Inner-cladding pump reflector based on chirped volume Bragg gratings
Bibliographic record
Abstract
The cladding-pumping scheme has made the power scalability of rare-earth-doped fiber lasers up to record levels possible by distributing the pump absorption along much longer fiber lengths. However, in addition to increasing the fiber cost and the cavity losses, a longer cavity length leads to enhanced detrimental nonlinear effects such as stimulated Raman scattering. As a way to reduce the required length of such lasers, we propose here an all-fiber laser architecture that makes use of a femtosecond-written chirped inner-cladding Bragg grating (ICBG) as a residual pump reflector. We report a 73% reflectivity of the pump power propagating in the highly multimode 125 μm-diameter inner cladding of the fiber made out of pure silica. This component was inscribed by using 400 nm femtosecond pulses and the phase-mask technique. Such a reflectivity was reached by optimizing the chirp of the grating and by inserting the fiber inside a hollow capillary with an outside diameter of 1 mm during the inscription. The latter reduces greatly the impact of the fiber’s curvature on the refraction of the writing beam. A larger writing area and consequently a stronger reflectivity could therefore be reached. The presence of this component at the output of a 21 m long erbium-doped silica fiber laser operating at 1.6 μm increased its slope efficiency from 20.5 to 25.1 % with respect to the injected pump power and increased its output from 22.8 to 29 W at 115 W of pump power.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".