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Exploring adiabatic quantum computing trajectories via optimal control

Constantin Brif, Sandia National Laboratories

(Session 6a : Friday from 2:00 - 2:30)

Abstract. Adiabatic quantum computation (AQC) employs a slow change of the Hamiltonian, which helps keeping the system in the instantaneous ground state. When the evolution time is finite, dynamic trajectories corresponding to different forms of time-dependent control function(s) will result in different degrees of adiabaticity (quantified as the average ground state population during evolution). We employ optimal control methods to search for control functions that achieve the target final state while simultaneously maximizing the degree of adiabaticity. Exploring properties of optimal AQC trajectories in model systems elucidates dynamic mechanisms that minimize unwanted excitations from the ground state.