Protein folding with an all-to-all trapped-ion quantum computer
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913889013202944 |
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| author | Romero, Sebastián V. Cadavid, Alejandro Gomez Nikačević, Pavle Solano, Enrique Hegade, Narendra N. Lopez-Ruiz, Miguel Angel Girotto, Claudio Yamada, Masako Barkoutsos, Panagiotis Kl. Kaushik, Ananth Roetteler, Martin |
| author_facet | Romero, Sebastián V. Cadavid, Alejandro Gomez Nikačević, Pavle Solano, Enrique Hegade, Narendra N. Lopez-Ruiz, Miguel Angel Girotto, Claudio Yamada, Masako Barkoutsos, Panagiotis Kl. Kaushik, Ananth Roetteler, Martin |
| contents | We experimentally demonstrate that the bias-field digitized counterdiabatic quantum optimization (BF-DCQO) algorithm, implemented on IonQ's fully connected trapped-ion quantum processors, offers an efficient approach to solving dense higher-order unconstrained binary optimization (HUBO) problems. Specifically, we tackle protein folding on a tetrahedral lattice for up to 12 amino acids, representing the largest quantum hardware implementations of protein folding problems reported to date. Additionally, we address MAX 4-SAT instances at the computational phase transition and fully connected spin-glass problems using all 36 available qubits. Across all considered cases, our method consistently achieves optimal solutions, highlighting the powerful synergy between non-variational quantum optimization approaches and the intrinsic all-to-all connectivity of trapped-ion architectures. Given the expected scalability of trapped-ion quantum systems, BF-DCQO represents a promising pathway toward practical quantum advantage for dense HUBO problems with significant industrial and scientific relevance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_07866 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Protein folding with an all-to-all trapped-ion quantum computer Romero, Sebastián V. Cadavid, Alejandro Gomez Nikačević, Pavle Solano, Enrique Hegade, Narendra N. Lopez-Ruiz, Miguel Angel Girotto, Claudio Yamada, Masako Barkoutsos, Panagiotis Kl. Kaushik, Ananth Roetteler, Martin Quantum Physics We experimentally demonstrate that the bias-field digitized counterdiabatic quantum optimization (BF-DCQO) algorithm, implemented on IonQ's fully connected trapped-ion quantum processors, offers an efficient approach to solving dense higher-order unconstrained binary optimization (HUBO) problems. Specifically, we tackle protein folding on a tetrahedral lattice for up to 12 amino acids, representing the largest quantum hardware implementations of protein folding problems reported to date. Additionally, we address MAX 4-SAT instances at the computational phase transition and fully connected spin-glass problems using all 36 available qubits. Across all considered cases, our method consistently achieves optimal solutions, highlighting the powerful synergy between non-variational quantum optimization approaches and the intrinsic all-to-all connectivity of trapped-ion architectures. Given the expected scalability of trapped-ion quantum systems, BF-DCQO represents a promising pathway toward practical quantum advantage for dense HUBO problems with significant industrial and scientific relevance. |
| title | Protein folding with an all-to-all trapped-ion quantum computer |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2506.07866 |