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Record W1974114546 · doi:10.1364/jon.5.000943

ZL-switching matrix: an optimal scalable free-space strictly nonblocking two-dimensional optical cross connect architecture

2006· article· en· W1974114546 on OpenAlexaff
Samer S. Abdallah, John T. W. Yeow

Bibliographic record

VenueJournal of Optical Networking · 2006
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOptical switchScalabilityPower (physics)PhotonicsComputer scienceElectronic engineeringOptical powerOptical burst switchingArchitectureFunction (biology)Matrix (chemical analysis)Topology (electrical circuits)Optical performance monitoringEngineeringElectrical engineeringPhysicsOpticsWavelength-division multiplexingMaterials science

Abstract

fetched live from OpenAlex

Feauture Issue on Photonics in SwitchingMicromirrors constitute a promising technological platform for implementing optical switches. The free-space propagation of optical signals in microelectromechanical system switches exhibits an exponential decrease in signal power as a function of the distance traveled. The strong dependence of power on distance leads to a wide dynamic range of power losses in the proposed 2D mirror architecture thereby limiting their use to small-scale switches. We present a ZL-switching matrix, which is a simple 2D architecture that is capable of realizing large-scale optical switches. Performance of the ZL-switching matrix in terms of minimizing variations in power losses is discussed, and comparison with previous switching architectures is presented.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.248
Teacher spread0.240 · 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
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

Citations0
Published2006
Admission routes1
Has abstractyes

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