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Record W2135572095 · doi:10.1063/1.3258840

Magnetic multipole induced zero-rotation frequency bounce-resonant loss in a Penning–Malmberg trap used for antihydrogen trapping

2009· article· en· W2135572095 on OpenAlexaff
Gorm Bruun Andresen, W. Bertsche, C. C. Bray, E. Butler, C. L. Cesar, S. C. Chapman, M. Charlton, J. Fajans, M. Fujiwara, D. R. Gill, W. N. Hardy, R. Hayano, M. E. Hayden, A. J. Humphries, R. Hydomako, L. V. Jørgensen, Sean Kerrigan, J. Keller, L. L. Kurchaninov, R. Lambo, N. Madsen, P. Nolan, K. Olchanski, A. Olin, A. Povilus, P. Pusa, F. Robicheaux, E. Sarid, S. Seif El Nasr, D. M. Silveira, James Storey, R. I. Thompson, D. P. van der Werf, J. S. Wurtele, Y. Yamazaki

Bibliographic record

VenuePhysics of Plasmas · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of CalgarySimon Fraser UniversityUniversity of British ColumbiaTRIUMF
FundersEngineering and Physical Sciences Research Council
KeywordsAntihydrogenPhysicsAntiprotonMultipole expansionPenning trapTrap (plumbing)TrappingAtomic physicsRotation (mathematics)Nuclear physicsProtonQuantum mechanicsElectronAntimatter

Abstract

fetched live from OpenAlex

In many antihydrogen trapping schemes, antiprotons held in a short-well Penning–Malmberg trap are released into a longer well. This process necessarily causes the bounce-averaged rotation frequency Ω¯r of the antiprotons around the trap axis to pass through zero. In the presence of a transverse magnetic multipole, experiments and simulations show that many antiprotons (over 30% in some cases) can be lost to a hitherto unidentified bounce-resonant process when Ω¯r is close to zero.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.263
Teacher spread0.245 · 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 designSimulation or modeling
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

Citations5
Published2009
Admission routes1
Has abstractyes

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