Antimatter transport processes
Bibliographic record
Abstract
A comparison of the 1S-2S transitions of hydrogen and antihydrogen will yield a stringent test of CPT conservation. Necessarily, the antihydrogen atoms need to be trapped to perform high precision spectroscopy measurements. Therefore, an approximately 0.75 T deep neutral atom trap, equivalent to about 0.5 K for ground state (anti)hydrogen atoms, has been superimposed on a Penning-Malmberg trap in which the anti-atoms are formed. The antihydrogen atoms are produced following a number of steps. A bunch of antiprotons from the CERN Antiproton Decelerator is caught in a Penning-Malmberg trap and subsequently sympathetically cooled and then compressed using rotating wall electric fields. A positron plasma, formed in a separate accumulator, is transported to the main system and also compressed. Antihydrogen atoms are then formed by mixing the antiprotons and positrons. The velocity of the anti-atoms, and their binding energies, will strongly depend on the initial conditions of the constituent particles, for example their temperatures and densities, and on the details of the mixing process. In this paper the complete lifecycle of antihydrogen atoms will be presented, starting with the production of the constituent antiparticles and the description of the manipulations necessary to prepare them appropriately for antihydrogen formation. The latter will also be described, as will the possible fates of the anti-atoms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".