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Polarization Agnostic Frequency-Comb WDM Transmission Enabling Net 800 Gbps OOK and 1.6 Tbps PAM4

2025· article· W4417053458 on OpenAlexaff
Aleksandar Nikic, Weijia Li, Santiago Bernal, Charles St-Arnault, Benton Qiu, Essam Berikaa, Kaibo Zhang, Alessandra Bigongiari, Fabio Cavaliere, A. D’Errico, Luca Giorgi, Stéphane Lessard, R. Sabella, Stefano Stracca, David V. Plant

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsTransceiverWavelength-division multiplexingPolarization (electrochemistry)Transmission (telecommunications)LaserOptical communicationPhotonicsEncoder

Abstract

fetched live from OpenAlex

Current and future radio access networks (RAN) require the placement of intensity modulation/direct detection (IM/DD) transceivers near the antenna atop outdoor radio tower masts. Hence, the transceiver is subject to high temperatures (85°C - 100°C), and the ambient outdoor environment, which can impact the performance of the carrier laser. Thus, to preserve the performance of the carrier laser, it is desirable to remotely operate the laser from the transceiver in RAN applications, at distances up to 1 km. However, due to the necessity of single-mode fiber (SMF) in RAN[3] , the carrier laser’s state of polarization (SOP) can fluctuate from the linear transverse electric state, inducing polarization-dependent loss (PDL) in typical silicon photonic (SiP) Mach-Zehnder modulators (MZMs).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.244
Teacher spread0.234 · 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.

Study designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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