Metadata-Version: 2.1
Name: scqubits
Version: 3.0.0
Summary: scqubits: superconducting qubits in Python
Home-page: https://scqubits.readthedocs.io
Author: Jens Koch, Peter Groszkowski
Author-email: jens-koch@northwestern.edu, piotrekg@gmail.com
License: BSD
Keywords: superconducting qubits
Platform: Linux
Platform: Mac OSX
Platform: Unix
Platform: Windows
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: Microsoft :: Windows
Requires-Python: >=3.7
License-File: LICENSE
Requires-Dist: cycler
Requires-Dist: matplotlib (>=3.0.0)
Requires-Dist: numpy (>=1.14.2)
Requires-Dist: pyyaml
Requires-Dist: qutip (>=4.3.1)
Requires-Dist: scipy (>=1.1.0)
Requires-Dist: sympy
Requires-Dist: tqdm
Requires-Dist: typing-extensions
Provides-Extra: explorer
Requires-Dist: ipywidgets (>=7.5) ; extra == 'explorer'
Provides-Extra: fitting
Requires-Dist: lmfit ; extra == 'fitting'
Provides-Extra: graphics
Requires-Dist: matplotlib-label-lines (>=0.3.6) ; extra == 'graphics'
Provides-Extra: h5-support
Requires-Dist: h5py (>=2.10) ; extra == 'h5-support'
Provides-Extra: pathos
Requires-Dist: pathos ; extra == 'pathos'
Requires-Dist: dill ; extra == 'pathos'


scqubits is an open-source Python library for simulating superconducting qubits. It is
meant to give the user a convenient way to obtain energy spectra of common
superconducting qubits, plot energy levels as a function of external parameters,
calculate matrix elements etc. The library further provides an interface to QuTiP,
making it easy to work with composite Hilbert spaces consisting of coupled
superconducting qubits and harmonic modes. Internally, numerics within scqubits is
carried out with the help of Numpy and Scipy; plotting capabilities rely on
Matplotlib.

If scqubits is helpful to you in your research, please support its continued
development and maintenance. Use of scqubits in research publications is
appropriately acknowledged by citing:

Peter Groszkowski and Jens Koch, 'scqubits:  a Python package for superconducting qubits',
Quantum 5, 583 (2021). https://quantum-journal.org/papers/q-2021-11-17-583/
