Among the embodiments disclosed herein are variants of the quantum approximate optimization algorithm with different parametrization. In particular embodiments, a different objective is used: rather than looking for a state which approximately solves an optimization problem, embodiments of the disclosed technology find a quantum algorithm that will produce a state with high overlap with the optimal state (given an instance, for example, of MAX-2-SAT). In certain embodiments, a machine learning approach is used in which a “training set” of problems is selected and the parameters optimized to produce large overlap for this training set. The problem was then tested on a larger problem set. When tested on the full set, the parameters that were found produced significantly larger overlap than optimized annealing times. Testing on other random instances (e.g., from 20 to 28 bits) continued to show improvement over annealing, with the improvement being most notable on the hardest problems. Embodiments of the disclosed technology can be used, for example, for near-term quantum computers with limited coherence times.
Claim CLM-00001. 1. A method of operating a quantum computing device, comprising:
causing a quantum computing device to evolve from a first state to a second state according to a schedule that is neither annealing nor adiabatic, the first state corresponding to a first Hamiltonian, the second state corresponding to a second Hamiltonian, wherein the schedule includes an X schedule for Hamiltonian terms in the X basis, and a Z schedule for Hamiltonian terms in the Z basis, and wherein the schedule is nonlinear or piecewise linear in the X schedule, the Z schedule, or both the X schedule and the Z schedule.
Claim CLM-00012. 12. A method, comprising:
generating a learned schedule for controlling a quantum computing device by performing a schedule-training process beginning from an initial schedule, wherein the initial schedule includes an initial X schedule for Hamiltonian terms in the X basis and an initial Z schedule for Hamiltonian terms in the Z basis.
Claim CLM-00020. 20. A system, comprising:
a processor; and at least one memory coupled to the processor and having stored thereon processor-executable instructions for:
generating a schedule that is neither annealing nor adiabatic for controlling a quantum computing device by performing a schedule-training process beginning from an initial schedule; andcausing a quantum computing device to evolve from a first state to a second state according to the schedule, the first state corresponding to a first Hamiltonian, the second state corresponding to a second Hamiltonian,wherein the schedule includes an X schedule for Hamiltonian terms in the X basis, and a Z schedule for Hamiltonian terms in the Z basis, andwherein the schedule is nonlinear or piecewise linear in one or both of the X schedule or the Z schedule.
