High-power Fixed-Field Accelerators
Bibliographic record
Abstract
Abstract We report the state of the field of High-Power Fixed-Field Accelerators (with an emphasis on cyclotrons) as discussed by international experts during a three-day workshop of the same name in 2021. The workshop was part of the Snowmass'21 Community Planning Exercise. Here, we take stock of the world inventory of high-power fixed-field accelerators, assess available beam currents and beam powers, and investigate limitations. Furthermore, we evaluate the role of these machines in particle physics, directly used or as injectors to other machines, and in industry, as drivers for (medical) isotope production and, potentially, for accelerator-driven systems and sub-critical reactors. Finally, we discuss novel concepts and cutting-edge developments to push the available current higher at several energy scales, thereby increasing relative power. Highlights include new spiral inflector types, direct RFQ injection, H 2 + acceleration, utilizing vortex motion, and self-extraction schemes. We also discuss modern computational frameworks to optimize accelerators more efficiently, and better describe the relevant physical processes in simulations.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".