40 GHz-rate all-optical cross-modulation of core-guided near infrared light in single mode fiber by surface plasmons on gold-coated tilted fiber Bragg gratings
Bibliographic record
Abstract
All-optical control of Surface Plasmon Polaritons (SPPs) can switch light with high speed and a large signal to noise ratio. We demonstrate 25 ps-time scale switching of continuous wave light by pump pulses copropagating in the same single mode fiber at different wavelengths near 1550 nm. The switching is due to hot carriers from the SPPs in a 45 nm-thin gold coating on the fiber cladding. The SPPs are generated by pump pulses coupled from the core to cladding modes by a tilted fiber Bragg grating (TFBG). Hot carriers modify the complex permittivity of the metal coating on a time scale of the order of picoseconds and hence the cladding mode resonance wavelengths of the TFBG. A probe light signal copropagating in the same fiber can therefore be modulated by the transmission resonance shifts. With 25 ps pulses at 1540.4 nm and 1 MHz and 50 mW average power, the modulation depth of a CW probe at 1543.4 nm copropagating in the core reached 4.5% ± 1% with a pulse width broadened to 56 ps. Under these conditions, the pump power density was 0.147 GW/cm2 in the metal layer, for a conversion efficiency as high as 30% ± 7% per GW/cm2. Since many other plasmonic and nonlinear active materials can be deposited on fiber claddings, we believe that this very simple all-fiber configuration to perform all-optical switching of core-guided light in single mode fibers by plasmon-modulated resonances has strong potential applications in studies of light-matter interactions over fast and ultrafast time scales.
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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".