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Record W3015915125 · doi:10.1063/5.0003290

Large signal analysis of multiple quantum well transistor laser: Investigation of imbalanced carrier and photon density distribution

2020· article· en· W3015915125 on OpenAlexaff
Iman Taghavi, Behzad Namvar, Mohammad Hosseini, Hassan Kaatuzian

Bibliographic record

VenueJournal of Applied Physics · 2020
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOptoelectronicsQuantum wellLaser linewidthMaterials scienceModulation (music)TransistorHeterojunctionSIGNAL (programming language)Quantum well laserBandwidth (computing)Rate equationLaserCarrier lifetimePhotonCharge-carrier densitySemiconductor laser theoryPhysicsQuantum dot laserOpticsComputer scienceTelecommunicationsVoltageSemiconductor

Abstract

fetched live from OpenAlex

In this paper, we present a large-signal and switching analysis for the Heterojunction Bipolar Transistor Laser (HBTL) to reveal its optical and electrical behavior under high current injection conditions. Utilizing appropriate models for carrier transport, nonlinear optical gain, and optical confinement factor, we have simulated the large-signal response of the HBTL in relatively low and high modulation frequencies. Our results predict that for multiple quantum well (MQW) structures at low frequencies, there should not be a difference in either the carrier density or the photon density. However, the carrier concentration can be differently distributed between subsequent wells in the case of a high speed yet large-signal input. This leads to increased linewidth instead as it depends on ΔNqw. We show the effect of different structural parameters on the switching behavior by performing a switching analysis of the single quantum well and MQW structures using computationally efficient numerical methods. A set of coupled rate equations are solved to investigate the large-signal and switching behavior of MQW-HBTL. Finally, to have a comprehensive judgment about this optoelectronic device, we introduce a relative performance factor taking into account all the optoelectronic characteristics such as the output power, ac current gain, modulation bandwidth, and base threshold current, as well as turn-on time in order to design a suitable TL for optoelectronic integrated circuits.

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 score0.307
Threshold uncertainty score0.340

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 head0.010
GPT teacher head0.195
Teacher spread0.185 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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