Feature Descriptions

This section describes new features that affect the D-Wave system, including annealing features, changes to the Solver API, and significant additions to the Leap™ quantum cloud service.

Features are listed in date order, with the most recent first.

2020-02-26 Leap Release: Leap 2

Hybrid Solver Service

Leap 2 introduces the Leap™ hybrid solver service (HSS), which includes cloud-based quantum-classical hybrid solvers to which you can submit problems formulated as arbitrarily structured binary quadratic models (BQMs). These hybrid solvers, which implement state-of-the art classical algorithms together with intelligent allocation of the quantum processing unit (QPU) to parts of the problem where it benefits most, are designed to accommodate even very large problems. This first release of the HSS includes the hybrid_v1 solver that accepts problems of up to 10,000 variables. It is a portfolio solver, meaning that in parallel to QPU processing it runs a variety of classical algorithms, making it suited to a wide range of problems.

Submit problems to the hybrid solver as you would submit any BQM-formulated problem; from Ocean software’s dwave-system tool, use the new LeapHybridSampler.

See the Structural Imbalance in a Social Network example in the Ocean software documentation.

Online Integrated Developer Environment

Leap 2 introduces a new online integrated developer environment (IDE) as part of Leap. The Leap IDE provides a ready-to-code environment in the cloud for Python development. Accessible from your browser, it is configured with the latest Ocean SDK and includes the new D-Wave problem inspector and standard Python debugging tools. Seamless GitHub integration means that developers can easily access D-Wave’s latest code examples, develop quantum applications, and contribute to the Ocean tools from within the IDE. Powered by gitpod.io, the Leap IDE is customizable via a Docker file.

Problem Inspector

Leap 2 introduces a tool for visualizing problems submitted to, and answers received from, a D-Wave structured solver such as a D-Wave 2000Q quantum computer.

dwave-inspector provides a graphic interface for examining D-Wave quantum computers’ problems and answers. The D-Wave system solves problems formulated as BQMs that are mapped to its qubits in a process called minor-embedding. Because the way you choose to minor-embed a problem (the mapping and related parameters) affects solution quality, it can be helpful to see it.

See the Using the Problem Inspector example in the Ocean software documentation.

Integrated Examples

Leap 2 introduces a D-Wave code examples GitHub repository and its search page on the Leap website. This collection of examples already contains over a dozen examples, including examples of factoring, graph problems, feature selection, and more. The new page on the Leap website enables you to filter the examples by tags such as problem type, industry, and tags.

New Subscription Options

Leap 2 adds new Leap subscription options that enable you to upgrade your account for additional time in blocks that suit your need and budget. With the introduction of Hybrid Solver Service, subscriptions now provide access to D-Wave’s hybrid solvers as well as its QPUs.

Documentation Enhancements

Leap 2 updates the following system documents:

  • Solver API REST Web Services Developer Guide has been updated to support uploading of large problems in multiple parts.
  • Solver Properties and Parameters Reference has been updated to support Leap’s hybrid solvers.
  • Solver Computation Time has been renamed and updated to support Leap’s hybrid solvers.

The online system documentation now includes a “Using Leap’s Hybrid Solvers” section.

2020-12-11 Leap Release

New Solver Property: category

This release introduces a new solver property, category, that identifies the solver type; for example, qpu.

New Solver Property: quota_conversion_rate

This release introduces a new solver property, quota_conversion_rate, so you can see the rate at which a particular solver consumes user or project quota. Some solver types might consume quota at different rates.

2020-11-27 Leap Release

New Jupyter Notebook: Hybrid Computing

Try out the new Hybrid Computing Jupyter Notebook, which demonstrates how you can apply dwave-hybrid solvers to your problem, create hybrid workflows, and develop custom hybrid components.

Jupyter Notebooks are available online through Leap.

2019-08-07 Leap Release

More Flexible Anneal Schedules Now Possible

For the online systems, this release introduces more flexible parameters for generating anneal schedules. Specifically, you can now create an anneal schedule with up to 12 points in its waveform (the previous configured maximum was 4), and the annealing slope range is expanded to -1.0 to 1.0 (the previous configured range was 0.0 to 1.0). Furthermore, the anneal fractions need not increase monotonically, which means that sawtooth patterns are possible.

For more information on modifying the default anneal schedule, see Technical Description of the D-Wave Quantum Processing Unit.

2019-06-26 Leap Release

General Availability of D-Wave Hybrid

D-Wave Hybrid is now part of the Ocean SDK. D-Wave Hybrid provides a simple, open-source hybrid workflow platform for building and running quantum-classical hybrid applications.

Download the Ocean SDK

New Jupyter Notebook: Feature Selection

Try out the new Feature Selection Jupyter Notebook, which uses a hybrid sampler to showcase a machine learning technique. Jupyter Notebooks are available online through Leap.

2019-04-01 Leap Release

New Solver Property: tags

This release introduces a new solver property, tags, that may hold attributes about a solver that you can use to have a client program choose one solver over another.

For example, the following attribute identifies a solver as lower-noise:

"tags": ["lower_noise"]

2019-03-06 Leap Release

Time-Dependent Gain in Hamiltonian Biases

This release increases user control of the Hamiltonian that represents the D-Wave system’s quantum anneal by introducing a time-dependent gain on its linear coefficients.

The h_gain_schedule parameter described in the Solver Properties and Parameters Reference guide enables users to specify the \(g(t)\) function in,

\begin{equation} {\cal H}_{ising} = - \frac{A({s})}{2} \left(\sum_i {\hat\sigma_{x}^{(i)}}\right) + \frac{B({s})}{2} \left(\sum_{i} g(t) h_i {\hat\sigma_{z}^{(i)}} + \sum_{i>j} J_{i,j} {\hat\sigma_{z}^{(i)}} {\hat\sigma_{z}^{(j)}}\right) \end{equation}

where \({\hat\sigma_{x,z}^{(i)}}\) are Pauli matrices operating on a qubit \(q_i\) (the quantum one-dimensional Ising spin) and \(h_i\) and \(J_{i,j}\) the qubit biases and coupling strengths.

Currently this feature is used experimentally for a form of material simulation described in http://science.sciencemag.org/content/361/6398/162.

2018-10-02 Leap Release

Leap™ Launch

With this release, D-Wave launches Leap™ , our new quantum cloud service. Access it here: https://cloud.dwavesys.com/leap.

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