What is SQcircuit? | Installation | Documentation | Examples | Contribution
⚠️ Note: SQcircuit is compatible with QuTip versions 5.0 and above.
SQcircuit is an open-source Python package designed to facilitate the analysis and optimization of arbitrary superconducting quantum circuits. Developed by researchers at Stanford University, SQcircuit provides a comprehensive framework to model, analyze, and optimize quantum circuits by constructing and diagonalizing their Hamiltonian from physical descriptions and efficient basis construction. This package supports the calculation of key circuit properties such as energy spectra, coherence times, transition matrix elements, coupling operators, and phase coordinate representations of eigenfunctions. With the integration of automatic differentiation capabilities using PyTorch, SQcircuit enables efficient computation of gradients for all the mentioned properties and custom-made loss functions, making it a powerful tool for optimizing superconducting quantum circuits.
The detailed theory behind the SQcircuit core code and an introduction to the library's functionalities are provided in the following paper:
Taha Rajabzadeh, Zhaoyou Wang, Nathan Lee, Takuma Makihara, Yudan Guo, Amir H. Safavi-Naeini,
Analysis of arbitrary superconducting quantum circuits accompanied by a Python package: SQcircuit,
Quantum 7, 1118,
https://quantum-journal.org/papers/q-2023-09-25-1118/
Additionally, the theory details, including examples of using auto-differentiation capabilities and gradient calculations, are thoroughly explained in the following paper:
Taha Rajabzadeh, Alex Boulton-McKeehan, Sam Bonkowsky, David I. Schuster, Amir H. Safavi-Naeini,
A General Framework for Gradient-Based Optimization of Superconducting Quantum Circuits using Qubit Discovery as a Case Study, arXiv:2408.12704 (2024),
https://arxiv.org/abs/2408.12704
For Python above 3.6, SQcirucit can be simply installed via Conda:
conda install -c conda-forge sqcircuit
Alternatively, installation via pip is also provided. (Note that installing pip under Conda environment is not recommended.)
pip install SQcircuit
The documentation of the SQcircuit is provided at: sqcircuit.org
To show the potential of SQcircuit for analyzing the arbitrary superconducting quantum circuits, we have provided variety of examples from state-of-the-art circuits in the literature at:
The source of Jupyter notebook examples can be found at:
https://github.com/stanfordLINQS/SQcircuit-examples
You are very welcome to contribute to SQcircuit development by forking this repository and sending pull requests, or filing bug reports at the issues page. All code contributions are acknowledged in the contributors' section in the documentation.