MétaCan
Menu
Back to cohort
Record W3139034340 · doi:10.1117/1.oe.60.5.051213

Methods to achieve fast, accurate, and mechanically robust optical breadboard alignment

2021· article· en· W3139034340 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOptical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Measurement and Metrology Techniques
Canadian institutionsInstitut National d'Optique
Fundersnot available
KeywordsBreadboardComputer scienceRobustness (evolution)Lens (geology)Optical engineeringOpticsAcousticsElectronic engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.276
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it