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On-Line Retuning of ISAC Linac Beam with Quadrupole Scan Tomography

2021· article· en· W3202355902 on OpenAlexaff
Olivier Shelbaya, R. Baartman, Paul M. Jung, O. Kester, Spencer Kiy, Thomas Planche, Yi‐Nong Rao, Stephanie Rädel

Bibliographic record

VenueJACOW · 2021
Typearticle
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsTRIUMF
Fundersnot available
KeywordsLinear particle acceleratorBeam (structure)Line (geometry)QuadrupolePhysicsNuclear medicineMedical physicsOpticsMedicineGeometryMathematics

Abstract

fetched live from OpenAlex

The method of tomographic reconstruction has been in use at TRIUMF and elsewhere for several years, allowing for the beam diagnostic extraction of elements of the beam matrix on-line. One of the more recent applications of the technique at ISAC consists of using the measured density distribution as the input parameters for a real-time tune re-computation. This technique is advantageous since it does not require installation of dedicated emittance meters, but can instead be carried out with existing position monitors. Instead of requiring an operator to manually re-tune quadrupoles in a matching section, which can be time consuming, the technique allows for a fast and reproducible means to precisely control the beam and can be proceduralized for use by operators tuning 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.425

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 head0.010
GPT teacher head0.210
Teacher spread0.201 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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