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 through real-time measurement-driven adjustments. 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. This model also acts as a digital twin, simulating quantum channel measurements under uncertainty. 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 [1] . Fidelity and leakage metrics are treated as measurable quantities, reinforcing the role of measurement in system adaptation. 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. The integration of adaptive RIS control and fidelity-aware modeling highlights the digitalization of quantum measurement processes. These results underscore the promise of dynamic RIS technology in enabling scalable and adaptive quantum communications over wireless THz links.
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 through real-time measurement-driven adjustments. 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. This model also acts as a digital twin, simulating quantum channel measurements under uncertainty. 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 [1] . Fidelity and leakage metrics are treated as measurable quantities, reinforcing the role of measurement in system adaptation. 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. The integration of adaptive RIS control and fidelity-aware modeling highlights the digitalization of quantum measurement processes. These results underscore the promise of dynamic RIS technology in enabling scalable and adaptive quantum communications over wireless THz links.
Quantum-classical hybrid communication is emerging as a key enabler for future 6G networks, where THz communication and quantum services are expected to coexist over intelligent and reconfigurable wireless infrastructures. A fundamental challenge in such systems is that reconfigurable intelligent surface (RIS) phase control simultaneously influences classical communication performance and quantum-state evolution, making reliable entanglement preservation difficult in dynamic propagation environments. To address this challenge, this paper proposes an AI-native Entanglement-Sustained Reconfigurable Intelligent Surface (AI-ES-RIS) framework for hybrid quantum-classical THz communication. A unified model is developed to jointly characterize THz-wave propagation and Bell-state evolution through a phase-flip-inspired decoherence representation. To capture RIS-induced quantum degradation, a weighted mismatch-based decoherence model is introduced that links RIS phase perturbations, channel-dependent element significance, and entanglement fidelity degradation. Furthermore, a Proximal Policy Optimization (PPO)-based controller is designed to adapt RIS phase configurations by jointly optimizing communication reliability and quantum-state preservation. Simulation results demonstrate that the proposed framework consistently achieves higher entanglement fidelity, lower decoherence probability, and competitive communication performance compared with communication-centric and model-based RIS optimization strategies. Distributional analysis further confirms improved quantum-state robustness across diverse channel realizations, while scalability studies demonstrate favorable runtime characteristics for larger RIS dimensions. Additional meta-learning and federated learning extensions show enhanced adaptation and convergence under heterogeneous propagation environments. The results establish that RIS control in hybrid quantum-classical networks should be treated as a joint communication-and-quantum optimization problem rather than as independent design objectives, providing a promising foundation for future THz-enabled quantum-aware 6G systems.
Quantum networks (QNs) relying on free-space optical (FSO) quantum channels can support quantum applications in environments wherein establishing an optical fiber infrastructure is challenging and costly. However, FSO-based QNs require a clear line-of-sight (LoS) between users, which is challenging due to blockages and natural obstacles. In this paper, a reconfigurable intelligent surface (RIS)-assisted FSO-based QN is proposed as a cost-efficient framework providing a virtual LoS between users for entanglement distribution. A novel modeling of the quantum noise and losses experienced by quantum states over FSO channels defined by atmospheric losses, turbulence, and pointing errors is derived. Then, the joint optimization of entanglement distribution and RIS placement problem is formulated, under heterogeneous entanglement rate and fidelity constraints. This problem is solved using a simulated annealing metaheuristic algorithm. Simulation results show that the proposed framework effectively meets the minimum fidelity requirements of all users’ quantum applications. This is in stark contrast to baseline algorithms that lead to a drop of at least 84% in users’ end-to-end fidelities. The proposed framework also achieves a 63% enhancement in the fairness level between users compared to baseline rate maximizing frameworks. Finally, the weather conditions, e.g., rain, are observed to have a more significant effect than pointing errors and turbulence.
This paper presents a novel system architecture for hybrid satellite communications, integrating quantum key distribution (QKD) and classical radio frequency (RF) data transmission using a dual-band reconfigurable intelligent surface (RIS). The motivation is to address the growing need for global, secure, and reliable communications by leveraging the security of quantum optical links and the robustness of classical RF channels within a unified framework. By employing a frequency-selective RIS, the system independently optimizes both quantum (850 nm) and classical (S-band) channels in real time, dynamically adapting to environmental fluctuations such as atmospheric turbulence and rain attenuation. The joint optimization of the quantum bit error rate (QBER) and the classical signal-to noise ratio (SNR) is formulated as a quadratic unconstrained binary optimization (QUBO) problem, enabling efficient adaptive phase control utilizing both quantum and classical computational methods. Comprehensive theoretical modeling and simulations, benchmarked against experimental data from the Micius satellite, demonstrate substantial performance gains. Notably, the RIS assisted system reduces QBER from approximately 2.5% to 0.7%, increases the secure key rate (SKR) to over 30,000 bits per second, and enhances classical RF SNR by about 3 dB at high elevation angles. These results illustrate the practical potential of hybrid RIS-assisted satellite links to deliver robust, efficient, and secure global communications.
A reconfigurable intelligent surface (RIS)-aided multiple-input multiple-output (MIMO) wireless communication system is considered in this paper wherein the transmitter, Alice modulates secret keys, by using a continuous variable quantum key distribution technique to be transmitted to the receiver, Bob, which employs homodyne detection for data decoding. The data is transmitted over two paths, namely a direct path between Alice and Bob and the wireless path between them via the RIS. Transmit and receive beamsplitters are employed in the system to transform the MIMO terahertz channels into parallel single-input single-output channels. Considering an eavesdropper, Eve, to attack all the three wireless channels in the system (i.e., the direct channel, the channel between Alice and RIS, and between the RIS and Bob) but having restricted quantum memory limiting it to store the ancilla modes from either of these three wireless channels, novel expressions for the secret key rate (SKR) of the system are derived. Numerical results are presented to demonstrate the dependency of the system's performance on various system parameters. It is observed that the RIS plays a key role in increasing the SKR of the system and the transmission distance, ensuring secure communications between Alice and Bob. The significance of employing RIS is observed specifically for the case when Eve measures the ancilla modes of the channel between the RIS and Bob. Furthermore, for all such measurement scenarios, optimal angles are obtained for the phase shifts of the RIS elements to maximize the SKR for various MIMO configurations and transmission distance between Alice and Bob.
In this paper, a multiple-input multiple-output (MIMO) wireless system incorporating a reconfigurable intelligent surface (RIS) to efficiently operate at terahertz (THz) frequencies is considered. The transmitter, Alice, employs continuous-variable quantum key distribution (CV-QKD) to communicate secret keys to the receiver, Bob, who utilizes either homodyne or heterodyne detection. The latter node applies the least-squares approach to estimate the effective MIMO channel gain matrix prior to receiving the secret key, and this estimation is made available to Alice via an error-free feedback channel. An eavesdropper, Eve, is assumed to employ either a collective Gaussian entanglement attack or an individual attack on the feedback channel to obtain the estimated channel state information. We present novel closed-form expressions for the secret key rate (SKR) performance of the proposed RIS-assisted THz CV-QKD system. An optimization framework to obtain the optimal phase shifts of the RIS to maximize the SKR is proposed, and a particle-swarm optimization (PSO)-based algorithm is deployed to solve the optimization problem. The effect of various system parameters, such as the number of RIS elements and their phase configurations, the channel estimation error, and the detector noise, on the SKR performance is studied via numerical evaluation of the derived formula. It is demonstrated that the RIS contributes to larger SKR for larger link distances, and that heterodyne detection is preferable over homodyne at lower pilot symbol powers.
A reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output (MIMO) continuous-variable quantum key distribution (CV-QKD) system operating at terahertz (THz) frequencies, in which a transmitter, Alice, encodes secret keys using Gaussian-modulated coherent states and communicates them to a legitimate receiver, Bob, is considered in this paper. The composite wireless channel, comprising the direct Alice-Bob link and the RIS-assisted reflected link, is modeled as a passive linear Gaussian quantum channel, enabling a unitary dilation that preserves the canonical commutation relations. The security of the considered system is investigated under collective Gaussian entangling attacks by introducing a practical access-constrained eavesdropping model, in which an eavesdropper, Eve, is assumed to access only the environmental modes associated with physically accessible propagation segments. A unified analytical framework is developed to derive the achievable secret key rate (SKR) across all single-segment, pairwise-segment, and full-segment access scenarios, assuming homodyne detection and reverse reconciliation at Bob. Furthermore, an optimization framework is developed to determine the optimal RIS phase configuration matrix and transmitter/receiver beam-splitter parameters that maximize the SKR performance. The resulting optimization problem is efficiently solved using particle swarm optimization. Numerical results are presented to demonstrate the system's performance with respect to various free parameters. It is showcased that the secrecy performance strongly depends on Eve's accessible propagation segments, with the Alice-RIS channel constituting the most security-critical segment.