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

Table 79 Release Summary
Release Date Features
2021-12-01 Project Admins Can Modify the Solver-Access Time Simultaneously for Multiple Users
Improved Leap Admin Feature for Setting Solver-Access Time
Project Admins Can Copy Multiple Email Addresses From Excel to Invitations
Extended Invitation Period for Joining a Leap Project
Resolved Incorrect QPU Plots in Documentation
2021-11-17 Project Administrators Can Simultaneously Remove Multiple Users
Resolved: Usage Statistics Graph Displayed Incorrectly on Leap Dashboard
Advantage_system1.1 Solver Decommissioned
2021-11-03 Resolved: Leap Administration Not Resending Invitations
2021-10-20 Leap Supports Resources in Multiple Geographic Regions
Resolved Readout Fidelity Issue in Advantage_system4.1
2021-10-13 Resolved Issues Affecting Leap Administration
2021-10-05 Hybrid Solver Service: CQM Solver
Advantage Performance Update
2021-09-27 New Leap Administration Tool
Resolved Leap IDE Workspace Outage
Resolved: Problems Completed Panel in the Leap Dashboard is Overbroad
2021-09-08 Higher Resolution of Timing Properties, Parameters, and Fields
2021-08-25 Resolved DQM Solver Scaling Issue
Resolved QPU Access Time Issue in Leap Dashboard
Documentation Restructure: QPU Solver Datasheet
2021-06-16 Revision to Release Note for Leap’s DQM Solver
2021-05-05 Change to Orders and Billing Access via Leap
2021-05-05 Documentation Improvement: Updated Solver Properties and Parameters Guide
2021-04-21 Documentation Improvement: Updated Problem-Solving Handbook
Japanese Translation of Leap Cloud Subscription Agreement: Japan
2021-03-24 New Working Graph for Backup Advantage System
2021-03-10 Downloadable Privacy Policy and Terms & Conditions
2021-02-22 Leap Expands to Singapore
2021-02-10 Deprecated Timing Fields Removed from Solver API
Resolved Energy Offset Issue Affecting Some Hybrid Problems
Resolved MFA Email Issue
2021-01-27 Removed Statistics Panel on Leap’s Dashboard
Assign Problem Labels
2021-01-13 Terms and Conditions for Japanese Users of Leap
Resolved Incorrect Energies Returned by Hybrid Solver
2020-12-16 User Statistics Available on Leap’s Dashboard
2020-12-02 Problem Details Available on Leap’s Dashboard
Multiple-Project Support
2020-11-18 Solver Details Available on Leap’s Dashboard
2020-11-04 Resolved Failures on Version 2 of Hybrid BQM Solver
2020-10-21 SAPI Returns Correct Estimate of Solver Load
2020-10-07 Hybrid Solver Service: DQM Solver
2020-09-29 Advantage™ General Availability
Leap’s Hybrid Solvers: Enhanced BQM Solver
2020-08-13 Access to D-Wave Quantum Computers via Amazon Braket
2020-07-29 Documentation Enhancement: Pegasus
Qubist Display of Problems Status
2020-07-15 Leap Expands to India and Australia
Project Managers Can Now Administer Quota
2020-06-17 Hybrid Solver Service: Increased Problem Size
2020-06-03 SAPI Sets Default Timing Information
2020-02-26 (Leap 2 launch) Hybrid Solver Service
Online Integrated Developer Environment
Problem Inspector
Integrated Examples
New Subscription Options
2020-12-11 New Solver Property: quota_conversion_rate
New Solver Property: category
2020-11-27 New Jupyter Notebook: Hybrid Computing
2019-08-07 More Flexible Anneal Schedules Now Possible
2019-06-26 General Availability of D-Wave Hybrid
New Jupyter Notebook: Feature Selection
2019-04-01 New Solver Property: tags
2019-03-06 Time-Dependent Gain in Hamiltonian Biases
2018-10-02 (Leap launch) Leap™ Launch

2021-12-01 Leap Release

Project Admins Can Modify the Solver-Access Time Simultaneously for Multiple Users

With this release, project administrators can modify the solver-access time simultaneously for multiple users as follows:

  1. On the Users tab, select the users for which you want to modify their solver-access time.
  2. Select the Manage Selected > Modify solver access time menu and set the desired solver-access time.

For more information, see the Administration Guide.

Improved Leap Admin Feature for Setting Solver-Access Time

With this release, a new dialog box is available for setting solver-access time when inviting users or modifying the solver-access time of current members.

In this dialog box, in addition to setting a user’s solver-access time to a specific value, project administrators can also set the user’s solver-access time to the project’s entire solver-access time or its default for all members.

For more information, see the Administration Guide.

Project Admins Can Copy Multiple Email Addresses From Excel to Invitations

With this release, project administrators can copy and paste multiple email addresses from a single column in an Excel spreadsheet into the Email field of invitations.

Extended Invitation Period for Joining a Leap Project

Instead of expiring after 1 week, invitations to join a Leap project now expire after 2 weeks.

Resolved Incorrect QPU Plots in Documentation

The Energy (Joules) scale’s exponent for the annealing schedule plots in the following documents was incorrect. The plots have now been corrected.

2021-11-17 Leap Release

Project Administrators Can Simultaneously Remove Multiple Users

With this release, project administrators can simultaneously remove multiple users from a project in Leap Admin. To do this, perform the following:

  1. On the Users tab, select the users to remove.
  2. Select the Manage Selected > Remove from project menu.

For more information, see the Administration Guide.

Resolved: Usage Statistics Graph Displayed Incorrectly on Leap Dashboard

The following issue, present in the previous release of the Leap Dashboard pages, is now resolved:

  • Usage Statistics Graph May Be Displayed Incorrectly

Advantage_system1.1 Solver Decommissioned

Per the 5 November 2021 notification, the Advantage_system1.1 solver has been decommissioned and removed from Leap.

2021-11-03 Leap Release

Resolved: Leap Administration Not Resending Invitations

The following issue, present in the previous release of the Leap Admin pages, is now resolved:

  • Resend Invitation Does Not Work

2021-10-20 Leap Release

Leap Supports Resources in Multiple Geographic Regions

This release adds support for processing problems on solvers located in multiple regions, such as North America and Europe. Your customer contract determines the solvers that are available in your projects. The Leap Dashboard has been enhanced to organize solvers by region. In addition, the Leap IDE and Ocean have been enhanced to enable you to submit problems to solvers by region.

Resolved Readout Fidelity Issue in Advantage_system4.1

Some qubits on the Advantage_system4.1 QPU suffered a slight degradation in readout fidelity. This issue is now resolved.

2021-10-13 Leap Release

Resolved Issues Affecting Leap Administration

The following issues, present in the previous release of the Leap Admin pages, are now resolved:

  • Cannot edit Customer Reference ID field
  • Assign Project Admin menu missing
  • Adding email addresses to invitations fails due to mismatched letter casing

2021-10-05 Leap Release: Hybrid CQM Solver and Advantage Performance Update

This release adds the new quantum-classical hybrid CQM solver to the Leap™ hybrid solver service and makes generally available a first system with the Advantage performance update.

Hybrid Solver Service: CQM Solver

Leap’s February 26, 2020 release introduced Leap’s 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) and discrete quadratic models (DQMs). This release introduces a constrained quadratic model (CQM) solver that accepts problems with binary and integer variables and one or more constraints. In contrast to previous hybrid solvers, which required that you represent any problem constraints as penalty models in your objective, the CQM solver natively supports equality and inequality constraints. To enable formulating such quadratic models with convenient notation, Ocean now supports symbolic math.

The first online CQM solver is hybrid_constrained_quadratic_model_v1. It accepts problems with up to 5,000 variables, each of which can represent binary or integer values, 750 million total linear plus quadratic biases (values assigned to both nodes and edges of the graph representing your problem), and 100,000 constraints.[1]

Submit problems to the hybrid CQM solver as you would submit any BQM-formulated problem; in Ocean software use dwave-system tool’s LeapHybridCQMSampler. Example CQM problems are available in the documentation and in Ocean software’s collection of code examples on GitHub.

For details on hybrid solvers, see Using Leap’s Hybrid Solvers. For performance information on the new hybrid CQM solver, see the Technical Report 14-1055A document.

[1]Contact D-Wave at sales@dwavesys.com if your application requires scale or performance that exceeds the currently advertised capabilities of Leap’s generally available hybrid solvers.

Advantage Performance Update

This release brings online the Advantage_system4.1 system that includes several enhancements to D-Wave’s quantum processing unit (QPU) technology:

For detailed QPU performance information (for example, numerical analyses on performance for clique and SAT problems), see the Technical Report 14-1054A document, which is now updated for the latest Advantage system.

Higher Yield

The working graph of a QPU is the subset of the Pegasus (or Chimera for D-Wave 2000Q systems) graph available to users[2]; The yield of the working graph is the percentage of working qubits that are present. Advantage QPUs are fabricated with 5,640 qubits connected in the Pegasus architecture by 40,484 couplers. Yield substantially affects problem embedding.

Previous Advantage QPUs had between 5,436 to 5,567 available qubits, providing working-graph yields of 96% to 98.7%. Crucially, previous yields for couplers were 92% to 97.4%. The Advantage_system4.1 system has a yield of 99.7% (5,627 qubits) with 99.4% of couplers (40,279) available for use. This increased yield greatly improves performance of embedding; for example, the largest clique (fully connected graph) that has been successfully embedded has grown from 119 to 177 nodes (with chain length of 17 qubits[3]).

[2]
For more information about QPU topologies and working graphs, see the D-Wave QPU Architecture: Topologies chapter of the Getting Started with D-Wave Solvers guide.
[3]Chains of such great length (17-qubit chains here) typically do not perform well for many problems. Depending on your problem, you might need to limit your chains to significantly shorter lengths.

Lower ICE

Integrated control errors (ICE) can limit the dynamic range of \(h\) and \(J\) values and include the main sources of infidelity in problem representation. The newest Advantage QPU exploits enhanced fabrication capabilities that reduce variations across its more than a million Josephson junctions. Additional design improvements enable more accurate programming of the values of qubit biases and coupling strengths that represent the linear and quadratic coefficients, respectively, of submitted objective functions. Consequently, solutions returned from newer QPUs—such as that in the Advantage_system4.1 system—have relatively lower errors and better scaling for problems.

Expanded Range of QPU Biases

This release expands the range of biases you can set on Advantage QPUs from the current nominal value of [-2.0, 2.0] to a nominal value of [-4.0, 4.0] (check the h_range property for your QPU solver for exact values).

The range of supported h biases of a QPU, as defined in the h_range property, determines the mapping from your problem’s linear coefficients to values of physical qubit biases (external magnetic fields applied to qubits that control probabilities of the qubits ending an anneal in 0 or 1 states). Typically, this mapping is handled automatically; however, if you turn off the auto_scale parameter, you map these yourself.

Doubling this range means that problems with diverse values of linear coefficients are more accurately represented (see the discussion on integrated control errors, ICE, in the QPU Solver Datasheet guide) and biases representing small coefficients are relatively high compared to noise due to the non-zero temperature of the QPU.

For example, submitting a problem with coefficients that include maximum values of \(J_{i,j} = 1, h_k = 10\) to a QPU solver with ranges j_range = [-1.0, 1.0] and h_range = [-2.0, 2.0] requires scaling by a factor of 5 (\(h_k = 10\) must fit under the upper limit of 2.0) while submitting it to a newer solver with h_range = [-4.0, 4.0] scales by 2.5. Consequently, if \(J_{i,j}\) is mapped to a single coupler bias, \(J_{x,y}\), its previous value of 0.2 is now increased to 0.4. For typical temperature-related noise amplitude of around 0.1–0.15, this increase can be significant. (Note that problems specified in QUBO form are converted to Ising when submitted and that bias values in the converted form, which have a dependency on the number of quadratic interactions in the QUBO, can be larger than the maximum bias of the original form—see the auto_scale parameter for more information.) For another example, see the Problem Scale example in the D-Wave Problem-Solving Handbook guide.

Support for Sub-Microsecond Anneals

This release enables users to specify a minimum anneal time smaller than one microsecond for newer Advantage QPUs. Previously, the range of anneal times for an Advantage QPU had a lower limit of 1 \(\mu s\); for example, on the Advantage_system1.1 system, annealing_time_range = [1, 2000]. The Advantage_system4.1 system supports a range of annealing_time_range = [0.5, 2000.0].

2021-09-27 Leap Release

New Leap Administration Tool

Leap Admin is a new, easy-to-use cloud-based administration tool. A project administrator uses Leap Admin to invite users and manage their access to projects in Leap, view the status of problems submitted to solvers, troubleshoot issues with problem submissions, and generate solver usage reports.

Leap Admin is available to project administrators from their Leap Dashboard. The Leap Admin menu should be accessible from your profile avatar. If you currently have project management permissions in Qubist (D-Wave’s legacy user interface) then you have been granted project administrator access in the new Leap pages. For questions about accessing Leap Admin, contact D-Wave Customer Support.

For instructions about using Leap Admin, go to the Administration Guide.

Resolved Leap IDE Workspace Outage

From September 9 to September 14, 2021, users were unable to access existing workspaces and create new ones in the Leap IDE. This issue is now resolved.

Resolved: Problems Completed Panel in the Leap Dashboard is Overbroad

In previous releases, in the Problem Completed panel on the Leap dashboard, the total number of completed problems shown included canceled and failed problems. However, such problems did not decrement solver access time and they did not appear in the usage statistics that show problems completed over time. This issue is now resolved.

2021-09-08 Leap Release

Higher Resolution of Timing Properties, Parameters, and Fields

For timing-related SAPI properties and parameters, and for timing fields in returned solutions, which currently have values defined as integers, this release updates the data type to floating-point number. This backwards-compatible change enables support for values with higher resolution and/or range.

Having higher resolution can be useful for benchmarking and quantum-simulation studies; for example, where previously a set of anneal times might have been increased by 1 \(\mu s\) steps, you can now set steps of 0.01 \(\mu s\) on Advantage systems to attain a smoother dataset.

Updated properties are annealing_time_range, default_annealing_time, default_programming_thermalization, default_readout_thermalization, problem_run_duration_range, programming_thermalization_range, and readout_thermalization_range. For example, the annealing_time_range property, which defines the range of time possible for one anneal, was specified on the Advantage_system1.1 system as a pair of integer numbers of microseconds with value [1, 2000] and is now a pair of floating-point numbers with value [1.0, 2000.0].

Updated parameters are annealing_time, programming_thermalization, and readout_thermalization. Some timing parameters, such as anneal_schedule, already supported floating-point numbers and are not changed.

All the timing fields in returned solutions are updated. See the QPU Timing Information from SAPI section of the QPU Solver Datasheet for an example output.

2021-08-25 Leap Release

Resolved DQM Solver Scaling Issue

In previous releases, the hybrid_discrete_quadratic_model_v1 solver returned different quality results for the same problem submitted at different scales. This issue is now resolved.

Resolved QPU Access Time Issue in Leap Dashboard

In previous releases, the QPU access time used by a hybrid problem was incorrectly displayed on the Leap dashboard. For example, a problem with QPU access time of 32,519 microseconds was shown in the in the dashboard as 0.33 seconds instead of 0.033 seconds. This display-only issue was limited to the Leap dashboard: the Ocean response object reported the QPU access time correctly. This issue is now resolved.

Documentation Restructure: QPU Solver Datasheet

The formerly titled Technical Description of the QPU is now the QPU Solver Datasheet guide. This guide describes the D-Wave QPU in detail—the quantum annealing process, effects of integrated control errors (ICE) and other errors—and now includes chapters on timing and postprocessing (for the D-Wave 2000Q), which were previously separate documents. This document also provides the high-level descriptions of the annealing control features that were previously duplicated in a Quantum Annealing Controls section.

The content previously in a Machine Learning section is now included in the Problem-Solving Handbook guide.

Note also that the title of the Getting Started with the D-Wave System guide has been altered to Getting Started with D-Wave Solvers.

2021-06-16 Leap Release

Revision to Release Note for Leap’s DQM Solver

The content of release note Hybrid Solver Service: DQM Solver is revised for a software update deployed in February 2021 that changed the limits on the supported numbers of variables (previously 5,000) and total biases (previously 2 billion). The revised sentence now states, “It accepts problems with up to 3,000 discrete variables, each of which can represent sets of up to 10,000 values, and 3 billion total linear plus quadratic biases (values assigned to both nodes and edges of the graph representing your problem).”

See the Hybrid Solver Service: DQM Solver release note below for more information.

2021-05-19 Leap Release

Change to Orders and Billing Access via Leap

As of May 19, 2021, orders and billing information is no longer directly available to customers through the Leap™ system.

No action is required: Our system will continue to charge your credit card for your monthly Leap access, and a copy of the receipt will automatically be sent to you.

2021-05-05 Leap Release

Documentation Improvement: Updated Solver Properties and Parameters Guide

The Solver Properties and Parameters describes the solvers available through SAPI, their properties, and the parameters they accept with a problem submission.

A recent update has restructured this guide to make it easier to use and added basic usage examples for QPU and hybrid solvers.

2021-04-21 Leap Release

Documentation Improvement: Updated Problem-Solving Handbook

The Problem-Solving Handbook provides advanced guidance on using D-Wave solvers, in particular QPU solvers. It explains and demonstrates techniques of problem formulation, minor-embedding, and configuring QPU parameters to optimize performance.

A recent update has restructured and expanded this guide and made its techniques more widely accessible by adding Ocean code examples for many that were previously described only through mathematical formulation.

Japanese Translation of Leap Cloud Subscription Agreement: Japan

A Japanese translation of the Leap Cloud Subscription Agreement for Japan is available for download at Subscription Agreement: Japan.

The official legal document is the English language version of the Agreement.

2021-03-24 Leap Release

New Working Graph for Backup Advantage System

The backup Advantage system—renamed to Advantage_system3.2—has a new working graph that can be found here: QPU-Specific Physical Properties.

The anneal schedule for Advantage_system3.2 is identical to the previous Advantage_system3.1 schedule, and can be found here: QPU-Specific Anneal Schedules.

2021-03-10 Leap Release

Downloadable Privacy Policy and Terms & Conditions

The Leap Privacy Policy and Terms and Conditions are now available for download as PDFs here:

2021-02-22 Leap Release

Leap Expands to Singapore

As of February 23, 2021, users from Singapore 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 in North America, Europe and Asia-Pacific to 38.

2021-02-10 Leap Release

Deprecated Timing Fields Removed from Solver API

In release notes 2.4 in 2016, the names of the four timing fields shown in the table below were reported as being deprecated and the Solver Computation Time guide was updated to show the replacement field names. From this release, the old field names are no longer supported in the Solver API. If you have any code that is still using the old names, please update to the new ones.

Table 80 Discontinued timing fields in SAPI
Discontinued Name New Name
total_real_time qpu_access_time
run_time_chip qpu_sampling_time
anneal_time_per_run qpu_anneal_time_per_sample
readout_time_per_run qpu_readout_time_per_sample

Resolved Energy Offset Issue Affecting Some Hybrid Problems

Some customers may have encountered an issue where the energy offset was dropped for some sparse problems submitted to the hybrid_binary_quadratic_model_version2 solver. This issue is now resolved.

Resolved MFA Email Issue

Some customers may have received multiple multi-factor authentication (MFA) emails when logging into Leap. This issue is now resolved.

2021-01-27 Leap Release

Removed Statistics Panel on Leap’s Dashboard

The Stats panel, which showed the status of a quantum computer (temperature, number of qubits, etc.) is removed. You can view information about solvers by clicking on the solver name.

Assign Problem Labels

You can now assign labels to the problems you submit to D-Wave solvers. Labels are strings that have meaning to you or are generated by your application, which can help you identify your problem submission. The Problem Status panel displays the problem label by default; you can return to displaying problem IDs by clicking the settings icon beside the Problem Label heading. Problems without labels are displayed with <unlabeled> in the Problem Label column. This example submits a simple problem and reads the label in the returned response.

>>> from dwave.system import DWaveSampler, EmbeddingComposite
>>> sampler = EmbeddingComposite(DWaveSampler())
>>> sampleset = sampler.sample_ising({}, {('q1', 'q2'): -1}, label="Simple Ising problem")
>>> sampleset.info['problem_label']
'Simple Ising problem'

The system-generated problem ID remains the unique identifier for a problem.

2021-01-13 Leap Release

Terms and Conditions for Japanese Users of Leap

Terms and conditions for Japanese users of Leap are here: Leap Cloud Subscription Agreement: Japan.

Resolved Incorrect Energies Returned by Hybrid Solver

This release resolves an issue where some problems submitted to hybrid_binary_quadratic_model_version2 returned noticeably incorrect energies.

2020-12-16 Leap Release

User Statistics Available on Leap’s Dashboard

Leap’s dashboard now lets you view and download your problem-submission statistics for Leap solvers.

_images/leap_site_user_stats.png

Fig. 121 User statistics panel in Leap.

2020-12-04 Leap Release

Problem Details Available on Leap’s Dashboard

You can now see detailed information about problems that you have submitted to Leap solvers. You can also search and filter the list of problems and cancel any pending ones (problems that are canceled before they complete do not use any solver access time).

_images/leap_site_problems.png

Fig. 122 Problem-Status panel in Leap.

Multiple-Project Support

This release enhances support for users in multiple projects. For users with access to multiple projects, Leap now displays information for the user’s active project; this includes the name of the project, amount of solver access time remaining in the current period, amount of time used, available solvers, API token used to connect to the solvers, and list of problems submitted. To switch which project is currently active, click the username on the top right of the Leap dashboard and select Projects. Any change to the active project also affects IDE workspaces. Be aware that any problem submitted, including those via Leap’s animated demos, will deduct time from the active project.

_images/leap_site_mps_dropdown_menu.png

Fig. 123 Changing active projects from the Dashboard.

While in an IDE workspace, you can use the leapide workspace command to see which project the workspace is pinned to.

Leap IDE /workspace/antenna-selection $ leapide workspace
Workspace ID: abc12345-1234-1a2b-3c4d5-123456789012
Project: Developer (id=123, code=DEV)
Leap IDE /workspace/antenna-selection $

The IDE periodically imports your API token from Leap. If you reset your token on the Leap dashboard, your new token is automatically updated in the IDE within a minute.

Every workspace you create is pinned to a project in your account. If your account has access to multiple projects, the IDE imports the API token for the project pinned to the current workspace. You can override the imported API token by setting the DWAVE_API_TOKEN environment variable in the IDE. (The imported token is set as in a system-wide configuration file; configuration priority is described in Ocean’s cloud-client documentation.) If you currently have manually set DWAVE_API_TOKEN environment variables in your workspace, consider deleting these to benefit from automatic imports.

Note

Only users in multiple projects will see this change. Self-signed up users with free Leap accounts only have access to the Developers project, which sets their usage quota and API tokens.

2020-11-18 Leap Release

Solver Details Available on Leap’s Dashboard

The properties of a solver and the user parameters that it accepts are available on the Leap™ dashboard. From the list of supported solvers, simply click a solver name to view these details. For more information on solver properties and parameters, see Solver Properties and Parameters Reference.

Some properties, such as the qubits property for a QPU solver, are Python dicts; these can be copied to your clipboard with a single click.

2020-11-04 Leap Release

Resolved Failures on Version 2 of Hybrid BQM Solver

This release resolves an issue that affected problems submitted to the following hybrid solver: hybrid_binary_quadratic_model_version2. Previously, problems with over 20,000 variables submitted to this solver may have failed. Affected problems did not consume any solver access time.

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.

2020-10-07 Leap Release

Hybrid Solver Service: DQM Solver

Note

This section was revised on June 16, 2021 to account for a software deployment in February that made the following updates:

  • The maximum_number_of_biases property, which sets the maximum number of biases, both linear and quadratic in total, accepted by the solver, was increased from 2 to 3 billion.
  • The maximum_number_of_variables property, which sets the maximum number of problem variables accepted by the solver, was reduced from 5,000 to 3,000.

The second paragraph below, which previously stated that the solver accepts problems with up to 5,000 variables and 2 billion biases, now contains the revised numbers 3,000 variables and 3 billion biases.

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 3,000 discrete variables, each of which can represent sets of up to 10,000 values, and 3 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.

[4]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 D-Wave Solvers 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[4] for problems submitted to Advantage and D-Wave 2000Q QPUs.

[5]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[5].

[6]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).

_images/hss_bqm_v1_vs_v2_from_pdf.png

Fig. 124 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 D-Wave Solvers. 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 in North America, Europe and Asia-Pacific to 37.

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 SAPI REST Developers 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 QPU Solver Datasheet.


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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