Efficient Hamiltonian programming in qubit arrays with nearest-neighbor couplings

We consider the problem of selectively controlling couplings in a practical quantum processor with always-on Ising interactions that are diagonal in the computational basis, using sequences of local not gates. This methodology is well known in nuclear magnetic resonance implementations, but previous approaches do not scale efficiently for the general fully connected Hamiltonian, where the complexity of finding time-optimal solutions makes them only practical up to a few tens of qubits. Given the rapid growth in the number of qubits in cutting-edge quantum processors, it is of interest to investigate the applicability of this control scheme to much larger-scale systems with realistic restrictions on connectivity. Here we present an efficient scheme to find near time-optimal solutions that can be applied to engineered qubit arrays with local connectivity for any number of qubits, indicating the potential for practical quantum computing in such systems. We will discuss the application of this scheme in realistic devices.