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Classical and Quantum Networks: Theory, Modeling and Optimization, 2nd Edition

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Quantum Information".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 373

Special Issue Editors


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Guest Editor
Center for Quantum Information Science and Tech-nology, Faculty of Engineering Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
Interests: classical and quantum information processing; quantum nonlocality; estimation theory; filtering theory; information processing; complex and multi-agent systems; natural; quantum and unconventional computation
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Guest Editor
Faculty of Engineering, Institute for Nanotechnology & Advanced Materials, and Center for Quantum Entanglement Science & Technology, Bar-Ilan University, Ramat-Gan 5290002, Israel
Interests: quantum mechanics; quantum information; quantum optics; quantum field theory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Network theory, both classical and quantum, has proved highly fruitful for analyzing a variety of problems. The formulation in terms of networks is often general and abstract, which allows it to fit into multiple different contexts. For example, the same tools from classical network science and percolation theory are applicable in the analysis of the resiliency of a complex system and, likewise, in the spread of an epidemic [1,2]. In this Special Issue, we will focus on generalizations and applications of classical networks to quantum systems, as well as on unique quantum constructions. The reported studies may relate to various areas, ranging from fundamental explorations of quantum nonlocality [3-5] to applications for quantum communications [6-9].

References:

[1] Newman, M. E. (2002). Spread of epidemic disease on networks. Physical review E, 66(1), 016128.

[2] Cohen, R., & Havlin, S. (2010). Complex networks: structure, robustness and function. Cambridge university press.

[3] Perseguers, S., Lapeyre, G. J., Cavalcanti, D., Lewenstein, M., & Acín, A. (2013). Distribution of entanglement in large-scale quantum networks. Reports on Progress in Physics, 76(9), 096001.

[4] Pozas-Kerstjens, A., Gisin, N., & Tavakoli, A. (2022). Full network nonlocality. Physical review letters, 128(1), 010403.

[5] Peled, B. Y., Te'eni, A., Cohen, E., & Carmi, A. (2021). Population dynamics of entangled species. arXiv preprint arXiv:2109.04237.

[6] Duan, L. M., & Monroe, C. (2010). Colloquium: Quantum networks with trapped ions. Reviews of Modern Physics, 82(2), 120.

[7] Kozlowski, W., & Wehner, S. (2019, September). Towards large-scale quantum networks. In Proceedings of the Sixth Annual ACM International Conference on Nanoscale Computing and Communication (pp. 1-7).

[8] Zhuang, Q., & Zhang, B. (2021). Quantum communication capacity transition of complex quantum networks. Physical Review A, 104(2), 022608.

[9] Meng, X., Gao, J., & Havlin, S. (2021). Concurrence percolation in quantum networks. Physical Review Letters, 126(17), 170501.

Dr. Avishy Carmi
Dr. Eliahu Cohen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • network dynamics
  • network topology
  • complex networks
  • percolation
  • quantum entanglement
  • quantum correlations
  • quantum interconnect
  • quantum walks
  • quantum key distribution

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Published Papers (1 paper)

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Research

58 pages, 3315 KiB  
Article
Overcoming Intensity Limits for Long-Distance Quantum Key Distribution
by Ibrahim Almosallam
Entropy 2025, 27(6), 568; https://doi.org/10.3390/e27060568 - 27 May 2025
Viewed by 269
Abstract
Quantum Key Distribution (QKD) enables the sharing of cryptographic keys secured by quantum mechanics. The BB84 protocol assumes single-photon sources, but practical systems rely on weak coherent pulses vulnerable to Photon-Number-Splitting (PNS) attacks. The Gottesman–Lo–Lütkenhaus–Preskill (GLLP) framework addresses these imperfections, deriving secure key [...] Read more.
Quantum Key Distribution (QKD) enables the sharing of cryptographic keys secured by quantum mechanics. The BB84 protocol assumes single-photon sources, but practical systems rely on weak coherent pulses vulnerable to Photon-Number-Splitting (PNS) attacks. The Gottesman–Lo–Lütkenhaus–Preskill (GLLP) framework addresses these imperfections, deriving secure key rate bounds under limited PNS scenarios. The decoy-state protocol further improves performance by refining single-photon yield estimates, but still considers multi-photon states as insecure, thereby limiting intensities and constraining key rate and distance. More recently, finite-key security bounds for decoy-state QKD have been extended to address general attacks, ensuring security against adversaries capable of exploiting arbitrary strategies. In this work, we focus on a specific class of attacks, the generalized PNS attack, and demonstrate that higher pulse intensities can be securely used by employing Bayesian inference to estimate key parameters directly from observed data. By raising the pulse intensity to 10 photons, we achieve a 50-fold increase in key rate and a 62.2% increase in operational range (about 200 km) compared to the decoy-state protocol. Furthermore, we accurately model after-pulsing using a Hidden Markov Model (HMM) and reveal inaccuracies in decoy-state calculations that may produce erroneous key-rate estimates. While this methodology does not address all possible attacks, it provides a new approach to security proofs in QKD by shifting from worst-case assumption analysis to observation-dependent inference, advancing the reach and efficiency of discrete-variable QKD protocols. Full article
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