Learning quantum disentanglement scheduling from reduced states via modular hybrid policies
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917451175821312 |
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| author | Xiao, Y. -X. Han, J. -Z. Zheng, Z. Zhang, Z. -H. Xue, M. Li, J. Lv, X. |
| author_facet | Xiao, Y. -X. Han, J. -Z. Zheng, Z. Zhang, Z. -H. Xue, M. Li, J. Lv, X. |
| contents | Quantum control with restricted state access is central to near-term quantum devices, where full wave-function information is unavailable. We study this problem through multiqubit disentanglement scheduling from partial observations, where a controller receives only two-qubit reduced density matrices and selects which qubit pair to disentangle at each step. We introduce a modular hybrid quantum--classical policy framework consisting of classical preprocessing, a parameterized quantum circuit as a compact nonlinear latent block, and classical postprocessing for pair-selection probabilities. Benchmarking 4-, 5-, and 6-qubit tasks, we find that preprocessing is the dominant factor governing performance under reduced-state observations, while the quantum module provides a conditional compact representation whose utility depends on the input features and model budget. We further identify a performance--efficiency trade-off across policy families and find that increasing circuit width is generally more useful than increasing depth. These results provide practical design principles for hybrid policies in reduced-information quantum control. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_28009 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Learning quantum disentanglement scheduling from reduced states via modular hybrid policies Xiao, Y. -X. Han, J. -Z. Zheng, Z. Zhang, Z. -H. Xue, M. Li, J. Lv, X. Quantum Physics Quantum control with restricted state access is central to near-term quantum devices, where full wave-function information is unavailable. We study this problem through multiqubit disentanglement scheduling from partial observations, where a controller receives only two-qubit reduced density matrices and selects which qubit pair to disentangle at each step. We introduce a modular hybrid quantum--classical policy framework consisting of classical preprocessing, a parameterized quantum circuit as a compact nonlinear latent block, and classical postprocessing for pair-selection probabilities. Benchmarking 4-, 5-, and 6-qubit tasks, we find that preprocessing is the dominant factor governing performance under reduced-state observations, while the quantum module provides a conditional compact representation whose utility depends on the input features and model budget. We further identify a performance--efficiency trade-off across policy families and find that increasing circuit width is generally more useful than increasing depth. These results provide practical design principles for hybrid policies in reduced-information quantum control. |
| title | Learning quantum disentanglement scheduling from reduced states via modular hybrid policies |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2604.28009 |