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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 trategies
- 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.
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