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Record W6963185731 · doi:10.18429/jacow-hiat2022-tup19

First Tests of Model-Based Linac Phasing in ISAC-II

2022· article· en· W6963185731 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACOW · 2022
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsPhaserLinear particle acceleratorBeam (structure)CalibrationEnergy (signal processing)Envelope (radar)

Abstract

fetched live from OpenAlex

As the e-linac and ARIEL facilities at TRIUMF progress, the impending complexity of operating three simultaneous rare ion beams (RIBs) approaches. To help prepare for this, a framework for the development of High Level Applications has been constucted, upon which multiple avenues for improvement towards model-based and automated tuning are being pursued. Along one of these avenues, the 40-cavity superconducting ISAC-II heavy ion linac has been studied and modelled in the envelope code transoptr. This has allowed for real-time integration through the on-axis fields, fitting focal strengths of solenoids to achieve desired beam waists, and calculation of necessary cavity phases to achieve a desired output energy for given input beam parameters. Initial tests have been completed, successfully phasing up to 37 cavities using the transoptr model and achieving a final output energy within 1% of the expected while maintaining nominal (>90%) transmission. A summary of the calibration of the model to the machine is given, followed by results of the phasing tests and an outlook towards future improvements.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.312

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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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