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Record W3098327936

Improvement of two-way continuous-variable quantum key distribution using optical amplifiers

2016· article· en· W3098327936 on OpenAlexaff
Yichen Zhang, Zhengyu Li, Christian Weedbrook, Wanyi Gu, Maozhu Sun, Xiang Peng, Hong Guo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsPQ Corporation (Canada)University of Toronto
Fundersnot available
KeywordsQuantum key distributionDetectorComputer scienceAmplifierKey (lock)Noise (video)Variable (mathematics)Electronic engineeringContinuous variableMode (computer interface)Optical amplifierQuantumTelecommunicationsPhysicsOpticsMathematicsComputer securityEngineeringQuantum mechanicsMathematical optimizationBandwidth (computing)
DOInot available

Abstract

fetched live from OpenAlex

Abstract. The imperfections of a receiver’s detector affect the performance of two-way continuous-variable quantum key distribution protocols and are difficult to adjust in practical situations. We propose a method to improve the performance of two-way continuous-variable quantum key distribution by adding a parameter-adjustable optical amplifier at the receiver. A security analysis is derived against a two-mode collective entangling cloner attack. Our simulations show that the proposed method can improve the performance of protocols as long as the inherent noise of the amplifier is lower than a critical value, defined as the tolerable amplifier noise. Furthermore, the optimal performance can approach the scenario where a perfect detector is used.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

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