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Loss Asymmetries in Quantum Traveling-Wave Parametric Amplifiers

2019· article· en· W2891693512 on OpenAlexafffund
Martin Houde, Luke C. G. Govia, Aashish A. Clerk

Bibliographic record

VenuePhysical Review Applied · 2019
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsMcGill University
FundersArmy Research OfficeNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsLossy compressionAmplifierParametric statisticsQuantumLimit (mathematics)Quantum information scienceSIGNAL (programming language)Quantum limitQuantum mechanicsComputer scienceQuantum entanglementOptoelectronicsMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

Traveling-wave parametric amplifiers (TWPAs) are widely used in quantum information science for amplification and measurement at the quantum limit, but their development is held back by a lack of understanding of their susceptibility to internal loss. The authors use both lumped-element and distributed-loss models to describe the output of a lossy TWPA, and identify a surprising, strong dependence on the symmetry of loss between signal and idler modes. This insight will have immediate impact on the design of TWPAs as both quantum-limited amplifiers and sources of squeezed radiation.

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)0.004
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.265
Teacher spread0.248 · 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

Citations25
Published2019
Admission routes2
Has abstractyes

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