Design and fabrication of a tapered fiber bundle for a pump combiner with a uniform splicing region
Bibliographic record
Abstract
A process of fabricating tapered fiber bundle (TFB) consisting of a set of input pump fibers, stacked inside a low-OH silica capillary, has been optimized to combine multiple multimode pump powers into different output fibers having cladding diameters of 400, 250, and 125 µm. Instead of individual input and output fiber processing, here pump combiner fabrication is based on the processing of the TFB to match its diameter with the output fiber to eliminate any perturbation in light guidance. Fabrication of the TFB includes multiple fusing steps and tapering with brightness conservation, followed by reduction of the outer silica layer through chemical etching to obtain the desired outer diameter. To reduce pump power leakage, the optimum fluorine cladding layer thickness outside the pump fiber cores and outer silica layer thickness have been estimated through numerical simulations using a finite element solver. The influence of fabrication parameters such as interstitial gaps between the input pump fibers, taper ratio, fluorine cladding, outer silica layer thickness, and non-uniformity of splicing region has been characterized in terms of transmission efficiency per port, as well as cumulative power handling along with the operating temperature at maximum power.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".