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Simple Multiuser Twin-Field Quantum Key Distribution Network

2022· article· en· W4206925405 on OpenAlexafffund
Xiaoqing Zhong, Wenyuan Wang, Reem Mandil, Hoi‐Kwong Lo, Li Qian

Bibliographic record

VenuePhysical Review Applied · 2022
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMitacsUniversity of Hong KongRoyal Bank of Canada
KeywordsQuantum key distributionComputer scienceQuantum networkEncryptionKey (lock)Alice and BobComputer networkSimple (philosophy)Stability (learning theory)Field (mathematics)Telecommunications networkQuantumComputer securityPhysicsAlice (programming language)Quantum informationQuantum mechanics

Abstract

fetched live from OpenAlex

Meet Alice, Bob, and David. Establishing secure encryption keys between any two of these users is important for a long-range communication network, but with dubious Charlie also around, it becomes tricky. Twin-field quantum key distribution (TFQKD), while promising for this application, has been limited so far to two users, because of its requirement for phase stability of optical signals. In this work, the authors demonstrate a TFQKD network by connecting three users in a Sagnac fiber ring, a configuration with inherent phase stability. This experiment suggests that the Sagnac TFQKD system is an effective, practical approach to implementing a long-range secure communication network.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.267
Teacher spread0.255 · 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

Citations32
Published2022
Admission routes2
Has abstractyes

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