Analysis of signal excited-state absorption for improving extended L-band erbium-doped fibers
Bibliographic record
Abstract
The precise characterization of signal excited-state absorption (ESA) in erbium-doped fibers (EDFs) is achieved through an ON/OFF pumping scheme, using a supercontinuum source in conjunction with a bandpass tunable filter to generate the input signal. Normalizing the ESA profile, by the value of the ESA peak, allows sample comparisons independent of their erbium concentration. This method directly assesses the impact of ESA on the net gain within the 1600-1730 nm range, providing a significant means to study how to expand the gain bandwidth toward longer wavelengths. As an illustrative application, we investigate the effect of chemical elements, such as Er, Al, and Ba, and their concentrations on ESA. We then optimize the Al content to enhance erbium solubility without inadvertently inducing detrimental ESA effects. This advancement in the ESA characterization presents substantial advantages for the pursuit of efficient extended L-band erbium-doped fiber amplifiers (EDFAs).
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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 | 0.000 | 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 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".