MétaCan
Menu
Back to cohort
Record W4406792384 · doi:10.1364/oe.549697

Time-of-flight spectroscopy with ultrafast all-optical gating

2025· article· en· W4406792384 on OpenAlexafffund
Kate L. Fenwick, Guillaume Thekkadath, Philip J. Bustard, Duncan England, Frédéric Bouchard, Benjamin Sussman

Bibliographic record

VenueOptics Express · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsNational Research Council Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsUltrashort pulseSpectroscopyGatingTime-resolved spectroscopyPhysicsMaterials scienceLaser

Abstract

fetched live from OpenAlex

Spectral measurement is crucial in applications ranging from the investigation of matter and its electronic properties to the wavelength-multiplexed routing of optical signals. We propose and demonstrate a spectral measurement technique based on an all-optical approach. The signal spectrum is mapped to the time domain by dispersion in 1 km of fiber and is then optically gated by an intense ultrafast pulse in 10 cm of single-mode fiber. A portion of the signal spectrum can be recovered by sweeping the gate pulse through the stretched signal. Spectral fringes are measured down to the minimum bound for frequency-to-time mapping of 51.5 GHz. Our measurement technique expands the toolbox of ultrafast measurements from the time domain to the frequency domain.

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 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 score0.195
Threshold uncertainty score0.547

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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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 teacher head, 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueOptics ExpressSame topicAdvanced Fiber Laser TechnologiesFrench-language works237,207