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Record W2078043019 · doi:10.1364/oe.16.004228

Chromatic dispersion tolerance in optimized NRZ-, RZ- and CSRZ-DPSK demodulation

2008· article· en· W2078043019 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

VenueOptics Express · 2008
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsOpticsDemodulationPolarization mode dispersionTransmitterDispersion (optics)Bandwidth (computing)Wavelength-division multiplexingOptical communicationOptical filterBit error rateComputer sciencePhysicsTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

We present the results of a comprehensive analysis optimizing the performance of DPSK systems with increased FSR and narrow optical filtering, establishing improved chromatic dispersion tolerance of NRZ-DPSK by 20%, RZ-DPSK by 71% and CSRZ-DPSK by 74% approximately. Transmitting a 40Gb/s signals on a spectrally efficient 50GHz DWDM grid still exhibit improvements of 7% for NRZ-DPSK, 37% for RZ-DPSK and 22% for CSRZ-DPSK, relative to a typical DPSK receiver. The optimized delay and optical filtering scale with the amount of chromatic dispersion. We also demonstrate the impact of limited transmitter bandwidth on optimal optical filtering and bit delay parameters.

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)0.000
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: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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