Gas-jet target with online interferometric thickness measurement for nuclear astrophysics
Bibliographic record
Abstract
A new jet gas target system has been developed for the Felsenkeller 5 MV underground ion accelerator for nuclear astrophysics. It provides either a 1.5 × 10 18 atoms/cm 2 thick cylindrical jet or a 8 × 10 17 atoms/cm 2 thick wall of nitrogen gas, with a surface of 10 × 10 mm 2 to be seen by the ion beam. The system includes a de Laval type nozzle and altogether five pumping stages: In addition to the jet catcher and the jet chamber surrounding it, there are three stages connecting the jet to the ion accelerator. Behind the jet chamber, as seen from the ion beam, a windowless static-type gas target and, subsequently, a beam calorimeter have been installed. This work describes the offline tests of the gas target system prior to its installation on the beam line of the Felsenkeller accelerator. The thickness of the jet has been determined using three different methods: By computational fluid dynamics simulations, with a Mach–Zehnder interferometer, and by α -energy loss using a mixed α source. The three methods were shown to be in agreement. For 0-6 bar inlet gas pressure, a linear relationship between inlet pressure and jet thickness has been found. Different shapes of de Laval type inlet nozzles, both circular and slit-type, have been manufactured from fused silica glass or stainless steel and tested using measurements and simulations. The power and stability of the beam calorimeter have been tested. The interferometry has been shown to work reliably and to give two-dimensional projections of the gas jet with sub-mm resolution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".