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| Natura: | Preprint |
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2025
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| Accesso online: | https://arxiv.org/abs/2507.23679 |
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| _version_ | 1866917407712346112 |
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| author | Parella-Dilmé, Teodor Kottmann, Jakob S. Acín, Antonio |
| author_facet | Parella-Dilmé, Teodor Kottmann, Jakob S. Acín, Antonio |
| contents | 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 ansätze. 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 ansätze provide enhanced trainability and resource-efficient design to capture complex correlations on devices with constrained qubit connectivity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_23679 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Swap Network Augmented Ansätze on Arbitrary Connectivity Parella-Dilmé, Teodor Kottmann, Jakob S. Acín, Antonio Quantum Physics 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 ansätze. 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 ansätze provide enhanced trainability and resource-efficient design to capture complex correlations on devices with constrained qubit connectivity. |
| title | Swap Network Augmented Ansätze on Arbitrary Connectivity |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2507.23679 |