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Record W3091809055 · doi:10.1364/osac.404060

CO-OFDM for bandwidth-reconfigurable optical interconnects using gain-switched comb

2020· article· en· W3091809055 on OpenAlexfundno aff
Lakshmi Narayanan Venkatasubramani, Yi Lin, Colm Browning, Anirudh Vijay, Frank Smyth, R. David Koilpillai, Deepa Venkitesh, Liam P. Barry

Bibliographic record

VenueOSA Continuum · 2020
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsnot available
FundersSoutheastern Ontario Academic Medical OrganizationMinistry of Education, IndiaMinistry of Electronics and Information technologyScience Foundation Ireland
KeywordsQAMOrthogonal frequency-division multiplexingBandwidth (computing)Quadrature amplitude modulationElectronic engineeringLaser linewidthComputer scienceOptoelectronicsMaterials scienceBit error ratePhysicsTelecommunicationsOpticsEngineeringLaserDecoding methodsChannel (broadcasting)

Abstract

fetched live from OpenAlex

We experimentally demonstrate superchannel transmission using CO-OFDM with higher cardinality QAM corresponding to total data rates up to 760 Gbps over 25 km fiber using optical carriers generated from an externally injection locked gain-switched comb source with linewidth ≈19 kHz. Bandwidth re-configurability is demonstrated by operating the comb with different line spacing (20 GHz, 11 GHz) for the choice of (16-/32-/64-) QAM considered and we show the BER performance is within the SD-FEC limit. The system proposed can be used in any short reach application including DCIs and in access networks.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.032
GPT teacher head0.247
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2020
Admission routes1
Has abstractyes

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