A Python module for smooth robust quantum control of periodic Hamiltonians.
The original author was Marcel Langer, who started this module as part of his Master's thesis. It is now maintained by Jake Lishman as part of the Imperial College London Controlled Quantum Dynamics group, and you can contact me at my Imperial email address jake.lishman16@imperial.ac.uk.
The theory behind this module can be found in Marcel's thesis, and in the paper Smooth optimal control with Floquet theory by Björn Bartels and Florian Mintert (arXiv, journal).
floq is not available through pip or conda, and must be installed
manually, by cloning the repository and adding the resulting directory to the
PYTHONPATH environment variable (or otherwise making the inner floq folder
visible to the Python search path).
The requirements are listed in the file requirements.txt in the root of the
repository. nose and mock are only required to run the tests, and are not
needed for a regular installation. floq suppports only Python 3.
If you have installed the test requirements, you can run them by navigating to
the folder that you cloned the repository into, and running nosetests. All
tests should pass.
The main use case of floq is to calculate the time-evolution operator for a
periodic Hamiltonian, and the evolution operators derivatives with respect to
both time and any parameters the Hamiltonian is a function of. The derivative
of the operator with respect to the controls allows us to use gradient-based
methods for optimal control.
There are a couple of examples in the examples/ folder, and there is more help
available in the docstrings of the code. Try calling help() on classes and
functions to find out more.
The base class is floq.System. This can be instantiated with just a
Hamiltonian (see the help() for details, and see Marcel's thesis for details
of the Fourier transformation), but the derivatives of the Hamiltonian can also
optionally be passed.