Methods to achieve fast, accurate, and mechanically robust optical breadboard alignment
Bibliographic record
Abstract
Typical laboratory optical systems use commercially off-the-shelf components in which emphasis is oriented toward ease of assembly and a wide range of adjustability. However, these mounts often require individual alignments that, when each degree of adjustability is cumulated in a complex optical system, can be inefficient and time consuming. Furthermore, most of these optomechanical mounts lack the mechanical robustness required to maintain operational performances out of the laboratory environment. An optomechanical assembly method based on passively aligning design features is proposed to simplify breadboard level optical systems, to improve alignment accuracy and maintaining operational pointing stability. Given the recent improvements in lens passive centering techniques, it seemed worth exploring methods to reduce alignment time and improve the mechanical robustness of laboratory setups. Recent studies show that a typical optical lens centering of <1 arc min with respect to its mount can be achieved using patented auto centering and edge contact mounting technologies. To achieve similar position accuracy between multiple lenses on a portable breadboard, lens mounts should be designed and built with proper reference surfaces and a system should easily reference one mount with respect to the other. The use of reference spheres and dedicated optomechanical mounts is employed to leverage the standard threaded holes of laboratory breadboards and achieve precise lens mount positioning. A series of optomechanical mounts incorporating these techniques are therefore tested. Position accuracy and repeatability are measured mechanically with a coordinate measuring machine and optically with the active monitoring of a laser beam centroid position. Measured position accuracy at the optomechanical mount level is <50 μm with a repeatability of less than 5 μm per interface. The optomechanical mounts robustness is tested within typical storage temperature range of −46 ° C to 63°C and at vibrations levels exceeding typical shipping conditions. Measured optical pointing stability of a simple optical system after environmental testing was found to be under 25 μm. This method should be a promising solution to bridge the design technological gap between the early prototyping and the production phases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".