Abstract SUPERCONDUCTING RF SYSTEMS FOR LIGHT SOURCES?
Bibliographic record
Abstract
with extremely high beam stability to maintain their source brightness characteristics, and this must be achieved with large multi-bunch beam currents. With the provision of very low emittance and use of high harmonic output from insertion devices, control of beam current instability thresholds is essential. At present no operating Light Source uses superconducting technology for its main RF system, although several such proposals are now being made and have been discussed at a recent international Workshop on this topic. The paper reports on the potential effect of a superconducting RF solution on these thresholds, together with the technical and economic realisation, operating reliability and efficiency, with particular emphasis on the UK DIAMOND project. Reference is made to the Workshop conclusions. 1 WHY SRF? Superconducting RF (SRF) systems exhibit several advantages compared with room temperature systems. Because the surface resistivity of SRF structures is extremely low the dissipated power in the structure is low and higher accelerating voltages can be more easily produced. This gives the designer the option of using less efficient designs which exhibit lower Higher Order Modes (HOM) and easier methods of damping them. Both the smaller number of required cavities and their better damped HOMs lead to increased thresholds for beam instabilities. It is also apparent that SRF systems have an overall lower energy consumption, even taking into account that consumed by the cryogenic plant, so that an equivalent room temperature system would be more costly to both purchase and operate. 2 APPLICABLE SRF EXAMPLES Although no light source currently uses SRF the existing Taiwan light source SRRC [1] and the Canadian light source project [2] both intend to install SRF systems. These will be procured from industry and will be manufactured to the CESR design under licence. The SOLEIL project also proposes to use SRF. The CESR storage ring at Cornell University [3] utilises four solid niobium 500 MHz single cell
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".