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Record W2007483150 · doi:10.1364/ol.37.001355

Single-shot photonic time-intensity integration based on a time-spectrum convolution system

2012· article· en· W2007483150 on OpenAlexaff
Antonio Malacarne, Reza Ashrafi, Ming Li, Sophie LaRochelle, Jianping Yao, José Azaña

Bibliographic record

VenueOptics Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of OttawaUniversité LavalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsOpticsWaveformTime delay and integrationPhotonicsConvolution (computer science)LaserPhysicsComputer scienceRadarTelecommunications

Abstract

fetched live from OpenAlex

Real-time and single-shot ultra-fast photonic time-intensity integration of arbitrary temporal waveforms is proposed and demonstrated. The intensity-integration concept is based on a time-spectrum convolution system, where the use of a multi-wavelength laser with a flat envelope, employed as the incoherent broadband source, enables single-shot operation. The experimental implementation is based on optical intensity modulation of the multi-wavelength laser with the input waveform, followed by linear dispersion. In particular, photonic temporal intensity integration with a processing bandwidth of 36.8 GHz over an integration time window of 1.24 ns is verified by experimentally measuring the integration of an ultra-short microwave pulse and an arbitrary microwave waveform.

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)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.018
GPT teacher head0.212
Teacher spread0.194 · 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

Citations73
Published2012
Admission routes1
Has abstractyes

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