MétaCan
Menu
Back to cohort
Record W2803844749 · doi:10.1103/physreva.98.043813

Gaussian functions are optimal for waveguided nonlinear-quantum-optical processes

2018· article· en· W2803844749 on OpenAlexafffund
Nicolás Quesada, Agata M. Brańczyk

Bibliographic record

VenuePhysical review. A/Physical review, A · 2018
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsPerimeter Institute
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBeam splitterGaussianQuantum entanglementNonlinear systemAmplitudeQuantum mechanicsGaussian beamFunction (biology)Gaussian random fieldNonlinear mediumPhysicsField (mathematics)QuantumOpticsGaussian functionMathematicsNonlinear opticsLaserPure mathematics

Abstract

fetched live from OpenAlex

Many nonlinear optical technologies require the two-mode spectral amplitude function that describes them---the joint spectral amplitude (JSA)---to be separable. We prove that the JSA factorizes only when the incident pump field and phase-matching function are Gaussian functions. We show this by mapping our problem to a known result, in continuous variable quantum information, that only squeezed states remain unentangled when combined on a beam splitter. We then conjecture that only a squeezed state minimizes entanglement when sent through a beam splitter with another prespecified ket. This implies that to maximize JSA separability when one of the (pump or nonlinear medium) functions is non-Gaussian, the other function must be Gaussian. This answers an outstanding question about optimal design of certain nonlinear processes and is of practical interest to researchers using waveguide nonlinear optics to generate and manipulate quantum light.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.024
GPT teacher head0.357
Teacher spread0.333 · 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.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations27
Published2018
Admission routes2
Has abstractyes

Explore more

Same venuePhysical review. A/Physical review, ASame topicQuantum Information and CryptographyFrench-language works237,207