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Record W4412353436 · doi:10.1109/jlt.2025.3588315

A WDM Capable SiP Polarization Compensator That Isolates the Carrier Laser

2025· article· en· W4412353436 on OpenAlexaff
Aleksandar Nikic, Weijia Li, Charles St-Arnault, Santiago Bernal, Benton Qiu, Essam Berikaa, Luhua Xu, Kaibo Zhang, Yixiang Hu, Jinsong Zhang, Zixian Wei, Max Zhang, Ian Plant, Alessandra Bigongiari, Fabio Cavaliere, A. D’Errico, Luca Giorgi, Stéphane Lessard, R. Sabella, Stefano Stracca, David V. Plant

Bibliographic record

VenueJournal of Lightwave Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsVanier CollegeCMC Microsystems (Canada)Collège Jean-de-BrébeufMcGill University
Fundersnot available
KeywordsWavelength-division multiplexingLaserOptoelectronicsOpticsOptical communicationPolarization (electrochemistry)Materials scienceOptical filterSemiconductor laser theoryPolarization mode dispersionOptical fiberPhysicsChemistryWavelength

Abstract

fetched live from OpenAlex

We demonstrate a SiP O-band transmitter, autonomously compensating for any injected laser state of polarization (SOP), achieving net 105 and 154 Gbps PAM4 and PAM8 transmission below the Hard-Decision and Soft-Decision FEC thresholds, respectively, with the carrier laser remotely connected to the transmitter over 1 km of single-mode fiber. To enable autonomy, a feedback gradient descent algorithm is implemented, with the starting point determined by the polarimeter, to mitigate the polarization-dependent loss on the device. Additionally, the wavelength dependence and performance of the transmitter are experimentally determined to increase the effective net rate. An emulated WDM transmission was then performed at the 1304.58 nm and 1309.14 nm wavelengths, achieving net 224 and 307 Gbps OOK and PAM4 performance, below the Hard-Decision and Soft-Decision forward error correction thresholds, respectively.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.305

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 head0.007
GPT teacher head0.211
Teacher spread0.205 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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