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Record W4414209585 · doi:10.1364/opticaq.559266

Emulation of satellite up-link quantum communication with entangled photons

2025· article· en· W4414209585 on OpenAlexaff
Thomas Jaeken, Faris Redza, Thomas Jennewein, Alessandro Fedrizzi

Bibliographic record

VenueOptica Quantum · 2025
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsSimon Fraser UniversityUniversity of Waterloo
FundersEngineering and Physical Sciences Research Council
KeywordsQuantum key distributionEmulationQuantum entanglementSatelliteCommunications satelliteQuantum networkQuantum information sciencePhotonKey (lock)

Abstract

fetched live from OpenAlex

Quantum communication rates in terrestrial quantum networks are fundamentally limited by fiber loss, even in the presence of quantum repeaters. Satellites offer a solution for long-distance communication, with the most commonly explored scenario involving prepare-and-measure protocols connecting from orbit to a trusted-node ground station via free-space down-links. In contrast, up-link scenarios allow for entanglement to be distributed between a satellite and remote end-users in terrestrial networks, eliminating any trust requirement on the ground station. Here, we demonstrate an ultra-bright source of far-non-degenerate entangled photons and perform quantum key distribution in emulated high-loss satellite scenarios. With a loss profile corresponding to that of one of the pioneering Micius up-link experiments, and a terrestrial end-user separated by 10 km of telecom fiber, we achieve secure key bit accumulation of 5.2 kbit in a single emulated overpass in the asymptotic limit. Our results confirm the viability of upcoming low-Earth orbit receiver satellite missions.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.009
GPT teacher head0.244
Teacher spread0.235 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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