ParameterizedQuantumControl.jl

Implementation of control methods for analytical parameterized control fields.

Part of QuantumControl.jl and the JuliaQuantumControl organization.

As usual, the package can be installed with

pkg> add ParameterizedQuantumControl

• Define a QuantumControl.ControlProblem that contains parameterized generators or control fields: get_parameters(problem) must return a vector of control parameters.

• Call QuantumControl.optimize using method=ParameterizedQuantumControl, and give an appropriate backend and optimizer, e.g.,

  optimize(
      problem;
      method=ParameterizedQuantumControl,
      backend=Optimization,
      optimizer=NLopt.LN_NELDERMEAD(),
  )
  

Currently, only Optimization.jl is supported as a backend, and only with gradient-free optimizers. In the future, this will be extended to gradient-based optimizers (i.e., the "GOAT" method), as well as specific pulse parametrizations (e.g., CRAB).

A minimal standalone documentation of ParameterizedQuantumControl.jl is available at https://juliaquantumcontrol.github.io/ParameterizedQuantumControl.jl.

For a broader perspective, see the documentation of the QuantumControl.jl package.