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Record W3195797017 · doi:10.1002/adom.202100803

Fiber‐Integrated Phase Change Metasurfaces with Switchable Group Delay Dispersion

2021· article· en· W3195797017 on OpenAlexafffund
Tiago Martins, Yihao Cui, Behrad Gholipour, Jun‐Yu Ou, Orlando Frazão, Kevin F. MacDonald

Bibliographic record

VenueAdvanced Optical Materials · 2021
Typearticle
Languageen
FieldComputer Science
TopicNeural Networks and Reservoir Computing
Canadian institutionsUniversity of Alberta
FundersEngineering and Physical Sciences Research CouncilAlberta InnovatesFundação para a Ciência e a TecnologiaMinistry of Education - Singapore
KeywordsMaterials scienceOptoelectronicsGroup delay and phase delayChalcogenideNeuromorphic engineeringDispersion (optics)PhotonicsOpticsComputer scienceTelecommunicationsArtificial neural networkPhysics

Abstract

fetched live from OpenAlex

Abstract Demonstration of a fiber‐integrated non‐volatile reconfigurable metasurface providing high‐contrast group delay dispersion switching functionality is reported, which may be engineered to operate at wavelengths across the near‐infrared (telecoms) band. Light‐induced amorphous‐crystalline phase switching in a chalcogenide (germanium antimony telluride) metasurface, only a fraction of a wavelength thick, fabricated on the end‐facet of a single‐mode optical fiber, enables intensity and phase modulation of the guided wave at metasurface designated bands. Such devices present a range of opportunities in fiberized remotely programmable phase/intensity multiplexing and dynamic dispersion compensation for emerging telecommunications and data storage/processing applications, including in photonic neural network and neuromorphic computing architectures.

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 score0.000
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)0.0000.000

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 head0.021
GPT teacher head0.263
Teacher spread0.243 · 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

Citations18
Published2021
Admission routes2
Has abstractyes

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