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Record W2191079212 · doi:10.1109/jphot.2015.2503923

Temporal Imaging of Incoherent-Light Intensity Waveforms Based on a Gated Time-Lens System

2015· article· en· W2191079212 on OpenAlexafffund
Bo Li, José Azaña

Bibliographic record

VenueIEEE photonics journal · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsOpticsWaveformLens (geology)Bandwidth (computing)Temporal resolutionPinhole (optics)Light intensityComputer scienceLight fieldPhysicsTelecommunications

Abstract

fetched live from OpenAlex

We experimentally demonstrate temporal imaging of incoherent-light intensity waveforms using a combination of a temporal gating process and a time lens. This design allows one to set the system temporal field of view and resolution in an independent fashion, thus overcoming the intrinsic time-bandwidth product tradeoff of previous incoherent-light schemes based on the temporal pinhole camera concept. In a proof-of-concept experiment, we report incoherent-light temporal compression of intensity waveforms by a factor of 2.86, with a time-bandwidth product exceeding 300, i.e., resolution of ~26 ps (approximately fourfold improvement over the corresponding pinhole-only design) along a temporal field of view of ~8 ns, using a basic linear-optics setup.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.021
GPT teacher head0.235
Teacher spread0.215 · 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 designBench or experimental
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

Citations1
Published2015
Admission routes2
Has abstractyes

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