MétaCan
Menu
Back to cohort
Record W2025131697 · doi:10.1142/s0217984907013122

SIMPLIFIED MODELING OF STEADY-STATE AND TRANSIENT BRILLOUIN GAIN IN MAGNETOACTIVE NON-CENTROSYMMETRIC SEMICONDUCTORS

2007· article· en· W2025131697 on OpenAlexfundno aff
Manjeet Singh, P. Aghamkar, P. K. Sen

Bibliographic record

VenueModern Physics Letters B · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsnot available
FundersCouncil of Scientific and Industrial Research, IndiaMcMaster University
KeywordsBrillouin scatteringSemiconductorTransient (computer programming)ElectrostrictionBrillouin zonePhysicsOpticsPiezoelectricityMaterials scienceSteady state (chemistry)Condensed matter physicsLaserOptoelectronicsAcoustics

Abstract

fetched live from OpenAlex

With the aid of a hydrodynamic model of semiconductor-plasmas, a detailed analytical investigation is made to study both the steady-state and the transient Brillouin gain in magnetized non-centrosymmetric III-V semiconductors arising from the nonlinear interaction of an intense pump beam with the internally-generated acoustic wave, due to piezoelectric and electrostrictive properties of the crystal. Using the fact that the origin of coherent Brillouin scattering (CBS) lies in the third-order (Brillouin) susceptibility of the medium, we obtained an expression of the gain coefficient of backward Stokes mode in steady-state and transient regimes and studied the dependence of piezoelectricity, magnetic field and pump pulse duration on its growth rate. The threshold-pump intensity and optimum pulse duration for the onset of transient CBS are estimated. The piezoelectricity and externally-applied magnetic field substantially enhances the transient CBS gain coefficient in III-V semiconductors which can be of great use in the compression of scattered pulses.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueModern Physics Letters BSame topicAdvanced Fiber Laser TechnologiesFrench-language works237,207