MétaCan
Menu
Back to cohort
Record W4321607985 · doi:10.1109/jlt.2023.3244777

Mode-Locking and Noise Characteristics of InAs/InP Quantum Dash/Dot Lasers

2023· article· en· W4321607985 on OpenAlexaff
Guocheng Liu, Philip J. Poole, Zhenguo Lü, Jiaren Liu, Youxin Mao, Pedro Barrios

Bibliographic record

VenueJournal of Lightwave Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsLaser linewidthLaserOptoelectronicsQuantum dot laserSemiconductor laser theoryNoise (video)Relative intensity noiseMaterials sciencePhysicsOpticsComputer science

Abstract

fetched live from OpenAlex

The mode-locking and noise characteristics of InP/InAs quantum dash (QDash) and quantum dot (QDot) multi-wavelength lasers, showing identical structural design, operating at the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</i> -band, are investigated and compared to each other. The QDash lasers exhibit improved repetition frequency stability with a lower threshold current and cavity loss. On the other hand, the QDot lasers show higher quality repetition frequency tunability with higher internal quantum efficiency, as well as lower average integrated relative intensity noise (RIN) and average optical linewidth. Furthermore, we demonstrate both the QDash and QDot lasers exhibit very clean constellation diagrams at 32 GBaud 16QAM base-band signal, while the QDot lasers’ bit-error ratio (BER) performance outperforms the QDashes. This finding highlights the viability of InAs/InP QDash/QDot lasers to be used as a low-cost optical source for large-scale 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 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 score0.302
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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

Citations22
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Lightwave TechnologySame topicPhotonic and Optical DevicesFrench-language works237,207