Integrator for Python-based quantum computing software
Project description
scikit-quant is an aggregator package to improve interoperability between quantum computing software packages. Our first focus in on classical optimizers, making the state-of-the art from the Applied Math community available in Python for use in quantum computing.
Full documentation: https://scikit-quant.readthedocs.io/
Website: http://scikit-quant.org
Installation
pip install sckit-quant
Usage
Basic example (component interfaces for standard quantum programming frameworks and for SciPy are available as well):
# create a numpy array of bounds, one (low, high) for each parameter bounds = np.array([[-1, 1], [-1, 1]], dtype=float) # budget (number of calls, assuming 1 count per call) budget = 40 # initial values for all parameters x0 = np.array([0.5, 0.5]) # method can be ImFil, SnobFit, Orbit, or Bobyqa result, history = \ minimize(objective_function, x0, bounds, budget, method='imfil')
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