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.
@article{arxiv.2506.07866,
title = {Protein folding with an all-to-all trapped-ion quantum computer},
author = {Sebastián V. Romero and Alejandro Gomez Cadavid and Pavle Nikačević and Enrique Solano and Narendra N. Hegade and Miguel Angel Lopez-Ruiz and Claudio Girotto and Masako Yamada and Panagiotis Kl. Barkoutsos and Ananth Kaushik and Martin Roetteler},
journal= {arXiv preprint arXiv:2506.07866},
year = {2025}
}