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Record W2010488273 · doi:10.1063/1.4801067

Experimental and computational study of the injection of antiprotons into a positron plasma for antihydrogen production

2013· article· en· W2010488273 on OpenAlexaff
C. Amole, M. D. Ashkezari, M. Baquero-Ruiz, W. Bertsche, E. Butler, A. Capra, C. L. Cesar, M. Charlton, A. Deller, S. Eriksson, J. Fajans, T. Friesen, M. Fujiwara, D. R. Gill, A. Gutiérrez, J. S. Hangst, W. N. Hardy, M. E. Hayden, C. A. Isaac, S. Jonsell, L. L. Kurchaninov, A. Little, N. Madsen, J. T. K. McKenna, S. Menary, S. C. Napoli, K. Olchanski, Å. Olin, P. Pusa, C. Ø. Rasmussen, F. Robicheaux, E. Sarid, C. R. Shields, D. M. Silveira, C. So, S. Stracka, R. I. Thompson, D. P. van der Werf, J. S. Wurtele, Andrey Zhmoginov

Bibliographic record

VenuePhysics of Plasmas · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsCanadian Institute for Advanced ResearchYork UniversityUniversity of British ColumbiaUniversity of VictoriaUniversity of CalgarySimon Fraser UniversityTRIUMF
FundersScience and Technology Facilities CouncilEngineering and Physical Sciences Research Council
KeywordsAntihydrogenAntiprotonPhysicsPositronCPT symmetryNuclear physicsAtomic physicsPlasmaPenning trapTrappingAntimatterProtonElectronClassical mechanics

Abstract

fetched live from OpenAlex

One of the goals of synthesizing and trapping antihydrogen is to study the validity of charge–parity–time symmetry through precision spectroscopy on the anti-atoms, but the trapping yield achieved in recent experiments must be significantly improved before this can be realized. Antihydrogen atoms are commonly produced by mixing antiprotons and positrons stored in a nested Penning-Malmberg trap, which was achieved in ALPHA by an autoresonant excitation of the antiprotons, injecting them into the positron plasma. In this work, a hybrid numerical model is developed to simulate antiproton and positron dynamics during the mixing process. The simulation is benchmarked against other numerical and analytic models, as well as experimental measurements. The autoresonant injection scheme and an alternative scheme are compared numerically over a range of plasma parameters which can be reached in current and upcoming antihydrogen experiments, and the latter scheme is seen to offer significant improvement in trapping yield as the number of available antiprotons increases.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.303

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 head0.009
GPT teacher head0.248
Teacher spread0.240 · 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 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

Citations29
Published2013
Admission routes1
Has abstractyes

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