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Record W2071217814 · doi:10.1109/jlt.2007.901342

Analysis of PMD-Induced System Penalty Using Pulse Spreading

2007· article· en· W2071217814 on OpenAlexaff
Na Young Kim, John C. Cartledge

Bibliographic record

VenueJournal of Lightwave Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsQueen's University
Fundersnot available
KeywordsPolarization mode dispersionBandwidth (computing)Computer scienceOpticsPhysicsElectronic engineeringTelecommunicationsDispersion (optics)Engineering

Abstract

fetched live from OpenAlex

This paper presents a technique that predicts the polarization-mode-dispersion (PMD)-induced system penalty based on rms pulse spreading. Amplifled-spontaneous-emission noise limited and thermal noise limited cases are investigated for the nonreturn to zero (NRZ) and return to zero modulation formats. A comparison is made with similar approaches that use three alternative metrics: the string length up to first order, the conventional string length, and the weighted string length. It is shown that the technique based on pulse spreading extends the applicable range of the system-penalty prediction in terms of both the mean link PMD and the modulated-signal bandwidth.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.256
Teacher spread0.240 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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