Compact angle-resolved optical spectrum analyzer using a programmable microcontroller approach
Bibliographic record
Abstract
We describe the characterization of a highly sensitive and adaptable angle-resolved optical spectrum analyzer constructed using off-the-shelf components. The flexible nature of programmable microcontrollers is exploited by this device, resulting in a diagnostic tool that can determine the mode structure from a variety of lasers, and monitor laser beam profiles in real time. A readily available CMOS image sensor provides sensitive detection of a Fabry?Perot interference pattern, and outputs a digital signal suitable for processing by these microcontrollers. In place of an oscilloscope, a considerably less expensive component-level LCD is used which is addressed by a microcontroller. Using a solid etalon with a free spectral range of 210?GHz, we demonstrate the ability of the device to determine the mode structure of an external cavity diode laser in real time. We show this device to be competitive with a commercial optical spectrum analyzer, in terms of both dynamic range and sensitivity. The low incident laser power required by this system (0.75??W) can typically be obtained from a back reflection from an optic, and this compact, low-cost device allows for the provision of a dedicated spectrum analyzer for each laser system of interest.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".