2018/10/31 by Mark Fingerhuth, Tomáš Babej, Fingerhuth, Mark +3 · 4 citations
Computer Science · #Advanced Data Storage Technologies #Algorithms and Data Compression #FOS: Physical sciences #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.1810.13411
openalex publication_date 2018/10/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Gate-based universal quantum computers form a rapidly evolving field of quantum computing hardware technology. In previous work, we presented a quantum algorithm for lattice protein folding on a cubic lattice, tailored for quantum annealers. In this paper, we introduce a novel approach for solving the lattice protein folding problem on universal gate-based quantum computing architectures. Lattice protein models are coarse-grained representations of proteins that have been used extensively over the past thirty years to examine the principles of protein folding and design.These models can be used to explore a vast number of possible protein conformations and to infer structural properties of more complex atomistic protein structures. We formulate the problem as a quantum alternating operator ansatz, a member of the wider class of variational quantum/classical hybrid algorithms. To increase the probability of sampling the ground state, we propose splitting the optimization problem into hard and soft constraints. This enables us to use a previously under-utilised component of the variational algorithm to constrain the search to the subspace of solutions that satisfy the hard constraints.