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Record W4393790407 · doi:10.5281/zenodo.8377806

A Random Optical Parametric Oscillator

2023· dataset· en· W4393790407 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

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typedataset
Languageen
FieldPhysics and Astronomy
TopicOptical and Acousto-Optic Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOptical parametric oscillatorParametric oscillatorParametric statisticsOptical parametric amplifierPhysicsStatistical physicsMathematicsComputer scienceOpticsStatisticsOptical amplifierLaser

Abstract

fetched live from OpenAlex

Synchronously pumped optical parametric oscillators (OPOs) provide ultra-fast light pulses at tuneable wavelengths. Their primary drawback is the need for precise cavity control (temperature and length), with flexibility issues such as fixed repetition rates and marginally tuneable pulse widths. Targeting a simpler and versatile OPO, we explore the inherent disorder of the refractive index in single-mode fibres realising the first random OPO -- the parametric analogous of random lasers. This novel approach uses modulation instability (\(\chi^{(3)}\) non-linearity) for parametric amplification and Rayleigh scattering for feedback. The pulsed system exhibits high inter-pulse coherence (coherence time of $\sim$0.4~ms), offering adjustable repetition rates (16.6 - 2000 kHz) and pulse widths (0.69 - 47.9 ns). Moreover, it operates continuously without temperature control loops, resulting in a robust and flexible device, which would find direct application in LiDAR technology. This work sets the stage for future random OPOs using different parametric amplification mechanisms.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.081

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 head0.026
GPT teacher head0.250
Teacher spread0.224 · 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