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Diverse Solutions (Archived Jupyter Notebook)

With the last previous-generation of D-Wave 2000Q quantum computer taken offline, only lower-noise D-Wave 2000Q quantum processing units (QPU) are available now in Leap. The Diverse Solutions Jupyter Notebook, which compared the two, has been archived here as a webpage that presents the output of a typical execution.

This notebook makes use of D-Wave's 2019 breakthrough in quantum device fabrication—its lower-noise technology for the quantum processing unit (QPU)—to provide some tools and demonstrate techniques that can help your quantum applications find better, more robust solutions to hard problems.

The D-Wave quantum computer solves binary quadratic models (BQM), the Ising model traditionally used in statistical mechanics and its computer-science equivalent, the quadratic unconstrained binary optimization (QUBO) problem. These formulations can express a wide range of hard optimization and constraint satisfaction problems, for example, such as job-shop scheduling, protein folding, and traffic-flow optimization.

For applications in such fields to be successful may require diverse solutions, which enable the application to respond to changes in the environment (problem conditions). Additionally, a diverse set of solutions may reflect and enable analysis of structural characteristics of the problem.

The notebook has the following sections:

  1. Lower-Noise QPU gives a basic explanation of what noise is reduced in newer-generation QPUs.
  2. Basic Solution Analysis shows some quick and simple ways to examine problem solutions.
  3. Analysis with Hamming Distance demonstrates a simple tool for analyzing solutions.
  4. Analysis with Autocorrelation explains a more powerful tool, autocorrelation, and demonstrates its use through a comparison of results between the newer and previous generation of QPUs.

License

See LICENSE file.