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Record W3136098820 · doi:10.1063/5.0031230

Perspectives on advances in high-capacity, free-space communications using multiplexing of orbital-angular-momentum beams

2021· article· en· W3136098820 on OpenAlexaff
Alan E. Willner, Zhe Zhao, Cong Liu, Runzhou Zhang, Haoqian Song, Kai Pang, Karapet Manukyan, Hao Song, Xinzhou Su, Guodong Xie, Yongxiong Ren, Yan Yan, Moshe Tur, Andreas F. Molisch, Robert W. Boyd, Huibin Zhou, Nanzhe Hu, Amir Minoofar, Hao Huang

Bibliographic record

VenueAPL Photonics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsUniversity of Ottawa
FundersDefense Security Cooperation AgencyAir Force Research LaboratoryNippon Telegraph and Telephone
KeywordsOrbital angular momentum multiplexingMultiplexingAngular momentumPhysicsOptical communicationCrosstalkFree-space optical communicationCommunications systemFree spaceChannel capacityTelecommunicationsOpticsOrbital angular momentum of lightComputer scienceElectronic engineeringChannel (broadcasting)EngineeringTotal angular momentum quantum numberQuantum mechanics

Abstract

fetched live from OpenAlex

Beams carrying orbital-angular-momentum (OAM) have gained much interest due to their unique amplitude and phase structures. In terms of communication systems, each of the multiple independent data-carrying beams can have a different OAM value and be orthogonal to all other beams. This paper will describe the use of multiplexing and the simultaneous transmission of multiple OAM beams for enhancing the capacity of communication systems. We will highlight the key advances and technical challenges in the areas of (a) free-space and fiber communication links, (b) mitigation of modal coupling and channel crosstalk effects, (c) classical and quantum systems, and (d) optical and radio frequency beam multiplexing.

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)0.003
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.008
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0110.002

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 head0.019
GPT teacher head0.272
Teacher spread0.252 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations126
Published2021
Admission routes1
Has abstractyes

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