Geometrical-based quasi-aspheric surface description and design method for miniature, low-distortion, wide-angle camera lens
Why this work is in the frame
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Bibliographic record
Abstract
In addition to utilizing traditional aspheric surfaces, complicated geometric curves for meeting stringent design requirements can also be adopted in optical systems. In this paper, we investigate two geometric shape modeling schemes, namely, pedal and cosine curves, which allow for representation of an S-shaped profile for the optical design of a camera lens. To obtain a powerful tool for representing a quasi-aspheric surface (QAS) to resemble the designed form surface, we linearly combine the pedal/cosine function with a base conic section. The detailed parameterization process of representation is discussed in this paper. Subsequently, an existing starting point that has similar specifications to that of the design requirements is selected. During the optimization process, a least-squares fitting algorithm is implemented to obtain the optimal coefficient values of the proposed QAS representation, and then the parameters (radii, air thickness, lens thickness, coefficients, materials, etc.) of the optical system are set to optimize the optical performance, gradually aiming to minimize the predefined merit function. We demonstrate the applicability of the proposed geometric modeling schemes via two design examples. In comparison to a conventional aspheric camera lens of the same specifications, the optical performance with respect to field of view and distortion has been improved due to higher degrees of design freedom. We believe that the proposed technology of geometric modeling schemes promises to improve optical performance due to these higher degrees of freedom and appears to be applicable to many different camera lenses.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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