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Record W4396939275 · doi:10.1088/2515-7647/ad4c34

Dynamic control of spontaneous emission using magnetized InSb higher-order-mode antennas

2024· article· en· W4396939275 on OpenAlexaff
Sina Aghili, Rasoul Alaee, Amirreza Ahmadnejad, Ehsan Mobini, Carsten Rockstuhl, Ksenia Dolgaleva

Bibliographic record

VenueJournal of Physics Photonics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMode (computer interface)Order (exchange)PhysicsControl (management)Materials scienceComputer scienceBusiness

Abstract

fetched live from OpenAlex

Abstract We exploit InSb’s magnetic-induced optical properties to design THz sub-wavelength antennas that actively tune the radiative decay rates of dipole emitters at their proximity. The proposed designs include a spherical InSb antenna and a cylindrical Si-InSb hybrid antenna demonstrating distinct behaviors. The former dramatically enhances both radiative and non-radiative decay rates in the epsilon-near-zero region due to the dominant contribution of the Zeeman-splitting electric octupole mode. The latter realizes significant radiative decay rate enhancement via magnetic octupole mode, mitigating the quenching process and accelerating the photon production rate. A deep-learning-based optimization of emitter positioning further enhances the quantum efficiency of the proposed hybrid system. These novel mechanisms are promising for tunable THz single-photon sources in integrated quantum 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 score0.002

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 head0.010
GPT teacher head0.281
Teacher spread0.270 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

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