Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Age of Entanglement in Satellite Repeater Chains with Intermittent Availability

Elif Tugce Ceran

Abstract

Timely availability of high-fidelity entanglement is essential for emerging quantum networks. This paper introduces the Age of Entanglement (AoE) as a novel performance metric that captures the freshness of bipartite entanglement under continuous distribution in quantum repeater chains. AoE extends classical Age of Information (AoI)-based metrics to quantum networking by capturing storage, decoherence, and probabilistic entanglement generation and swapping. We study a satellite-assisted quantum repeater network in which entangled pairs are generated probabilistically, stored in quantum memories that suffer from decoherence, and combined to form end-to-end entangled links. Satellite-ground connectivity is intermittent and modeled as a two-state Markov chain. The resulting AoE minimization problem is formulated as an infinite-horizon Markov decision process (MDP), where control actions determine when to generate, store, or swap entangled pairs under stochastic link availability and memory degradation. Using relative value iteration, we characterize AoE-optimal policies and evaluate their performance numerically. Our results highlight the impact of decoherence, imperfect operations, and visibility dynamics, and show that the proposed dynamic policies significantly outperform swap-as-soon-as-possible and greedy entanglement generation strategies. Our results provide practical design and control guidelines for satellite-enabled quantum repeater chains supporting continuous entanglement distribution.

Age of Entanglement in Satellite Repeater Chains with Intermittent Availability

Abstract

Timely availability of high-fidelity entanglement is essential for emerging quantum networks. This paper introduces the Age of Entanglement (AoE) as a novel performance metric that captures the freshness of bipartite entanglement under continuous distribution in quantum repeater chains. AoE extends classical Age of Information (AoI)-based metrics to quantum networking by capturing storage, decoherence, and probabilistic entanglement generation and swapping. We study a satellite-assisted quantum repeater network in which entangled pairs are generated probabilistically, stored in quantum memories that suffer from decoherence, and combined to form end-to-end entangled links. Satellite-ground connectivity is intermittent and modeled as a two-state Markov chain. The resulting AoE minimization problem is formulated as an infinite-horizon Markov decision process (MDP), where control actions determine when to generate, store, or swap entangled pairs under stochastic link availability and memory degradation. Using relative value iteration, we characterize AoE-optimal policies and evaluate their performance numerically. Our results highlight the impact of decoherence, imperfect operations, and visibility dynamics, and show that the proposed dynamic policies significantly outperform swap-as-soon-as-possible and greedy entanglement generation strategies. Our results provide practical design and control guidelines for satellite-enabled quantum repeater chains supporting continuous entanglement distribution.
Paper Structure (15 sections, 1 theorem, 12 equations, 4 figures, 1 algorithm)

This paper contains 15 sections, 1 theorem, 12 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related Work
  3. System Model
  4. Age of Entanglement (AoE)
  5. MDP Formulation and RVI
  6. Markov Decision Process Formulation
  7. State Space
  8. Action Space
  9. Visibility Dynamics
  10. State Transitions
  11. Reward
  12. Simulation Results
  13. Benchmark Heuristic Policies
  14. Numerical Results
  15. Conclusion

Key Result

Theorem 1

For the satellite repeater-chain average AoE minimization problem defined in average_reward, there exists an average-cost optimal stationary deterministic policy $\pi^*$. Moreover, the Relative Value Iteration (RVI) algorithm converges (up to an additive constant), and the resulting stationary polic

Figures (4)

  • Figure 1: Average age of entanglement (AoE) versus the elementary link generation probability $p_L$ under mostly visible links with visibility transition matrices $P_{12}=P_{23}=[0.3\ 0.7;\ 0.3\ 0.7]$, when $p_{sw} = 0.8$.
  • Figure 2: Average age of entanglement (AoE) versus elementary link generation probability $p_L$ under moderately visible links with visibility transition matrices $P_{12}=P_{23}=[0.6\ 0.4;\ 0.4\ 0.6]$, when $p_{sw} = 0.8$.
  • Figure 3: Average age of entanglement (AoE) versus swapping success probability $p_{sw}$ under asymmetric visibility with visibility transition matrices $P_{12}=[0.1\ 0.9;\ 0.1\ 0.9]$ and $P_{23}=[0.55\ 0.45;\ 0.55\ 0.45]$, when $p_L = 0.3$.
  • Figure 4: Convergence of the Relative Value Iteration (RVI) algorithm under different scenarios.

Theorems & Definitions (2)

  • Theorem 1: Optimal stationary policy and RVI optimality
  • proof