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Linear coupling and tune adjustment for the 500 MeV cyclotron

2023· article· en· W4387331536 on OpenAlexafffund
L. G. Zhang, Yi‐Nong Rao, R. Baartman, Y. Bylinskii, Thomas Planche

Bibliographic record

VenuePhysical Review Accelerators and Beams · 2023
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
FundersNational Research Council CanadaTRIUMF
KeywordsBetatronPhysicsCyclotronCyclotron resonanceCoupling (piping)AmplitudeBeam (structure)Resonance (particle physics)AccelerationNuclear physicsMagnetic fieldComputational physicsNuclear magnetic resonanceAtomic physicsOpticsClassical mechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

The horizontal and vertical betatron tunes vary during acceleration in TRIUMF 500 MeV cyclotron, leading the beam to cross the linear coupling resonance ${\ensuremath{\nu}}_{r}\ensuremath{-}{\ensuremath{\nu}}_{z}=1$ multiple times. This results in a measurable transfer of betatron amplitude between the horizontal and the vertical planes. In this paper, we report the observation of an unanticipated crossing of this resonance which cannot be understood from the tune diagram derived from the original magnetic field survey of the cyclotron. We present how we have resolved this conundrum and the technique we have developed to measure the vertical tune, which is particularly challenging in a cyclotron. To correct the deleterious effects of this particular crossing, rather than canceling the resonance driving term, a new strategy was adopted whereby the vertical tune is adjusted locally and pushed away from the resonance line. This is accomplished using the axial field of trim coils, while also maintaining the overall isochronism of the machine.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.523

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 head0.024
GPT teacher head0.294
Teacher spread0.270 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

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