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.


Features introduced before October 2018 are not listed here.

2020-10-21 Leap Release

SAPI Returns Correct Estimate of Solver Load

This release fixes the returned value for a solver’s recent average load, avg_load. When queried for a solver, SAPI returns estimates of how busy each solver was in the recent past, which enables client software such as Ocean’s cloud-client to prefer solvers that are less busy. You can see this estimate, provided at the time of selection, for an Ocean sampler:

>>> from dwave.system import DWaveSampler
>>> sampler = DWaveSampler()
>>> sampler.solver.avg_load

An error introduced in late 2019 caused SAPI to always return a value of 1.0.

2020-10-7 Leap Release

Hybrid Solver Service: DQM Solver

Leap 2 introduced the Leap™ hybrid solver service (HSS), which provides cloud-based quantum-classical hybrid solvers. 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.

Until this release, you could submit problems formulated as arbitrarily structured binary quadratic models (BQMs). This release introduces a discrete quadratic model (DQM) solver for problems with variables that that represent a set of values such as {red, green, blue, yellow} or {3.2, 67}. The first online DQM solver is hybrid_discrete_quadratic_model_v1. It accepts problems with up to 5,000 discrete variables, each of which can represent sets of up to 10,000 values, and 2 billion total linear plus quadratic biases (values assigned to both nodes and edges of the graph representing your problem).

Submit problems to the hybrid DQM solver as you would submit any BQM-formulated problem; in Ocean software use dwave-system tool’s LeapHybridDQMSampler.

For details on the solver, see Using Leap’s Hybrid Solvers.

2020-09-29 Leap Release: Advantage

Advantage™ General Availability

With this release, D-Wave’s new quantum computer, Advantage, becomes generally available to users with Leap and Amazon Braket accounts.

Advantage is the first and only quantum system designed for business and is the most powerful and connected commercial quantum computer in the world. With more than 5000 qubits and 35,000 couplers, Advantage gives users the ability to solve larger, more complex problems, both directly on the quantum processing unit (QPU) and indirectly by using Leap’s hybrid solvers, and drive real-world value for their businesses.

Advantage QPUs are named Advantage_system<x.y>, with x numbering solver (D-Wave system) resources[#] and y possibly incrementing on updates such as newer calibrations; for example, the first online QPU is Advantage_system1.1 with backup provided by Advantage_system2.1.

[1]Because Ocean software provides postprocessing tools such as dwave-greedy in lieu of online (server-side) postprocessing, Virtual Full-Yield Chip Solver (VFYC) resources are not supported for the Advantage.

You can learn about the Advantage QPU’s Pegasus topology in the Getting Started with the D-Wave System guide and in Leap’s new Exploring the Pegasus Topology Jupyter Notebook, which also demonstrates relevant Ocean tools and gives an example of setting different chain strengths[1] for problems submitted to Advantage and D-Wave 2000Q QPUs.

[2]When running on the Advantage problems previously configured for a D-Wave 2000Q, you should adjust the chain_strength parameter because chains are typically shorter on the Advantage. For an example, see Using the Problem Inspector, which uses Ocean’s problem inspector tool to illustrate the benefit of using an appropriate chain strength.

By default, if you do not specify selection criteria for a QPU, Ocean gives preference to Advantage over D-Wave 2000Q solvers[2].

[3]You can explicitly select a D-Wave 2000Q solver; for example, sampler = EmbeddingComposite(DWaveSampler(solver={'topology__type': 'chimera'})).

Leap’s Hybrid Solvers: Enhanced BQM Solver

Hybrid portfolio solvers, which in parallel to QPU processing run a variety of classical algorithms, are suited to a wide range of binary quadratic model (BQM) problems.

D-Wave’s hybrid solver service released its first hybrid portfolio solver, hybrid_v1, on February 26. That solver accepts problems of up to 10,000 variables and makes use of the D-Wave 2000Q for quantum acceleration.

This release supports an enhanced version of this solver, hybrid_binary_quadratic_model_version2, which uses stronger algorithms, exploits the more powerful Advantage QPU, and accepts larger problems. You can now submit problems with up to 1 million variables, or 200 million total linear plus quadratic biases (values assigned to both nodes and edges of the graph representing your problem).


Fig. 111 Problem size comparison: hybrid_binary_quadratic_model_version2 versus hybrid_v1.

For more information, see Technical Report 4-1048A-A.

2020-08-12 Amazon Braket Release

Access to D-Wave Quantum Computers via Amazon Braket

Access to D-Wave quantum computers is now also possible through Amazon Braket, a fully managed Amazon Web Services (AWS) service.

2020-07-29 Leap Release

Documentation Enhancement: Pegasus

This release updates the system documentation with descriptions of the new QPU topology, Pegasus, in advance of the upcoming release of D-Wave’s new Advantage™ quantum computer.

As of July 2020, users do not yet have access to an Advantage system. However, if you wish to familiarize yourself with the new topology, see the chapter on QPU topologies in Getting Started with the D-Wave System. See also the Pegasus functionality of Ocean tools under dwave_networkx.

Qubist Display of Problems Status

This release updates the presentation of the status of submitted problems in the Qubist user interface: by default, problems from the last day are displayed. Previously results were not filtered by date.

2020-07-15 Leap Release

Leap Expands to India and Australia

As of July 20 2020, users from India and Australia who are interested in real-time access to a commercial quantum computer can sign up for the Leap™ quantum cloud service. This expansion brings the total number of supported countries to 37, in North America, Europe and Asia-Pacific.

Access Leap™ here: https://cloud.dwavesys.com/leap.

Project Managers Can Now Administer Quota

Customers with a D-Wave “project manager” role for the systems used by their organization can now administer their own project’s user quota without having to go through D-Wave Support. Project managers can manage quota via the Qubist user interface: select Admin > Manage Quota to do so.

2020-06-17 Leap Release

Hybrid Solver Service: Increased Problem Size

This release increases the maximum size of problems you can upload to the Leap™ hybrid solver service (HSS) from 2 GB to 40 GB.

Note for users of the hybrid_v1 solver: this change does not enable increases to problem size for this solver, which continues to accept problems of up to 10,000 variables.

For uploading large problems in in multiple parts, see Solver API REST Web Services Developer Guide.

2020-06-03 Leap Release

SAPI Sets Default Timing Information

This release sets default values of zero (0) in all timing fields returned from a D-Wave system for non-executed problems; for example, an Ising problem with empty input fields for both \(h\) and \(J\). Previously, SAPI returned an empty dict.

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:

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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