Metadata-Version: 2.1
Name: scqubits
Version: 1.0.1
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: cython (>=0.28.5)
Requires: numpy (>=1.14.2)
Requires: scipy (>=1.1.0)
Requires: matplotlib (>=3.0.0)
Requires: qutip (>=4.3.1)
Requires: h5py (>=2.7.1)
Requires-Python: >=3.4
Requires-Dist: cython (>=0.28.5)
Requires-Dist: numpy (>=1.14.2)
Requires-Dist: scipy (>=1.1.0)
Requires-Dist: matplotlib (>=3.0.0)
Requires-Dist: qutip (>=4.3.1)
Requires-Dist: h5py (>=2.7.1)
Provides-Extra: graphics
Requires-Dist: matplotlib-label-lines (>=0.3.6) ; extra == 'graphics'


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.


