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IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT)

Optimizing Entanglement Distribution and Quantum Source Placement in Probabilistic Quantum Networks

S. N. Singh, Adhishek Kr. Mishra, Rajesh Singh

Published May 15, 2026• 0 citations
Publisher
DOI
10.1109/ic2pct68894.2026.11584482

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The evolution of quantum networks towards distributed quantum computing and sensing necessitates the efficient distribution of multipartite entangled states among multiple users. However, most existing entanglement routing studies primarily focus on efficient entanglement distribution and typically assume that quantum sources are either fixed or available on all network edges. Due to the scarcity and high cost of quantum sources, some prior studies have focused on optimized source placement strategies, but these existing studies are confined to bipartite state distributions. Consequently, how to jointly optimize quantum source placement and entanglement routing for efficient multipartite state distribution under realistic resource constraints remains an open problem. In this work, we propose an Optimized source Placement and Reactive entanglement Routing (OP-RR) framework to maximize the multipartite state distribution rate given a limited amount of quantum sources. Numerical results on a grid and on the Tokyo topology demonstrate that OP-RR consistently outperforms baseline algorithms with non-optimized source placement, achieving an improvement of up to 16.7× in the multipartite distribution rate, while maintaining robustness under varying operation probabilities and scalability as the size of multipartite states increases.
Quantum network implementations using single spontaneous parametric downconversion (SPDC)-based broadband entangled photon pair source (EPPS) have been reported recently. Here, leveraging the wavelength-correlation between entangled photon pairs, the traditional wavelength division multiplexing (WDM) method is utilized to route photons based on their wavelengths. From single EPPS, entangled photon pairs are distributed in a centralized way to different node pairs in the network. However, the number of nodes pairs that can be entangled in a network is limited by the number of entangled wavelength pairs that an EPPS can generate. To entangle a higher number of node pairs in a network, multiple EPPSs can be employed. In this work, we present a WDM-based entanglement distribution approach using multiple EPPSs in multi-hop repeaterless mesh optical networks. We experimentally characterize two EPPSs developed in-house and consider multiple such EPPSs in the network to perform network-level simulations. We consider heterogeneous entanglement demands requiring different entanglement bit (ebit) rates and entanglement visibility. For each entanglement demand, EPPS placement/selection, wavelength-pair assignment, and photon pair routing are performed considering the degradation in both ebit rate and visibility with fiber length and hops in the network. Two main findings of this study include: (i) a hybrid approach of one-photon (OP) and both-photon (BP) entanglement distribution provides higher flexibility in multi-EPPS placement and (ii) distributed entanglement distribution using multiple EPPSs enables better entanglement resource utilization and higher entanglement demand acceptance as compared to centralized entanglement distribution.
Entanglement routing plays a vital role in quantum networks. Previous works on entanglement routing did not note that all-optical switching capacity can be used to improve the network throughput or ignored that the placement of Entangled Photon Sources (EPS), another type of precious (and costly) quantum source, which also limits the network throughput. In this paper, we propose OptEPS to jointly optimize all-optical switching and EPS placement in entanglement routing to maximize the quantum network throughput. The main challenge of OptEPS lies in two folds: i). an entanglement may fail to be created; ii). the joint optimization problem suffers from a large time complexity. To overcome these challenges, we first formulate the joint optimization problem as a link-path based model and prune out some candidate paths in order to reduce the time complexity. Then, efficient algorithms are proposed to derive a near-optimal solution in a timely manner. Extensive simulations show that compared with the solutions ignoring EPS placement or without introducing all-optical switching, OptEPS will increase the network throughput by 1557% and 109%, respectively.