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Record W2756468477 · doi:10.1364/optica.4.001126

Superresolution far-field imaging of complex objects using reduced superoscillating ripples

2017· article· en· W2756468477 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptica · 2017
Typearticle
Languageen
FieldEngineering
TopicNear-Field Optical Microscopy
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWaveformSidebandPoint spread functionOpticsSuperresolutionComputer scienceImage resolutionFourier transformField of viewNear and far fieldPhysicsArtificial intelligenceTelecommunicationsImage (mathematics)Radio frequencyRadar

Abstract

fetched live from OpenAlex

Superoscillation is a phenomenon where a wave oscillates locally faster than its highest Fourier component. While previous reports have shown attractive possibilities for a superoscillation-based far-field superresolution imaging device, it has also been recognized that a high-energy “sideband” region coexists with the superresolution features. This sideband causes strong restrictions and necessitates trade-offs in achievable resolution, viewing area, and sensitivity of the imaging device. In this work, we introduce a new class of superoscillation waveform—which consists of a diffraction-limited hotspot surrounded by low-energy superoscillating sidelobe ripples. This waveform alleviates the aforementioned trade-off and enables superresolution imaging for complex objects over a larger viewing area while maintaining a practical level of sensitivity. Using this waveform as the point spread function of an imaging system, we demonstrate the successful superresolution of Latin letters without performing scanning and/or post-processing operations.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.291
Teacher spread0.257 · 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