Development of a technique for the precise determination of atomic lifetimes based on photon echoes
Bibliographic record
Abstract
We explore the sensitivity of the photon echo technique for achieving precise measurements of atomic lifetimes. Using short-pulse excitation of atomic rubidium vapor, we report the most statistically precise measurement of ($26.11\ifmmode\pm\else\textpm\fi{}0.03$) ns for the $5^{2}{P}_{3/2}$ lifetime. This statistical uncertainty of 0.11% was achieved in a total data acquisition time of 4 h over several weeks and rivals the most precise measurements in this atomic system. The experiment primarily relies on heterodyne detection and exploits the signal-to-noise ratio of the coherent release of energy along the direction of excitation, which is an exponential decay as a function of pulse separation $T$, as well as large repetition rates that are feasible in a gently heated vapor cell. We have developed an understanding of the technical limitations responsible for lifetime measurement instabilities on the basis of a simple model, which also enables us to propose a feedback scheme to limit these effects. Studies of the fractional uncertainty of the lifetime suggest that the statistical precision of this technique can be extended to the level of 0.03% in 10 min of data acquisition if the technical limitations are addressed. This level of precision has so far been exceeded by only one other lifetime measurement. Under these conditions, a rigorous investigation of systematic effects could potentially allow the echo technique to achieve the most accurate measurement of atomic lifetimes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".