Quantum Optimal Control and its Applications to Shaken Lattice Interferometry and Superconducting Qubits
Shao, Jieqiu
Quantum optimal control is an important technology that enables fast state preparationand gate design. In the absence of an analytic solution, most quantum optimal control methods rely on an iterative scheme to update the solution estimate. At present, the convergence rate of existing solvers is, at most, superlinear. In this thesis, we develop a new general purpose solver for quantum optimal control, Quantum PRojection Operator-based Newton method for Trajectory Optimization (Q-PRONTO). Specifically, the proposed approach uses a projection operator to incorporate the Schr¨odinger equation directly into the cost function, which is then minimized using a Newton descent method. The resulting method guarantees monotonic convergence at every iteration and quadratic convergence in proximity of the solution. We then implement the method to different quantum applications: the first application is shaken lattice interferometry, which is a novel atom-based interferometry for quantum sensing; the second application is fluxonium qubit, which is a novel superconducting qubit for quantum computing. The potential of Q-PRONTO is showcased by computing an interferometry sequence for shaken lattice interferometry and designing a quantum gate for fluxonium qubit. The encouraging simulation results represent a first step in the development of a new paradigm for both quantum sensing and quantum computing.
•Jun 25, 2024•0 citations