Strategy for Bayesian optimised Beam Steering at TRIUMF-ISAC's MEBT and HEBT Beamlines
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In preparation for operation of multiple Rare Isotope Beams (RIBs) when the Advanced Rare Isotope Laboratory (ARIEL) becomes operational, TRIUMF embarked on a program of advanced beam tuning applications and machine learning tools. The strategy for operationalizing Bayesian optimisation for beam steering purposes is being developed. A previously reported centroid correction algorithm is used to tune accelerated charged particle beams at TRIUMF's ISAC postaccelerator facility. We present findings and results from multiple machine development experiments conducted between October and November 2024, as part of a pivot toward semi-automated machine tuning methods. These findings were instrumental in shaping the tuning strategy for the medium and high energy beam transport (MEBT, HEBT) lines at ISAC, by sequentially optimising sub-sections of the beamlines.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it