Cold antihydrogen experiments and radial compression of antiproton clouds in the ALPHA apparatus at CERN
Bibliographic record
Abstract
Antihydrogen is the simplest neutral antimatter atom. Precision comparisons between hydrogen and antihydrogen would provide stringent tests of CPT (charge conjugation/parity transformation/time reversal) invariance and the weak equivalence principle. In the last few years, the ALPHA collaboration has produced, and trapped antihydrogen. Most recently, this collaboration has probed antihydrogen’s internal structure by inducing hyperfine transitions in ground state atoms. In this thesis, many details of the cold antihydrogen formation, trapping and measurements of antihydrogen performed in the ALPHA apparatus are presented, with a focus on antiproton cloud compression. Such compression is an important tool for the formation and trapping of cold antihydrogen, since it allows control of the radial size and density of the antiproton cloud. Compression of non-neutral plasmas can be achieved using a rotating time-varying azimuthal electric field, which has been called rotating wall technique. In this work, we have observed a new mechanism for compression of a non-neutral plasma, specifically where antiprotons embedded in an electron plasma are compressed by a rotating wall drive at a frequency close to the sum of the axial bounce and rotation frequencies (in a frequency range of 50 – 750 kHz). The radius of the antiproton cloud is reduced by up to a factor of 20 with the smallest radius measured to be ∼ 0.2 mm. We have studied antiproton cloud compression as a function of the rotating wall frequency, the duration of compression, the rotating wall amplitude, the numbers of electrons and antiprotons, the magnetic field and the shape of the potential well. The frequency range over which compression is evident is compared to the sum of the antiproton bounce frequency and the system’s rotation frequency. It is suggested that bounce resonant transport is a likely explanation for the compression of antiproton clouds in this regime.
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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 | 0.001 | 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".