# 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.

Note

Features introduced before October 2018 are not listed here.

## Summary¶

## 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
0.04
```

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).

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:

*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¶

## 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¶

## 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,

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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