This is a repo for constructing customized annealing schedules for flux qubits. The paper at arXiv:2103.06461 details the theory and methods that were used in this codebase.
First clone the repo using git clone , which copies all the contents of this package into a directory on your system.
Next go to the repo directory, e.g., using cd CAS.
Then run pip install . to install this package. You can also use pip install -e . to install the package in the 'editable' mode, which allows you to edit the source code and makes the changes immediately available for your use.
Before using the pip install, it is strongly recommended to create an isolated virtual environment and install the package in that environment.
For instructions on creating python virtual environments, please see this article
It contains modules that can simulate the circuit model for Capacitively Shunted FLux Qubits (CSFQ) and tunable inductive couplers. It can then construct a circuit containing multiple CSFQs and tunable couplers that are coupled together.
For these circuits, the code can calculate the Pauli coefficients of the effective qubit models given a set of circuit magnetic fluxes. It can also calculate circuit magnetic biases that yield a given customized annealing schedule. For small circuits (depending on computer memory, typically 4 qubits and 4 couplers) the code can calculate the above using the full Schrieffer–Wolff (SW) method. For larger circuits, the code uses a pairwise-SW approximation to find the circuit biases and Pauli schedules.
The examples directory contains jupyter example notebooks that explain how different methods of the module are used. The examples/cas_paper directory includes the notebooks that were used to make the figures and plots of the paper at arXiv:2103.06461.
Fork the repo for yourself, create a branch associated to your specific issue on your forked repo, push your changes to that branch, and then create a pull request to be merged onto the main repo.
If you use this code in your research, please cite its paper.