Evidence map›Paper›PMID 40566202›Full record

ArticleEntropy (Basel, Switzerland)2025

Efficient Entanglement Swapping in Quantum Networks for Multi-User Scenarios.

Binjie He, Seng W Loke, Luke Lu, Dong Zhang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Binjie HeCollege of Computer and Data Science, Fuzhou University, Fuzhou 350108, China.ORCID 0000-0003-2373-0391
Seng W LokeSchool of Information Technology, Deakin University, Melbourne, VIC 3125, Australia.ORCID 0000-0002-5339-9305
Luke LuCisco Systems Inc., Suzhou 215123, China.ORCID 0009-0007-2062-395X
Dong ZhangFujian Province Key Laboratory of Information Security of Network System, Fuzhou University, Fuzhou 350108, China.ORCID 0000-0002-6379-0244

Funding

National Key Research and Development Program of China 2023YFB2904000National Key Research and Development Program of China 2023YFB2904005
6 · The paper itself

Abstract

Entanglement swapping is a crucial step in quantum communication, generating long-distance entanglements between quantum users for quantum network applications, such as distributed quantum computing. This study focuses on the efficiency of entanglement swapping strategies in quantum networks, particularly in multi-user concurrent quantum communication. Since multi-user concurrent quantum communication consists of multiple point-to-point quantum communications, we first analyze the challenges faced by existing entanglement swapping strategies in this scenario and then propose Parallel Segment Entanglement Swapping (PSES) to address them. PSES utilizes a tree-like model to divide the path into segments and execute entanglement swapping in parallel across them, thereby enhancing the generation rate of long-distance entanglement. Furthermore, we analyze the impact of resource contention on entanglement swapping in multi-user concurrent quantum communication and propose Multi-user PSES (M-PSES) to alleviate this negative impact. M-PSES leverages the entanglement swapping trigger signal and resource locking mechanisms to mitigate resource contention. The simulation results show that PSES performs superiorly to existing entanglement swapping strategies in point-to-point quantum communication, and M-PSES can achieve better performance than PSES in multi-user concurrent quantum communication.

Indexed as

entanglement swappingquantum communicationquantum networks

Identifiers

PMID40566202
PMCPMC12191485

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.