Advantage for Discrete Variational Quantum Algorithms in Circuit Recompilation
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914070591963136 |
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| author | Kyriienko, Oleksandr Umeano, Chukwudubem Holmes, Zoë |
| author_facet | Kyriienko, Oleksandr Umeano, Chukwudubem Holmes, Zoë |
| contents | The relative power of quantum algorithms, using an adaptive access to quantum devices, versus classical post-processing methods that rely only on an initial quantum data set, remains the subject of active debate. Here, we present evidence for an exponential separation between adaptive and non-adaptive strategies in a quantum circuit recompilation task. Our construction features compilation problems with loss landscapes for discrete optimization that are unimodal yet non-separable, a structure known in classical optimization to confer exponential advantages to adaptive search. Numerical experiments show that optimization can efficiently uncover hidden circuit structure operating in the regime of volume-law entanglement and high-magic, while non-adaptive approaches are seemingly limited to exhaustive search requiring exponential resources. These results indicate that adaptive access to quantum hardware provides a fundamental advantage. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_01154 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Advantage for Discrete Variational Quantum Algorithms in Circuit Recompilation Kyriienko, Oleksandr Umeano, Chukwudubem Holmes, Zoë Quantum Physics Neural and Evolutionary Computing The relative power of quantum algorithms, using an adaptive access to quantum devices, versus classical post-processing methods that rely only on an initial quantum data set, remains the subject of active debate. Here, we present evidence for an exponential separation between adaptive and non-adaptive strategies in a quantum circuit recompilation task. Our construction features compilation problems with loss landscapes for discrete optimization that are unimodal yet non-separable, a structure known in classical optimization to confer exponential advantages to adaptive search. Numerical experiments show that optimization can efficiently uncover hidden circuit structure operating in the regime of volume-law entanglement and high-magic, while non-adaptive approaches are seemingly limited to exhaustive search requiring exponential resources. These results indicate that adaptive access to quantum hardware provides a fundamental advantage. |
| title | Advantage for Discrete Variational Quantum Algorithms in Circuit Recompilation |
| topic | Quantum Physics Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2510.01154 |