Thermal Feedback in Coaxial SRF Cavities
Bibliographic record
Abstract
The phenomenon of Q-slope in SRF cavities is caused by a combination of thermal feedback and field-dependent surface resistance. There is currently no commonly accepted model of field-dependent surface resistance, and studies of Q-slope generally treat thermal feedback as a correction to whichever surface resistance model is being used. In the present study, we treat thermal feedback as a distinct physical effect whose effect on Q-slope is calculated using a novel finite-element code. We performed direct measurements of liquid helium pool boiling from niobium surfaces to obtain input parameters for the finite-element code. This code was used to analyze data from TRIUMF’s coaxial test cavity program, which has provided a rich dataset of Q-curves at temperatures between 1.7 K and 4.4 K at five different frequencies. Preliminary results show that thermal feedback makes only a small contribution to Q-slope at temperatures near 4.2 K, but has stronger effects as the bath temperature is lowered.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".