Communication
Star‑Connected Computer Network and Communication


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Received: 1 December 2025; Revised: 25 December 2025; Accepted: 29 December 2025; Published: 8 January 2026
Star-connected computer networks are explored using the example of terahertz modeling. Existence conditions for the complete synchronization between constituent lasers are found numerically. Numerical simulations were conducted using the Matrix Laboratory (MATLAB) software to solve Delay Differential Equations. Extensive numerical simulations with different initial states confirm that high-quality, near-perfect complete synchronization between terahertz lasers occurs. As in the real world, parameters can differ; we simulated the star-connected computer network model with parameter mismatches of 3–5%. Still, we have obtained close to 100% of correlation between the dynamics of terahertz lasers. Synchronization is important in chaos-based communication. It is underlined that chaos-based communication security between computer networks can offer an additional layer of security to the traditional cryptography based on the Rivest, Shamir, and Adleman (RSA) algorithm. This algorithm uses the mathematical challenge of factoring very large prime numbers. The extra layer of security is of immense importance in light of the exponential increase in central processing units (CPUs) in computers. This is especially true in light of the quantum processing unit (QPU), which is the core processor of a quantum computer, using qubits in superposition and entanglement to perform complex, parallel calculations far beyond classical CPUs. Unlike traditional binary CPUs, QPUs excel at optimization, cryptography, and artificial intelligence tasks.
Keywords:
Star Networks Terahertz Model Josephson Junctions Time Delay Systems Chaos Synchronization CommunicationReferences
- Schoell, E.; Schuster, H.G. Handbook of Chaos Control, 2nd ed; Wiley-VCH: Weinheim, Germany, 2007; pp. 1–849.
- Shahverdiev, E.M. Modulated Time Delays, Synchronized Josephson Junctions in High-Temperature Superconductors and Chaotic Terahertz Waves. J. Supercond. Nov. Magn. 2021, 34, 1125–1132. DOI: https://doi.org/10.1007/s10948-021-05837-7
- Nishijima, S.; Eckroad, S.; Marian, A.; et al. Superconductivity and the environment: a Roadmap. Supercond. Sci. Technol. 2013, 26, 113001. DOI: https://doi.org/10.1088/0953-2048/26/11/113001
- Pecora, L.M.; Carroll, T.L. Synchronization in Chaotic Systems. Phys. Rev. Lett. 1990, 64, 821–824. DOI: https://doi.org/10.1103/PhysRevLett.64.821
- Shahverdiev, E.M.-O. Boundedness of Dynamical Systems and Chaos Synchronization. Phys. Rev. E 1999, 60, 3905–3909. DOI: https://doi.org/10.1103/PhysRevE.60.3905
- Rosenblum, M.G.; Pikovsky, A.S.; Kurths, J. From Phase to Lag Synchronization in Coupled Chaotic Oscillators. Phys. Rev. Lett. 1997, 78, 4193–4196. DOI: https://doi.org/10.1103/PhysRevLett.78.4193
- Shahverdiev, E.M.; Sivaprakasam, S.; Shore, K.A. Lag Synchronization in Time-Delayed Systems. Phys. Lett. A 2002, 292, 320–324. DOI: https://doi.org/10.1016/S0375-9601(01)00824-6
- Shahverdiev, E.M.; Nuriev, R.A.; Hashimova, L.H.; et al. Complete Inverse Chaos Synchronization, Parameter Mismatches and Generalized Synchronization in the Multi-Feedback Ikeda Model. Chaos Solitons Fractals 2008, 36, 211–216. DOI: https://doi.org/10.1016/j.chaos.2006.06.026
- Ghosh, S.; Sar, G.K.; Majhi, S.; et al. Antiphase Synchronization in a Population of Swarmalators. Phys. Rev. E 2023, 108, 034217. DOI: https://doi.org/10.1103/PhysRevE.108.034217
- Shahverdiev, E.M.; Shore, K.A. Generalized Synchronization in Time-Delayed Systems. Phys. Rev. E 2005, 71, 016201. DOI: https://doi.org/10.1103/PhysRevE.71.016201
- Shahverdiev, E.M.; Sivaprakasam, S.; Shore, K.A. Dual and Dual-Cross Synchronizations in Chaotic Systems. Opt. Commun. 2003, 216, 179–183. DOI: https://doi.org/10.1016/S0030-4018(02)02286-1
- Mercadier, J; Doumbia, Y; Bittner, S; et al. Optical chaos synchronization in a cascaded injection experiment. Opt. Lett. 2024, 49, 2613-2616. DOI: https://doi.org/10.1364/OL.522576
- Khattar, D.; Agrawal, N.; Singh, G. Chaos Synchronization of a New Chaotic System Having Exponential Term Via Adaptive and Sliding Mode Control. Differ. Equ. Dyn. Syst. 2025, 33, 475–493. DOI: https://doi.org/10.1007/s12591-023-00635-0
- Liu, J.; Zuo, T. Deep Adaptive Chaos Synchronization Based on Optimization Algorithm. IEEE Access 2025, 13, 38671–38684. DOI: https://doi.org/10.1109/ACCESS.2025.3545441
- Voss, H.U. Anticipating Chaotic Synchronization. Phys. Rev. E 2000, 61, 5115–5119.
- Ott, E.; Spano, M. Controlling Chaos. Phys. Today 1995, 48, 34–40. DOI: https://doi.org/10.1063/1.881461
- Ditto, W.L.; Showalter, K. Introduction: Control and synchronization of chaos. Chaos 1997, 7, 509-511. DOI: https://doi.org/10.1063/1.166276
- Sivaprakasam, S.; Shahverdiev, E.; Spencer, P.; et al. Experimental Demonstration of Anticipating Synchronization in Chaotic Semiconductor Lasers with Optical Feedback. Phys. Rev. Lett. 2001, 87, 154101. DOI: https://doi.org/10.1103/PhysRevLett.87.154101
- Eckhardt, B.; Ott, E.; Strogatz, S.H.; et al. Modelling walker synchronization on the Millennium Bridge. Phys. Rev. E 2007, 75, 021110. DOI: https://doi.org/10.1103/PhysRevE.75.021110
- Yanchuk, S.; Giacomelli, G. Spatio-Temporal Phenomena in Complex Systems with Time Delays. J. Phys. A: Math. Theor. 2017, 50, 103001. DOI: https://doi.org/10.1088/1751-8121/50/10/103001
- Kinzel, W. Chaos in networks with time-delayed couplings. Philos. Trans. A Math Phys. Eng. Sci. 2013, 371, 20120461. DOI: https://doi.org/10.1098/rsta.2012.0461
- Ghosh, D.; Banerjee, S.; Chowdhury, A.R. Synchronization between variable time-delayed systems and cryptography. Europhys. Lett. 2007, 80, 30006. DOI: https://doi.org/10.1209/0295-5075/80/30006
- Star Topology. Available online: https://www.sciencedirect.com/topics/computer-science/star-topology (accessed on 1 June 2025).
- Strogatz, S.H. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, 3rd ed.; Chapman and Hall/CRC: Boca Raton, FL, USA, 2024. DOI: https://doi.org/10.1201/9780429398490
- Lin, S.-Z. Mutual Synchronization of Two Stacks of Intrinsic Josephson Junctions in Cuprate Superconductors. J. Appl. Phys. 2014, 115, 173901. DOI: https://doi.org/10.1063/1.4874677
- What is network topology? Available online: https://www.ibm.com/think/topics/network-topology (accessed on 1 December 2025).
- Network Topology. Available online: https://www.sciencedirect.com/topics/computer-science/network-topology (accessed on 1 December 2025).
- Types of network topology. Available online: https://www.geeksforgeeks.org/computer-networks/types-of-network-topology (accessed on 1 December 2025).
- Fitch, M.J.; Osiander, R. Terahertz waves for communications and sensing. J. Johns Hopkins APL Tech. Dig. 2004, 25, 348–355.
- Argyris, A.; Syvridis, D.; Larger, L.; et al. Chaos-Based Communications at High Bit Rates Using Commercial Fibre-Optic Links. Nature 2005, 438, 343–346. DOI: https://doi.org/10.1038/nature04275
- Ki, E.-J.; Shin, S.; Oh, J. The State of Environmental Communication Research: An Analysis of Published Studies in the Communication Disciplines. J. Intell. Commun. 2022, 2. DOI: https://doi.org/10.54963/jic.v2i1.38
- Kallas, K.; Tannous, C.; Faraoun, H. A Zero-Sum Game-Theoretic Analysis for CostAware Backdoor Attacks and Defenses in Deep Learning. J. Intell. Commun. 2025, 4, 74–92. DOI: https://doi.org/10.54963/jic.v4i2.1576.
- Kanthavel, R.; Dhaya, R.; Ahilan, A. AI-Based Efficient WUGS Network Channel Modeling and Clustered Cooperative Communication. ACM Trans. Sen. Netw. 2022, 18, 1–14. DOI: https://doi.org/10.1145/3469034
- Baek, S.-H.; Walsh, N.; Chugunov, I.; et al. Centimeter-Wave Free-Space Neural Time-of-Flight Imaging. ACM Trans. Graph. 2023, 42, 1–18. DOI: https://doi.org/10.1145/3522671
- Krishna Moorthy, S.; Mcmanus, M.; Guan, Z. ESN Reinforcement Learning for Spectrum and Flight Control in THz-Enabled Drone Networks. IEEE/ACM Trans. Networking 2022, 30, 782–795. DOI: https://doi.org/10.1109/TNET.2021.3128836
- Lei, D.; Lin, X.; Yu, X.; et al. Privacy preserving optimization of communication networks. Nat. Commun. 2025, 16, 8501. DOI: https://doi.org/10.1038/s41467-025-63504-0
- Parastesh, F.; Mehrabbeik, M.; Rajagopal, K.; et al. Synchronization stability in simplicial complexes of near-identical systems. Phys. Rev. Research 2025, 7, 033039. DOI: https://doi.org/10.1103/ml7b-r35h
- Fang, F.; Ma, J.; Ma, Y.-J.; et al. Social contagion on higher-order networks: The effect of relationship strengths. Chaos Solitons Fractals 2024, 186, 115149. DOI: https://doi.org/10.1016/j.chaos.2024.115149

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