Highly accurate transition frequencies in the H<sub>2</sub> Lyman and Werner absorption bands
Bibliographic record
Abstract
The transition frequencies of low-J excitation lines in the B1Σu+ X1Σg+,(ν′,0) Lyman bands have been measured for ν′ = 218 and in the C1ΠuX1Σg+,(ν′,0) Werner bands for ν′ = 04, using a narrow-band tunable extreme UV laser source at wavelengths λ = 92105 nm in conjunction with the technique of 1 + 1′ two-photon ionization. The measurements can be divided into three categories for which varying absolute accuracies were obtained. Special focus was on the B, ν′ = 25 bands, where an accuracy of 0.004 cm1 or δv/v = 4 x 108 is achieved. For transitions to B, ν′ ≤ 13 and C, ν′ ≤ 3 states the accuracy is 0.005 cm1 or δv/v = 5 x 108. Due to a different frequency mixing scheme uncertainties for B, ν′ ≥ 13 and C, ν′ = 4 are at the level of 0.011 cm1 or δv/v = 1.1 x 107. Inspection of combination differences between R(J) and P(J + 2) lines shows that the accuracies are even better than estimated in the error budget. Based on the measurements of 138 spectral lines and the known combination differences, transition frequencies of 60 P-lines could be calculated as well, so that a data base of 198 accurately calibrated lines results for the Lyman and Werner bands of H2. Key words: vacuum UV, molecular spectroscopy, hydrogen, precision metrology.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".