gresh, Matt Grau, Kevin C. Cossel, Tanya Roussy, Yiqi Ni, Yan Zhou, Jun Ye, Eric Cornell

Bibliographic record

VenuePhysical Review Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute of Standards and TechnologyNational Science Foundation
KeywordsPhysicsMetastabilityAtomic physicsDipoleElectric dipole momentElectronIonMoment (physics)Resonance (particle physics)Quantum mechanics

Abstract

fetched live from OpenAlex

We describe the first precision measurement of the electron's electric dipole moment (d_{e}) using trapped molecular ions, demonstrating the application of spin interrogation times over 700 ms to achieve high sensitivity and stringent rejection of systematic errors. Through electron spin resonance spectroscopy on ^{180}Hf^{19}F^{+} in its metastable ^{3}Δ_{1} electronic state, we obtain d_{e}=(0.9±7.7_{stat}±1.7_{syst})×10^{-29} e cm, resulting in an upper bound of |d_{e}|<1.3×10^{-28} e cm (90% confidence). Our result provides independent confirmation of the current upper bound of |d_{e}|<9.4×10^{-29} e cm [J. Baron et al., New J. Phys. 19, 073029 (2017)NJOPFM1367-263010.1088/1367-2630/aa708e], and offers the potential to improve on this limit in the near future.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.342
Teacher spread0.304 · 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 designBench or experimental
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

Citations391
Published2017
Admission routes1
Has abstractyes

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