Temperature-Insensitive Tunable Optical Filter Based on a Microsphere-Coupled Off-Core Spliced Fiber
Bibliographic record
Abstract
A low-cost fiber-integrated temperature-insensitive tunable Fabry-Pérot filter fabricated from an off-core spliced segment of standard single mode fiber (SMF) and a commercially available barium titanate (BaTiO3) microsphere is proposed and demonstrated. The filter’s cavity extends from the cleaved face of the launching SMF to the back face of the microsphere, thus forming a hybrid (air + BaTiO3) cavity. The device is robust against temperature variations due to the null thermo-optic coefficient of air, and a self-compensating optical path effect within the microsphere enabled by diffraction optics, which is credited to its spherical structure. Indeed, the filter’s spectrum exhibits an ultra-low temperature-dependence, with experiments showing a temperature coefficient of 2 pm/°C for spectral shifts, agreeing well with theoretical calculations. Spectral contrasts higher than 35 dB were experimentally obtained, which were shown to depend on the longitudinal position of the microsphere. Such high contrasts are due to the high refractive index of the microsphere (1.9), which allows for greater reflectivity at the microsphere-air interface. Different from other off-core based filters, the one studied in this work offers wavelength tunability, which is achieved by changing the position of the microsphere either along (coarse tuning) or transversally (fine tuning) on the off-core segment. From its simplicity, low-cost, high-contrast, repeatability, temperature-independence, tunability and fiber-integration, it is expected that the proposed filter will find direct application in both research and industry.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".