Analysis of Optical Diffraction Profiles Created by Phase-Modulating MEMS Micromirror Arrays
Bibliographic record
Abstract
This paper presents modeling and analysis of light diffraction and light-intensity modulation performed by an optical phased array (OPA) system based on metal-coated silicon micromirrors. The models can be used in the design process of a microelectromechanical system (MEMS)-based OPA device to predict its optical performance in terms of its field of view, response, angular resolution, and long-range transmission. Numerical results are derived using an extended model for the 1st-order diffracted light intensity modulation due to phase shift. The estimations of the optical characteristics are utilized in the designs of an OPA system capable of active phase modulation and an OPA system capable of array pitch tuning. Both designs are realized using the Multi-User MEMS Processes (PolyMUMPs) in which polysilicon is used as structural material for the MEMS-actuated mirrors. The experiments are performed to evaluate the optical performance of the prototypes. The tests show that the individually actuated micromirrors, which act as phase shifters, can transmit the most optical power along the 1st-order diffracted beam by actively changing their out-of-plane positions. In addition, the 1st-order diffracted beam with high optical intensity can be steered for distance measurement.
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.
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 | 0.000 | 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 | 0.000 |
| 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 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".