A new approach for the ortho-positronium lifetime determination in a vacuum cavity
Bibliographic record
Abstract
Currently, the experimental uncertainty for the determination of the ortho-positronium (o-Ps) decay rate is at 150 ppm precision; this is two orders of magnitude lower than the theoretical one, at 1 ppm level. Here we propose a new proof of concept experiment aiming for an accuracy of 100 ppm to be able to test the second-order correction in the calculations, which is $\simeq 45\left(\frac{\alpha}{\pi}\right)^2\approx 200$ ppm. The improvement relies on a new technique to confine the o-Ps in a vacuum cavity. Moreover, a new method was developed to subtract the time dependent pick-off annihilation rate of the fast backscattered positronium from the o-Ps decay rate prior to fitting the distribution. Therefore, this measurement will be free from the systematic errors present in the previous experiments. The same experimental setup developed for our recent search for invisible decay of ortho-positronium is being used. The precision will be limited by the statistical uncertainty, thus, if the expectations are fulfilled, this experiment could pave the way to reach the ultimate accuracy of a few ppm level to confirm or confront directly the higher order QED corrections. This will provide a sensitive test for new physics, e.g. a discrepancy between theoretical prediction and measurements could hint the existence of an hidden sector which is a possible dark matter candidate.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".