Quantum circuits constructed from Josephson junctions and superconducting electronics are key to many quantum computing and quantum optics applications. Designing these circuits involves calculating the Hamiltonian describing their quantum behavior. QuCAT, or “Quantum Circuit Analyzer Tool”, is an open-source framework to help in this task. This open-source Python library features an intuitive graphical or programmatical interface to create circuits, the ability to compute their Hamiltonian, and a set of complimentary functionalities such as calculating dissipation rates or visualizing current flow in the circuit. QuCAT currently supports quantization in the basis of normal modes.

How QuCAT works

For an overview of the circuit quantization method used by QuCAT and the algorithmic methods which implement it, go to our technical paper https://arxiv.org/pdf/1908.10342.pdf.


QuCAT is currently developped and maintained by Mario Gely in the group of Gary Steele at the University of Delft in the Netherlands.


Don’t hesitate to contact Mario at mario.gely@qucat.org


Your contribution is more than welcome! You can submit pull requests on our Github, or contact Mario if you want to bring big contributions to the project.

Possible extensions of the QuCAT features could include black-box impedance components to model distributed components [1], more precisely modeling lossy circuits [2], [3], handling static offsets in flux or charge through DC sources, additional elements such as coupled inductors or superconducting quantum interference devices (SQUIDS) and different quantization methods, enabling for example quantization in the charge or flux basis. The latter would extend QuCAT beyond the scope of weakly-anharmonic circuits.

In terms of performance, QuCAT would benefit from delegating analytical calculations to a more efficient, compiled language.

[1] arxiv.org/abs/1204.0587

[2] arxiv.org/abs/1403.7341

[3] arxiv.org/abs/1505.04116


This work is supported by the European Research Council under the European Union’s H2020 program with grant agreements 681476 - QOM3D and 732894 - HOT.