qubit-discovery

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1.0.0 qubit_discovery-1.0.0-py3-none-any.whl

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Project: qubit-discovery
Version: 1.0.0
Filename: qubit_discovery-1.0.0-py3-none-any.whl
Download: [link]
Size: 38738
MD5: 76d9a785f4c580c125d4436accd8ecfa
SHA256: 46ce978c9bd49f61eef35f3194068af0e05c9e8a4ce66d8291b57b61f93938ee
Uploaded: 2024-08-26 08:47:56 +0000

dist-info

METADATA

Metadata-Version: 2.1
Name: qubit-discovery
Version: 1.0.0
Summary: Tools to optimize superconducting circuits using SQcircuit.
Author-Email: Taha Rajabzadeh <tahar[at]stanford.edu>, Alex Boulton-McKeehan <mckeehan[at]stanford.edu>, Sam Bonkowsky <sbonkov[at]ucsb.edu>, Amir Safavi-Naeini <safavi[at]stanford.edu>
Project-Url: Homepage, https://github.com/stanfordLINQS/Qubit-Discovery
License: BSD 3-Clause License Copyright (c) 2024, Taha Rajabzadeh, Alex Boulton-McKeehan, Sam Bonkowsky, and Amir Safavi-Naeini Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Keywords: superconducting circuits,superconducting qubits,machine learning,pytorch
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Requires-Dist: numpy (>=1.23)
Requires-Dist: torch (>=2.0)
Requires-Dist: scipy (>=1.10)
Requires-Dist: SQcircuit (>=1.0.0)
Requires-Dist: dill (==0.3.8)
Requires-Dist: matplotlib (>=3.7.2)
Requires-Dist: tqdm (>=4.60.0)
Requires-Dist: docopt; extra == "scripts"
Requires-Dist: pyyaml; extra == "scripts"
Requires-Dist: pytest (>7.4); extra == "tests"
Provides-Extra: scripts
Provides-Extra: tests
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 1471 characters]

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top_level.txt

qubit_discovery