Swap Network Augmented Ansätze on Arbitrary Connectivity

• URL: http://arxiv.org/abs/2507.23679v2
• Date: Fri, 01 Aug 2025 08:34:09 GMT
• Title: Swap Network Augmented Ansätze on Arbitrary Connectivity
• Authors: Teodor Parella-Dilmé, Jakob S. Kottmann, Antonio Acín,
• Abstract summary: We introduce an algorithm that optimize qubit routing for arbitrary connectivity graphs, resulting in a swap network that enables direct interactions between any pair of qubits.<n>We then propose a co-design of circuit layers and qubit routing by embedding the derived swap networks within layered, connectivity-aware ans"atze.<n>This construction significantly improves the trainability of the ansatz, leading to enhanced performance with reduced resources.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Efficient parametrizations of quantum states are essential for trainable hybrid classical-quantum algorithms. A key challenge in their design consists in adapting to the available qubit connectivity of the quantum processor, which limits the capacity to generate correlations between distant qubits in a resource-efficient and trainable manner. In this work we first introduce an algorithm that optimizes qubit routing for arbitrary connectivity graphs, resulting in a swap network that enables direct interactions between any pair of qubits. We then propose a co-design of circuit layers and qubit routing by embedding the derived swap networks within layered, connectivity-aware ans\"atze. This construction significantly improves the trainability of the ansatz, leading to enhanced performance with reduced resources. We showcase these improvements through ground-state simulations of strongly correlated systems, including spin-glass and molecular electronic structure models. Across exemplified connectivities, the swap-enhanced ansatz consistently achieves lower energy errors using fewer entangling gates, shallower circuits, and fewer parameters than standard layered-structured baselines. Our results indicate that swap network augmented ans\"atze provide enhanced trainability and resource-efficient design to capture complex correlations on devices with constrained qubit connectivity.

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