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Record W4390058699 · doi:10.1038/s42005-023-01489-2

Photonic integrated processor for structured light detection and distinction

2023· article· en· W4390058699 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCommunications Physics · 2023
Typearticle
Languageen
FieldComputer Science
TopicNeural Networks and Reservoir Computing
Canadian institutionsMax Planck - University of Ottawa Centre for Extreme and Quantum Photonics
FundersHorizon 2020 Framework ProgrammeKarl-Franzens-Universität GrazChristian Doppler ForschungsgesellschaftEuropean CommissionÖsterreichische Nationalstiftung für Forschung, Technologie und Entwicklung
KeywordsPhotonicsComputer sciencePolygon meshPhotonic integrated circuitStructured lightChipPhysicsOpticsTelecommunications

Abstract

fetched live from OpenAlex

Abstract Integrated photonic devices are pivotal elements across research fields that involve light-based applications. Particularly versatile platforms are programmable photonic integrated processors, which are employed in applications like communication or photonic computing. Free-space distributions of light can be coupled to such processors, which subsequently control the coupled light on-chip within meshes of programmable optical gates. This enables access to the spatial properties of free-space light, particularly its relative phase, which is usually challenging to measure. Here, we discuss and show the detection of amplitude and phase distributions of structured higher-order light beams using a multipurpose photonic processor. This can be used to directly distinguish light’s orbital angular momentum without including additional elements interacting with the free-space light. We envision applications in a range of fields that rely on the spatial distributions of light’s properties, such as microscopy or communications.

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.

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)0.000
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 score0.958
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.032
GPT teacher head0.281
Teacher spread0.248 · 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