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Record W4322507172 · doi:10.1116/5.0133009

Waveguided sources of consistent, single-temporal-mode squeezed light: The good, the bad, and the ugly

2023· article· en· W4322507172 on OpenAlexafffund
Martin Houde, Nicolás Quesada

Bibliographic record

VenueAVS Quantum Science · 2023
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsApodizationBrightnessPhysicsMode (computer interface)State (computer science)Parametric statisticsSqueezed coherent stateOpticsQuantumQuantum mechanicsComputer scienceCoherent statesMathematicsAlgorithm

Abstract

fetched live from OpenAlex

We study theoretically how the brightness of the pumps, with fixed profiles, affects the temporal mode structure of squeezed states generated by fixed parametric waveguided sources. We find that the temporal modes of these squeezed states can be partially mismatched and thus distinguishable, which is undesirable when using these states as resources for quantum computing or heralded state generation. By studying common frequency filtering techniques used experimentally, we find that although one can regain indistinguishability, it comes at the price of potentially greatly reducing the purity of the state. We consider three different source configurations: unapodized single pass, apodized single pass, and apodized double pass. We find that the double pass configuration produces optimal results with almost perfectly indistinguishable states over varying degrees of brightness.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.249
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations22
Published2023
Admission routes2
Has abstractyes

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