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Record W4297547870 · doi:10.3390/photonics9100695

Ultralow Noise and Timing Jitter Semiconductor Quantum-Dot Passively Mode-Locked Laser for Terabit/s Optical Networks

2022· article· en· W4297547870 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

VenuePhotonics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsOptoelectronicsTerabitOpticsLaser linewidthJitterMaterials scienceOptical amplifierQuantum dot laserSemiconductor laser theoryLaserPhysicsWavelength-division multiplexingSemiconductorWavelengthTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Diode optical frequency comb lasers are promising compact solutions to generate high-speed optical pulses for applications in high spectral efficiency wavelength division multiplexing transmission with advanced modulation formats. In this paper, an InAs/InP quantum dot (QDot) C-band single-section passively mode-locked laser (MLL) based broadband optical frequency comb source with a free spectral range of 28.4 GHz is presented. The device exhibits less than 1.5 MHz optical linewidth (phase noise) over 56 channels and 2.1 fs pulse-to-pulse timing jitter with a central wavelength of 1550 nm. Using this comb, we demonstrate an aggregate data transmission capacity of 12.5 Terabit/s over 100 km of standard single mode fiber by employing dual-polarization with 16 QAM modulation format. This investigation shows the viability for semiconductor QDot MLLs to be used as low-cost optical source in Terabit/s or higher optical 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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.889

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 integrity0.0000.001
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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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