https://github.com/dwavesystems/dwave-hybrid
Hybrid Asynchronous Decomposition Sampler prototype framework.
https://github.com/dwavesystems/dwave-hybrid
quantum-computing
Last synced: 3 months ago
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Hybrid Asynchronous Decomposition Sampler prototype framework.
- Host: GitHub
- URL: https://github.com/dwavesystems/dwave-hybrid
- Owner: dwavesystems
- License: apache-2.0
- Created: 2018-08-03T06:15:19.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2025-03-26T11:30:28.000Z (10 months ago)
- Last Synced: 2025-10-02T16:36:07.865Z (4 months ago)
- Topics: quantum-computing
- Language: Python
- Homepage: https://docs.dwavequantum.com/en/latest/ocean/api_ref_hybrid/
- Size: 20.8 MB
- Stars: 88
- Watchers: 13
- Forks: 51
- Open Issues: 29
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
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README
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============
dwave-hybrid
============
.. start_hybrid_about
A general, minimal Python framework for building hybrid asynchronous
decomposition samplers for quadratic unconstrained binary optimization (QUBO)
problems.
*dwave-hybrid* facilitates three aspects of solution development:
* Hybrid approaches to combining quantum and classical compute resources
* Evaluating a portfolio of algorithmic components and problem-decomposition
strategies
* Experimenting with workflow structures and parameters to obtain the best
application results
The framework enables rapid development and insight into expected performance
of productized versions of its experimental prototypes.
Your optimized algorithmic components and other contributions to this project
are welcome!
.. end_hybrid_about
Installation or Building
========================
Install from a package on PyPI::
pip install dwave-hybrid
or from source in development mode::
git clone https://github.com/dwavesystems/dwave-hybrid.git
cd dwave-hybrid
pip install -e .
Testing
=======
Install test requirements and run ``unittest``::
pip install -r tests/requirements.txt
python -m unittest
Example
=======
.. start_hybrid_example
.. code-block:: python
import dimod
import hybrid
# Construct a problem
bqm = dimod.BinaryQuadraticModel({}, {'ab': 1, 'bc': -1, 'ca': 1}, 0, dimod.SPIN)
# Define the workflow
iteration = hybrid.RacingBranches(
hybrid.InterruptableTabuSampler(),
hybrid.EnergyImpactDecomposer(size=2)
| hybrid.QPUSubproblemAutoEmbeddingSampler()
| hybrid.SplatComposer()
) | hybrid.ArgMin()
workflow = hybrid.LoopUntilNoImprovement(iteration, convergence=3)
# Solve the problem
init_state = hybrid.State.from_problem(bqm)
final_state = workflow.run(init_state).result()
# Print results
print("Solution: sample={.samples.first}".format(final_state))
.. end_hybrid_example
Documentation
=============
Documentation for latest stable release included in Ocean is available
`here `_.
License
=======
Released under the Apache License 2.0. See ``_ file.
Contributing
============
Ocean's `contributing guide `_
has guidelines for contributing to Ocean packages.