Characterizing flat-top laser beams using standard beam parameters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We examine the correspondence between various models describing flat-top laser beam profiles using two standard parameters; namely, the M 2 factor and the kurtosis parameter. Numerical expressions for M 2 , based on the second moment of the beam irradiance distribution in the near and far fields and for the kurtosis parameter, k, based on the fourth moment at the near field, are obtained. Plots of k in the near field versus M 2 demonstrate the similarities between the different analytical models used to describe flat-top profiles. Using the Padé approximation, a relationship between k and M 2 , a new reference formula, is derived that predicts the values of M 2 to within less than a percent for these flattened beams. This method is then extended to define numerical expressions relating the beam parameters (i.e., M 2 and k) and the parameters describing the beam characteristic in each analytical model (model parameters). The results obtained using the Padé method are used to describe the output beam profiles for a high power copper vapour laser fitted with an unstable resonator.PACS Nos.: 42.55.–f, 42.55.Lt, 42.60.–v
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.
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 | 0.000 | 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 it