Improved determination of the optical constants of anisotropic thin films by ellipsometry using ant colony fitting algorithms
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Bibliographic record
Abstract
Birefringent TiO2 thin films were characterized using spectroscopic ellipsometry. Ellipsometric data were fitted to a model, taking into account the anisotropic nature of the film and the coherence length of the source being shorter than the thickness of the substrate. Using a conventional gradient-based algorithm often produced a wrong set of optical constants corresponding to a local minimum of the objective function, unless the initial guess was carefully chosen. Using an optimization algorithm inspired by the foraging behavior of ants makes it possible to systematically find that small region in the parameter space where the best solution lies, without a priori knowledge of the optical properties of the sample. The proposed method is especially suitable for samples with unknown optical properties or complex materials, such as anisotropic thin films, for which a large number of parameters are needed to describe them.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 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