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.
Website: http://scikit-quant.org
Installation
pip install sckit-quant
Usage
Basic example:
# 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')
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
scikit-quant-0.5.0.tar.gz
(17.2 kB
view details)
File details
Details for the file scikit-quant-0.5.0.tar.gz.
File metadata
- Download URL: scikit-quant-0.5.0.tar.gz
- Upload date:
- Size: 17.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ff05fb5d0ed43a728e3e420f28419463f4a6bae2f3378ea711ac0124415a594e
|
|
| MD5 |
b8dce48ac63bc259ce58742ed6c312de
|
|
| BLAKE2b-256 |
65ec1684fd5763213be7a36be8dc57fd18bce8a13851e0bd6fa5b9ec4699a095
|
