https://xlin.io/authors/nageswara-s-v-rao/Nageswara S. V. RaoHugoBlox Kit (https://hugoblox.com)en-USThu, 27 Aug 2026 00:00:00 +0000https://xlin.io/media/authors/nageswara-s-v-rao_hu_31e9c64aee4910bc.jpghttps://xlin.io/authors/nageswara-s-v-rao/https://xlin.io/publication/ton-26-entanglement/Thu, 27 Aug 2026 00:00:00 +0000https://xlin.io/publication/ton-26-entanglement/<h2 id="abstract">Abstract</h2> <p>Entanglement distribution is a core function of quantum networks essential for operations including teleportation, distributed quantum sensing, and multisite computation. Entanglement throughput and fidelity are two critical performance measures that depend on the quantum transmission along the links and swapping operations at the repeaters along the path. We study the problem of computing a end-to-end entanglement path that satisfies both fidelity and throughput requirements, leveraging qubit buffers at the nodes and considering the sequential swapping order. We show that the general problem of simultaneously satisfying both metrics to be NP-hard, and develop an algorithm to maximize throughput subject to a given fidelity threshold. We introduce the concepts of entanglement probability distribution and path domination and exploit them in the design of our algorithm. Extensive numerical results show that our algorithm can find optimal solutions in networks with thousands of nodes in less than a second. We also describe practical and possible implementation aspects of this algorithm in terms of devices and architecture support.</p> <p>Published online as an Early Access article on August 27, 2026. Final volume and page numbers have not yet been assigned.</p>https://xlin.io/publication/arxiv-26-quantum/Tue, 11 Aug 2026 00:00:00 +0000https://xlin.io/publication/arxiv-26-quantum/<h2 id="abstract">Abstract</h2> <p>Entanglement distribution in quantum networks must jointly account for limited link capacities, probabilistic entanglement swapping, and heterogeneous link fidelities. In this paper, we study multi-pair fidelity-aware rate allocation in quantum networks. We formulate three rate-allocation problems: rate sum, rate sum subject to minimum-rate constraints, and max-min fairness. Prior work has studied a special case of the rate sum problem, where all links have identical fidelity. This special case admits a polynomial-time algorithm. We prove that all three problems are NP-hard. We then study optimization versions of these problems which maximize the minimum end-to-end fidelity subject to throughput or fairness requirements. We present fully polynomial-time approximation schemes (FPTAS) for solving these optimization problems. Experiments on randomly generated networks demonstrate the computational effectiveness of the proposed schemes.</p> <p>Preprint, first submitted 2026-08-11.</p>