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Record W4404862542 · doi:10.1088/1361-6501/ad9510

Intensity-varied interferometric autocorrelations for characterisations of optical nonlinearity

2024· article· en· W4404862542 on OpenAlexafffund
Matthias F. Jenne, Jonathan F. Holzman

Bibliographic record

VenueMeasurement Science and Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of British Columbia, Okanagan Campus
FundersWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsInterferometryIntensity (physics)OpticsNonlinear systemMaterials scienceNonlinear opticalPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract In this work, we present the theoretical framework and experimental setup for intensity-varied interferometric autocorrelations. This is done to resolve the manifestations of multiphoton absorption and saturation, while avoiding the complexities of analogous techniques. Our system is demonstrated with the standardised wavelength of 1550 nm, at the centre of the optical communication band, and a conventional silicon photodiode, whose bandstructure allows for multiple pathways for multiphoton absorption. With this system, we see the silicon exhibit negligible one-photon absorption, strong two-photon absorption for intensities up to 160 GW cm −2 , strong three-photon absorption for intensities between 160 and 350 GW cm −2 , and saturation for intensities above 350 GW cm −2 . Ultimately, such results suggest that the proposed theoretical framework and experimental setup are effective tools for nonlinear characterisations of multiphoton absorption and saturation.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.259
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

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 designSimulation or modeling
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
Published2024
Admission routes2
Has abstractyes

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