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Record W4280603215 · doi:10.1515/joc-2021-0120

Raman pumps power distribution optimization for maximum overall gain and flatness of a hybrid SOA/EDFA/Raman optical amplifier

2022· article· en· W4280603215 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Optical Communications · 2022
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsOptiwave Systems (Canada)
Fundersnot available
KeywordsFlatness (cosmology)Optical amplifierOpticsWavelength-division multiplexingWavelengthNoise figureRaman amplificationMaterials scienceAmplifierOptoelectronicsAmplified spontaneous emissionLaserPhysics

Abstract

fetched live from OpenAlex

Abstract A hybrid optical amplifier (HOA) is designed and optimized for the transmission of 40 dense wavelength division multiplexed system (DWDM) channels modulated at 10 Gbps having 25 GHz spacing at the edge of the L and U wavelength bands over more than 250 km. Multi-parameter optimization process is used to achieve the highest gain and best gain flatness. Different power combinations distributed among four lasers of a total forward pumping power (1270 mW) and total backward pumping power of either 730 mW or 850 mW are investigated for their effect on the hybrid amplifier gain and flatness. The best power distribution among the pumps provides about 31 dB overall gain with a flatness about 0.8 dB and noise figure ∼5.7 dB. It is found that the red-shifted pumps’ wavelengths should be used in the forward direction, while the blue-shifted pumps’ wavelengths should be used in the backward direction.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.593
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.251
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it