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Record W2013594600 · doi:10.1109/acc.2012.6315331

Oscillation analysis for a quasi-ring optical network

2012· article· en· W2013594600 on OpenAlexaff
Zheng Wang, Jyh-Woei Tsai, Yan Pan, Daniel C. Kilper, Lacra Pavel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMultiplexerControl theory (sociology)Channel (broadcasting)AmplifierOscillation (cell signaling)Topology (electrical circuits)Computer sciencePhysicsElectronic engineeringMathematicsMultiplexingTelecommunicationsEngineeringBandwidth (computing)Control (management)

Abstract

fetched live from OpenAlex

We study a two-channel quasi-ring network composed of two reconfigurable optical add-drop multiplexers (ROADMs) equipped with dynamic gain equalizers (WSS/DGEs) and two constant gain controlled optical amplifiers. We conduct an equilibrium and stability analysis on the quasi ring network because it is the simplest scenario in which optical channel power can oscillate within a loop. Due to the difference of time scale between pump control and channel power equalization, we treat the amplifiers in the loop as static nonlinear function mappings. Based on this mapping and considering transmission delay, we show that a specific type of channel flattening control by a output-average tracking WSS/DGE can cause oscillations in the quasi-ring network. Theoretical results are validated using numerical simulations.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.665
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.237
Teacher spread0.219 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2012
Admission routes1
Has abstractyes

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