An electron beam ion trap and source for re-acceleration of rare-isotope ion beams at TRIUMF
Bibliographic record
Abstract
Electron beam driven ionization can produce highly charged ions (HCIs) in a few well-defined charge states. Ideal conditions for this are maximally focused electron beams and an extremely clean vacuum environment. A cryogenic electron beam ion trap fulfills these prerequisites and delivers very pure HCI beams. The Canadian rare isotope facility with electron beam ion source-electron beam ion sources developed at the Max-Planck-Institut für Kernphysik (MPIK) reaches already for a 5 keV electron beam and a current of 1 A with a density in excess of 5000 A/cm2 by means of a 6 T axial magnetic field. Within the trap, the beam quickly generates a dense HCI population, tightly confined by a space-charge potential of the order of 1 keV times the ionic charge state. Emitting HCI bunches of ≈107 ions at up to 100 Hz repetition rate, the device will charge-breed rare-isotope beams with the mass-over-charge ratio required for re-acceleration at the Advanced Rare IsotopE Laboratory (ARIEL) facility at TRIUMF. We present here its design and results from commissioning runs at MPIK, including X-ray diagnostics of the electron beam and charge-breeding process, as well as ion injection and HCI-extraction measurements.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".