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1. Verfasser: Ahmed, Shakil
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2510.23610
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author Ahmed, Shakil
author_facet Ahmed, Shakil
contents Quantum networks (QNs) supported by terahertz (THz) wireless links present a transformative alternative to fiber-based infrastructures, particularly in mobile and infrastructure-scarce environments. However, signal attenuation, molecular absorption, and severe propagation losses in THz channels pose significant challenges to reliable quantum state transmission and entanglement distribution. To overcome these limitations, we propose a dynamic reconfigurable intelligent surface (RIS)-assisted wireless QN architecture that leverages adaptive RIS elements capable of switching between active and passive modes based on the incident signal-to-noise ratio (SNR). These dynamic RIS elements enhance beamforming control over amplitude and phase, enabling robust redirection and compensation for THz-specific impairments. We develop a detailed analytical model that incorporates key physical layer phenomena in THz quantum links, including path loss, fading, thermal noise, and alignment variations. A secure optimization framework is formulated to jointly determine RIS placement and entanglement generation rate (EGR) allocation, while satisfying fidelity, security, and fairness constraints under diverse quality of service (QoS) demands. The model also includes an exploration of side-channel vulnerabilities arising from dynamic RIS switching patterns. Simulation results demonstrate that the proposed architecture yields up to 87\% fidelity enhancement and 65\% fairness improvement compared to static RIS baselines, while maintaining robustness under realistic THz channel conditions. These results underscore the promise of dynamic RIS technology in enabling scalable and adaptive quantum communications over wireless THz links.
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publishDate 2025
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spellingShingle Dynamic RIS-Assisted THz Quantum Networks: Joint Optimization of Entanglement Generation and Fidelity under Channel Impairments
Ahmed, Shakil
Quantum Physics
Emerging Technologies
Information Theory
Quantum networks (QNs) supported by terahertz (THz) wireless links present a transformative alternative to fiber-based infrastructures, particularly in mobile and infrastructure-scarce environments. However, signal attenuation, molecular absorption, and severe propagation losses in THz channels pose significant challenges to reliable quantum state transmission and entanglement distribution. To overcome these limitations, we propose a dynamic reconfigurable intelligent surface (RIS)-assisted wireless QN architecture that leverages adaptive RIS elements capable of switching between active and passive modes based on the incident signal-to-noise ratio (SNR). These dynamic RIS elements enhance beamforming control over amplitude and phase, enabling robust redirection and compensation for THz-specific impairments. We develop a detailed analytical model that incorporates key physical layer phenomena in THz quantum links, including path loss, fading, thermal noise, and alignment variations. A secure optimization framework is formulated to jointly determine RIS placement and entanglement generation rate (EGR) allocation, while satisfying fidelity, security, and fairness constraints under diverse quality of service (QoS) demands. The model also includes an exploration of side-channel vulnerabilities arising from dynamic RIS switching patterns. Simulation results demonstrate that the proposed architecture yields up to 87\% fidelity enhancement and 65\% fairness improvement compared to static RIS baselines, while maintaining robustness under realistic THz channel conditions. These results underscore the promise of dynamic RIS technology in enabling scalable and adaptive quantum communications over wireless THz links.
title Dynamic RIS-Assisted THz Quantum Networks: Joint Optimization of Entanglement Generation and Fidelity under Channel Impairments
topic Quantum Physics
Emerging Technologies
Information Theory
url https://arxiv.org/abs/2510.23610