Logical Resource Estimation for Quantum State Preparation with Compilation
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866916024452907008 |
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| author | Liu, Diyi Wang, Hanyu Zhu, Shuchen Cong, Jason de Jong, Wibe A. Fang, Di Huang, Zhen Iancu, Costin Yang, Chao |
| author_facet | Liu, Diyi Wang, Hanyu Zhu, Shuchen Cong, Jason de Jong, Wibe A. Fang, Di Huang, Zhen Iancu, Costin Yang, Chao |
| contents | Quantum state preparation is a fundamental primitive in quantum algorithms for encoding classical data into quantum amplitudes. We compare the cost of preparing general $n$-qubit states with real amplitudes using two common paradigms: rotation-based methods, based on controlled rotations, and sampling-based methods, based on a structured representation of the target state. Although these approaches are often theoretically compared using CNOT count and $T$-count, their relative performance in total gate count remains less well understood practically. We compare representative rotation-based and sampling-based methods using $T$-count and total gate count, and analyze how compilation overhead affects their relative performance. We also develop a software package for compiling state preparation circuits, designed as a practical subroutine for more general quantum computations. Numerical experiments on resource states and quantum states related to quantum chemistry, condensed matter physics, and simulation via Magnus expansion over a range of target accuracies $ε$ support the analysis. Our results show that sampling-based methods achieve asymptotically lower $T$-count and retain an overall advantage after accounting for total gate count and compilation overhead. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2605_18877 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Logical Resource Estimation for Quantum State Preparation with Compilation Liu, Diyi Wang, Hanyu Zhu, Shuchen Cong, Jason de Jong, Wibe A. Fang, Di Huang, Zhen Iancu, Costin Yang, Chao Quantum Physics 81P68, 68Q12 Quantum state preparation is a fundamental primitive in quantum algorithms for encoding classical data into quantum amplitudes. We compare the cost of preparing general $n$-qubit states with real amplitudes using two common paradigms: rotation-based methods, based on controlled rotations, and sampling-based methods, based on a structured representation of the target state. Although these approaches are often theoretically compared using CNOT count and $T$-count, their relative performance in total gate count remains less well understood practically. We compare representative rotation-based and sampling-based methods using $T$-count and total gate count, and analyze how compilation overhead affects their relative performance. We also develop a software package for compiling state preparation circuits, designed as a practical subroutine for more general quantum computations. Numerical experiments on resource states and quantum states related to quantum chemistry, condensed matter physics, and simulation via Magnus expansion over a range of target accuracies $ε$ support the analysis. Our results show that sampling-based methods achieve asymptotically lower $T$-count and retain an overall advantage after accounting for total gate count and compilation overhead. |
| title | Logical Resource Estimation for Quantum State Preparation with Compilation |
| topic | Quantum Physics 81P68, 68Q12 |
| url | https://arxiv.org/abs/2605.18877 |