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Record W4414229696 · doi:10.1088/2058-9565/ae0759

Strategies for generating separable photon triplets in waveguides and ring resonators

2025· article· en· W4414229696 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

VenueQuantum Science and Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsNational Research Council CanadaPolytechnique Montréal
FundersHORIZON EUROPE Digital, Industry and SpaceNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsPhotonPhotonicsLimit (mathematics)Parametric statisticsResonatorQuantumSpontaneous parametric down-conversionOptical fiberWaveguide

Abstract

fetched live from OpenAlex

Abstract Photon triplet sources exhibit non-Gaussian features, a key property for applications in quantum computing and quantum information. However, spectral correlations can limit the performance and detection efficiency of these systems. Motivated by this observation, we present a theoretical analysis of the spectral properties of photon triplets generated through spontaneous third-order parametric down-conversion in photonic devices, and discuss strategies to quantify and minimize such correlations. We propose two approaches: dispersion engineering in waveguides and pump engineering in resonators. We apply these strategies in two realistic source designs, namely a high-index-contrast optical fiber and a silicon nitride microring resonator. Finally, we discuss detection strategies for probing non-Gaussian features of the triplet state. We find that it is feasible to achieve few-mode generation of photon triplets using state-of-the-art experimental systems, a crucial step toward practical applications of photon triplet sources in quantum technologies.

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 score0.859
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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