MétaCan
Menu
Back to cohort
Record W2082950337 · doi:10.1364/optica.1.000281

Fast and highly resolved capture of the joint spectral density of photon pairs

2014· article· en· W2082950337 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptica · 2014
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of DelawareUniversity of Delaware Research FoundationNational Science Foundation
KeywordsPhotonJoint (building)PhysicsOpticsEngineering

Abstract

fetched live from OpenAlex

Controlling the spatial and spectral–temporal properties of photon pairs produced in artificially structured materials is fundamental to the realization of numerous photonic quantum information applications. Tailoring the joint spectral properties of photon pairs is of particular importance for applications relying on time–energy entanglement, high-visibility interference, and heralding. Yet measuring the joint spectral properties is a time-consuming task requiring coincidence counting, typically resulting in low-resolution spectra with a poor signal-to-noise ratio. In this work we capture the joint spectral correlations of photon pairs that would be produced in optical fibers with unprecedented speed, resolution, and signal-to-noise ratio, using a scheme based on stimulated four-wave mixing. We also illustrate that this technique can be used in engineering joint spectral correlations, making it a powerful tool for studying quantum states.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.135

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 head0.007
GPT teacher head0.185
Teacher spread0.178 · 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