Efficient framework for the examination of the field of view sensitivity of a field-widened birefringent interferometer
Bibliographic record
Abstract
An efficient approach is presented that allows the field of view sensitivities of a field-widened birefringent interferometer constructed from several stacked birefringent slabs to be examined. The approach utilizes a Jones matrix framework that is valid for birefringent slabs that have their optic axis parallel to the surface of the slab. It neglects Fresnel effects and multiple reflections, but accounts for birefringent splitting and does not neglect higher-order angular effects. The simplified approach allows the angular sensitivity of the optical path difference near the field-widened configuration to be examined in the presence of misalignment and mismatches between the components. Understanding these effects is critical to developing wide-field interferometers that can be utilized for imaging purposes. Here, we present the developed framework and apply it to examine the field of view effects of a three-element field-widened static birefringent interferometer that is being developed for the measurement of upper atmospheric winds. We examine the sensitivity of the device to rotational misalignment, mismatches, and wavelength shifts. Comparisons among the modeled interference fringes, output from Zemax optical design software, and lab observations are used to validate the approach. It is also shown that the approach accurately simulates parasitic fringes associated with unwanted coupling between extraordinary and ordinary waves at the interfaces.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".