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Record W2116572940 · doi:10.1109/jlt.2002.806768

Tunable dispersion compensation at 40-Gb/s using a multicavity etalon all-pass filter with NRZ, RZ, and CS-RZ modulation

2002· article· en· W2116572940 on OpenAlexaff
L.M. Lunardi, David Moss, S. Chandrasekhar, L. L. Buhl, Michael R. E. Lamont, Sheldon Mclaughlin, G. Randall, Paul Colbourne, Shiva Kiran, Charles A. Hulse

Bibliographic record

VenueJournal of Lightwave Technology · 2002
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsJDSU (Canada)
Fundersnot available
KeywordsFabry–Pérot interferometerOpticsChannel spacingBandwidth (computing)RippleDispersion (optics)PhysicsModulation (music)SIGNAL (programming language)Optical filterWavelength-division multiplexingCompensation (psychology)Band-pass filterMaterials scienceTelecommunicationsWavelengthAcousticsEngineeringComputer science

Abstract

fetched live from OpenAlex

We present a multichannel tunable dispersion compensator (TDC) based on multicavity all-pass etalons that is capable of operation at 40 Gb/s. The device has a tuning range of +200/-220 ps/nm with a group delay ripple < /spl plusmn/5 ps over a channel bandwidth of 80 GHz, an overall loss of < 5.2 dB, very low insertion loss ripple, and can operate on any channel on a 200-GHz grid over the C-band. In addition, we present system performance results at 40 Gb/s using NRZ, RZ, and CS-RZ modulation, compensating up to 45 km of nonzero dispersion shifted fiber (NZDSF). Our results show that this device introduces very little excess system penalty with signal frequency drifts of up to 20 GHz when operated near the center of its tuning range. For single channel experiments with fiber, the system penalty increase versus signal detuning is more significant, but can be reduced by dynamically optimizing the device dispersion during detuning. Finally, we demonstrate simultaneous compensation of 4 channels across the C-band over 25 km of NZDSF.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.213
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), 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

Citations113
Published2002
Admission routes1
Has abstractyes

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