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Record W1833190085 · doi:10.1088/1674-1137/35/6/016

Power coupler kick of the TRIUMF ICM capture cavities

2011· article· en· W1833190085 on OpenAlexaff
Fang Yan

Bibliographic record

VenueChinese Physics C · 2011
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsPhysicsThermal emittanceElectronDeflection (physics)Offset (computer science)Beam (structure)BunchesKlystronAdiabatic processLinear particle acceleratorNuclear physicsOptics

Abstract

fetched live from OpenAlex

The TRIUMF Injector CryoModule (ICM) adapted two superconducting single cavities as the capture section for the low injecting energy of 100 keV electrons. Coupler kick induced beam deflection and projected emittance growth are one of the prime concerns of the beam stability, especially at low energies. In low energy applications, the electron velocity changes rapidly inside the cavity, which makes the numerical analysis much more complicated. The commonly used theoretical formulas of the direct integral or the Panofsky-Wenzel theorem is not suitable for the kick calculation of β < 1 electrons. Despite that, the above mentioned kick calculation method doesn't consider injecting electron energy, the beam offset due to the coupler kick may not be negligible because of the low injection energy even if the kick is optimized. Thus the beam dynamics code TRACK is used here for the simulation of the power coupler kick perturbation. The coupler kick can be compensated for by a judicious choice of the coupler position in successive cavities from upstream to downstream. The simulation shows that because of the adiabatic damping by the following superconducting 9-cell cavity, even for the worst orbit distortion case after two capture cavities, the kick is still acceptable at the exit of the ICM after reaching 10 MeV. This paper presents the analysis of the transverse kick and the projected emittance growth induced by the coupler for β < 1 electrons. The simulated results of the TRIUMF ICM capture cavities are described and presented.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.299

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 head0.011
GPT teacher head0.199
Teacher spread0.187 · 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 designObservational
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

Citations1
Published2011
Admission routes1
Has abstractyes

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