Multipartite Entanglement Distribution in Quantum Networks using Subgraph Complementations

• URL: http://arxiv.org/abs/2308.13700v4
• Date: Sun, 19 May 2024 16:20:33 GMT
• Title: Multipartite Entanglement Distribution in Quantum Networks using Subgraph Complementations
• Authors: Aniruddha Sen, Kenneth Goodenough, Don Towsley,
• Abstract summary: We propose a novel approach for distributing graph states across a quantum network. We show that the distribution of graph states can be characterized by a system of subgraph complementations. We find a close to optimal sequence of subgraph complementation operations to distribute an arbitrary graph state.
• Score: 9.32782060570252
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quantum networks are important for quantum communication and allow for several tasks such as quantum teleportation, quantum key distribution, quantum sensing, and quantum error correction. Graph states are a specific class of multipartite entangled states that can be represented by graphs. We propose a novel approach for distributing graph states across a quantum network. We show that the distribution of graph states can be characterized by a system of subgraph complementations, which we also relate to the minimum rank of the underlying graph and the degree of entanglement quantified by the Schmidt-rank of the quantum state. We analyze resource usage for our algorithm and show that it improves on the number of qubits, bits for classical communication, and EPR pairs utilized, as compared to prior work. In fact, the number of local operations and resource consumption for our approach scales linearly in the number of vertices. This produces a quadratic improvement in completion time for several classes of graph states represented by dense graphs, which translates into an exponential improvement by allowing parallelization of gate operations. This leads to improved fidelities in the presence of noisy operations, as we show through simulation in the presence of noisy operations. Common classes of graph states are classified along with their optimal distribution time using subgraph complementations. We find a close to optimal sequence of subgraph complementation operations to distribute an arbitrary graph state, and establish upper bounds on distribution time along with providing approximate greedy algorithms.

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