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Record W4324325655 · doi:10.1117/12.2655454

Hemispherical retro-modulation technologies for passive free-space optical communication links

2023· article· en· W4324325655 on OpenAlexaff
Alexander C. MacGillivray, Sayra Gorgani, Ilija R. Hristovski, Matthias F. Jenne, Nikolai I. Lesack, Jonathan F. Holzman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsModulation (music)OptoelectronicsMaterials scienceOpticsIntensity modulationOptical communicationIndium tin oxideLayer (electronics)PhysicsPhase modulationNanotechnologyAcoustics

Abstract

fetched live from OpenAlex

In this work, we introduce the concept of a hemispherical retro-modulator for the realization of passive free-space optical communication links. The hemispherical retro-modulator is implemented with a high-refractive-index glass (S-LAH79) hemisphere on a semi-insulating-InP (SI-InP) layer, whose thickness dictates the effectiveness of both retroreflection and modulation. A voltage is applied across transparent indium tin oxide (ITO) and gold (Au) films on either side of the SIInP layer to bring about the desired modulation. The overall device is designed to enable low divergence on the retroreflected beam, as defined by a small divergence angle, and deep modulation on the retroreflected beam, as a result of electroabsorption in the SI-InP layer. To this end, the device is analysed with a ray-based model for retroflection and a unified Franz-Keldysh/Einstein model for modulation in the SI-InP layer. The theoretical results show strong agreement with the experimental results from our prototype. Moreover, the results show effective retroflection and deep modulation—with an applied electric field of 2.167 kV/cm yielding modulation depths of 13%, 34%, and 50% for our 980-nm photons and SI-InP layer thicknesses of 200, 600, and 1,000 μm, respectively. From this, we deem the SI-InP layer thickness of 600 μm to be optimal given its combined capabilities for retroflection and modulation. Ultimately, the introduced hemispherical retro-modulator is shown to be an effective element for future realizations of passive freespace optical communication links.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.800
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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 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
Published2023
Admission routes1
Has abstractyes

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