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Magnet Design Considerations for an Ultralow Emittance Canadian Light Source

2018· article· en· W3160300753 on OpenAlexaffabout
Les Dallin, Drew Bertwistle

Bibliographic record

VenueJACOW · 2018
Typearticle
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsChicken Farmers of Saskatchewan (Canada)
Fundersnot available
KeywordsLight sourceThermal emittanceComputer scienceEnvironmental sciencePhysicsOpticsBeam (structure)

Abstract

fetched live from OpenAlex

The strong focusing requirements for ultralow emittance light sources result in high field magnets that are very close together. High fields are readily achieved by using small magnet gaps. This is possible due to the small beam sizes involved. Reduction in the physical aperture and the reduction in the good field region requirements results in magnets with compact transverse dimensions. The very strong focusing of the magnets results in very small drift spaces between the various magnetic elements. To keep these drift spaces clear magnets with recessed coils have been studied. In such magnets the coils do not stick out beyond the end of the magnet yoke in the longitudinal direction. By placing the coils on the outer yoke loss of efficiency can be avoided while maintaining good control of the higher order field harmonics. This is very well suited for quadrupole magnets where only two coils are required. Possible designs for gradient dipoles and sexutpoles are also considered.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.031
GPT teacher head0.231
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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
Published2018
Admission routes2
Has abstractyes

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