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Reconfigurable Intelligent Surface (RIS)-Assisted Entanglement Distribution in FSO Quantum Networks

Mahdi Chehimi, Mohamed Elhattab, Walid Saad, Gayane Vardoyan, Nitish K. Panigrahy, Chadi Assi, Don Towsley

TL;DR

This work tackles entanglement distribution in obstructed free-space optical quantum networks by introducing a RIS-assisted architecture that creates a virtual LoS. It derives a physics-aware quantum-channel model incorporating atmospheric loss, Gamma-Gamma turbulence, and pointing errors, and develops a turbulence-induced phase-noise model; a closed-form probability of success and a Bell-diagonal end-to-end state analysis are provided. The authors formulate and solve a non-convex optimization to jointly place the RIS and allocate initial entanglement generation rates under heterogeneous rate and fidelity requirements using simulated annealing, via a weighted fairness index. The results demonstrate that the framework satisfies minimum fidelity for all users, achieves substantial fairness gains (∼64%), and outperforms fidelity-agnostic baselines, while revealing weather as a dominant factor and the end-to-end distance as a key rate predictor. This work offers a scalable, practical approach to deploying multi-user QNs in obstructed environments without quantum repeaters or satellites.

Abstract

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 83% in users' end-to-end fidelities. The proposed framework also achieves a 64% 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.

Reconfigurable Intelligent Surface (RIS)-Assisted Entanglement Distribution in FSO Quantum Networks

TL;DR

This work tackles entanglement distribution in obstructed free-space optical quantum networks by introducing a RIS-assisted architecture that creates a virtual LoS. It derives a physics-aware quantum-channel model incorporating atmospheric loss, Gamma-Gamma turbulence, and pointing errors, and develops a turbulence-induced phase-noise model; a closed-form probability of success and a Bell-diagonal end-to-end state analysis are provided. The authors formulate and solve a non-convex optimization to jointly place the RIS and allocate initial entanglement generation rates under heterogeneous rate and fidelity requirements using simulated annealing, via a weighted fairness index. The results demonstrate that the framework satisfies minimum fidelity for all users, achieves substantial fairness gains (∼64%), and outperforms fidelity-agnostic baselines, while revealing weather as a dominant factor and the end-to-end distance as a key rate predictor. This work offers a scalable, practical approach to deploying multi-user QNs in obstructed environments without quantum repeaters or satellites.

Abstract

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 83% in users' end-to-end fidelities. The proposed framework also achieves a 64% 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.
Paper Structure (17 sections, 2 theorems, 42 equations, 7 figures, 1 table, 1 algorithm)

This paper contains 17 sections, 2 theorems, 42 equations, 7 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Prior Works
  3. Contributions
  4. System Model
  5. Quantum Network (QN) Elements and Geometry
  6. Quantum Channel Model
  7. Atmospheric loss
  8. Atmospheric turbulence
  9. Pointing Error Model
  10. Entanglement Generation and Distribution
  11. Losses and EGR Analysis
  12. Noise and E2E Entangled State Analysis
  13. Joint RIS Placement and EGR Allocation Optimization Problem
  14. Simulation Results and Analysis
  15. Conclusion
  16. ...and 2 more sections

Key Result

Theorem 1

The probability of successfully sending a single entangled photon from the QBS to user $i\in\mathcal{N}$ over an FSO quantum channel (given in eq_channel) considering the atmospheric loss, turbulence, and pointing error is given by: where $G_{n,m}^{p,q}$ is the Meijer's G-function, $\Gamma(.)$ is the Gamma function, and $\chi_{\mathrm{th}} = \frac{\zeta_{\mathrm{th}}}{\varsigma \eta}$.

Figures (7)

  • Figure 1: Studied system model of an RIS-assisted FSO-based QN with blockages that result in the absence of direct LoS connections between the QBS and end users.
  • Figure 2: Performance of the proposed probability of success expression in Theorem 1 against turbulence parameter and weather condition.
  • Figure 3: Optimal RIS placement for different scenarios of user distribution.
  • Figure 4: E2E EGR achieved at the optimal RIS location for a QN with three users located based on scenario 1 in Fig. \ref{['fig_result_fig1_RIS_placement']}.
  • Figure 5: Achieved E2E fidelity in a 3-user QN under different turbulence effects.
  • ...and 2 more figures

Theorems & Definitions (5)

  • Theorem 1
  • proof
  • Remark 1
  • Proposition 1
  • proof