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Record W4417430795 · doi:10.1364/opticaq.571470

Demonstration of a reconfigurable quantum network architecture suitable for ground-to-space communication

2025· article· en· W4417430795 on OpenAlexafffund
Stephane Vinet, Duncan England, Chang‐Qing Xu, Thomas Jennewein

Bibliographic record

VenueOptica Quantum · 2025
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsSimon Fraser UniversityNational Research Council CanadaMcMaster UniversityUniversity of Waterloo
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaCanada Excellence Research Chairs, Government of CanadaCanada Foundation for InnovationOntario Research Foundation
KeywordsQuantum key distributionSatelliteQuantum entanglementMetropolitan area networkQuantum networkOverhead (engineering)MultiplexingCommunications satelliteTopology (electrical circuits)

Abstract

fetched live from OpenAlex

We experimentally demonstrate a reconfigurable quantum network architecture suitable for integrating satellite links in metropolitan quantum networks. The network architecture is designed such that once a satellite is in range, it is configured in a multipoint-to-point topology where all ground nodes establish entanglement with the satellite receiver using time multiplexing to optimize long-distance transmission. Otherwise, the satellite up-link can be rerouted to the ground nodes to form a pair-wise ground network. Leveraging both the time and frequency correlations of our photon-pair source, we demonstrate an increased coincidence-to-accidental ratio without additional resource overhead in a five-node network. To contextualize these experimental findings, we project their performance in a quantum key distribution scenario and outline a feasible route toward field deployment, using integrated photonics to enable network integration of up to 72 users.

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)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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