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Record W2065695146 · doi:10.1109/jlt.2012.2235820

Experimental Investigation of the Optical Injection Locking Dynamics in Single-Section Quantum-Dash Fabry-Pérot Laser Diode for Packet-Based Clock Recovery Applications

2012· article· en· W2065695146 on OpenAlexaff
Ramón Maldonado-Basilio, Josué Parra-Cetina, Sylwester Latkowski, Nicola Calabretta, Pascal Landais

Bibliographic record

VenueJournal of Lightwave Technology · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOscilloscopeLaser diodeOpticsMode-lockingLaserPhysicsDiodeSemiconductor laser theoryInjection lockingBiasingSynchronization (alternating current)OptoelectronicsMaterials scienceVoltageComputer scienceTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

An experimental study of the dynamics of a quantum-dash Fabry-Pérot passively mode-locked laser diode is presented. Firstly, the switching on and off characteristic times of the mode-locking mechanism with pulsed biasing current are assessed. Secondly, the locking and unlocking characteristic times to the injection of a 10-Gbps pseudo-random binary sequence of nonreturn-to-zero data are determined. The dynamics is analysed through the instantaneous frequency of the ~40 GHz beat-tone signal measured at the output of the laser under investigation, which after a frequency down-conversion stage, is recorded by a real-time oscilloscope. Experimental results indicate that a time of 5 ns characterizes the establishment of the passive mode-locking mechanism for a pulsed biasing current. A time of 20 ns has been measured for the synchronization of the quantum-dash laser diode to the injected 10 Gbps data sequence. In addition, the mode-locked laser diode de-synchronizes and switches to the free-running condition in also 20 ns after a holding time of ~ 100 ns.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.480

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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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 designBench or experimental
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

Citations11
Published2012
Admission routes1
Has abstractyes

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