Construction of model Hamiltonians for adiabatic quantum computation and its application tofinding low-energy conformations of lattice protein models

摘要

In this paper we explore the use of a quantum optimization algorithm for obtaining low-energy conforma-tions of protein models. We discuss mappings between protein models and optimization variables, which are inturn mapped to a system of coupled quantum bits. General strategies are given for constructing Hamiltoniansto be used to solve optimization problems of physical, chemical, or biological interest via quantum computa-tion by adiabatic evolution. As an example, we implement the Hamiltonian corresponding to the hydrophobic-polar model for protein folding. Furthermore, we present an approach to reduce the resulting Hamiltonian totwo-body terms gearing toward an experimental realization.