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Record W2093600026 · doi:10.1109/lpt.2013.2286151

Digital Back Propagation With Optimal Step Size for Polarization Multiplexed Transmission

2013· article· en· W2093600026 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

VenueIEEE Photonics Technology Letters · 2013
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNonlinear systemMultiplexingTransmission (telecommunications)Polarization (electrochemistry)Computer scienceMathematicsTopology (electrical circuits)Mathematical optimizationPhysicsTelecommunications

Abstract

fetched live from OpenAlex

A digital back propagation (DBP) scheme with optimal step size for polarization division multiplexed transmission system is proposed. For a fixed number of steps in DBP, the optimum step size is calculated by minimizing the mismatch between the area under the exponentially increasing nonlinearity profile and its stepwise approximation. In simulations, the vector nonlinear Schödinger equation or Manakov equations are used for forward propagation and Manakov equations are used for backward propagation. The simulation results show that the proposed scheme using the optimum step size outperforms that using the uniform step size at the same computational cost.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.939

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 head0.004
GPT teacher head0.179
Teacher spread0.175 · 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