A quantum alternating operator ansatz with hard and soft constraints for lattice protein folding
Abstract
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.
- Publication:
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arXiv e-prints
- Pub Date:
- October 2018
- DOI:
- 10.48550/arXiv.1810.13411
- arXiv:
- arXiv:1810.13411
- Bibcode:
- 2018arXiv181013411F
- Keywords:
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- Quantum Physics
- E-Print:
- All three authors have contributed equally to this work, 12 pages, 8 figures