Reference Documentation#

dimod: Quadratic models (BQM, CQM).

Shared API for binary quadratic samplers. Provides a binary quadratic model (BQM) class, which contains Ising and quadratic unconstrained binary optimization (QUBO) models used by samplers such as D-Wave quantum computers, and a constrained quadratic model (CQM) used by hybrid samplers. Also provides utilities for constructing new samplers and composed samplers.

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dwavebinarycsp: Generates BQMs from constraint satisfaction problems.

Library to construct a binary quadratic model from a constraint satisfaction problem (CSP) with small constraints over binary variables.

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dwave-cloud-client: API client to the Leap service’s solvers.

Minimal implementation of the REST interface used to communicate with SAPI servers.

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dwave-gate: Package for quantum circuits.

A software package for constructing, modifying and running quantum circuits.

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dwave-hybrid: Framework for building hybrid solvers.

A general, minimal Python framework for building hybrid asynchronous decomposition samplers for quadratic unconstrained binary optimization (QUBO) problems.

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dwave-inspector: Visualizer for problems submitted to quantum computers.

A tool for visualizing problems submitted to, and answers received from, a D-Wave structured solver such as an Advantage quantum computer.

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dwave-networkx: NetworkX extension.

Extension of NetworkX—a Python language package for exploration and analysis of networks and network algorithms—for users of D-Wave quantum computers.

This package provides tools for working with Pegasus and Zephyr graphs and implementations of graph-theory algorithms on D-Wave quantum computers and other binary quadratic model (BQM) samplers.

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dwave-ocean-sdk: Ocean software development kit.

Installer for D-Wave’s Ocean Tools.

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dwave-optimization: Nonlinear models.

API for nonlinear models. The package includes:

  • A class for nonlinear models used by the Leap service’s hybrid nonlinear-program solver.

  • Model generators for industrial optimization problems.

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dwave-preprocessing: Preprocessing tools for quadratic models.

Library containing common preprocessing tools for quadratic models.

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dwave-samplers: Classical algorithms for solving binary quadratic models.

A library that implements the following classical algorithms as samplers for solving binary quadratic models (BQM):

  • Planar: an exact solver for planar Ising problems with no linear biases.

  • Random: a sampler that draws uniform random samples.

  • Simulated Annealing: a probabilistic heuristic for optimization and approximate Boltzmann sampling well suited to finding good solutions of large problems.

  • Steepest Descent: a discrete analogue of gradient descent, often used in machine learning, that quickly finds a local minimum.

  • Tabu: a heuristic that employs local search with methods to escape local minima.

  • Tree Decomposition: an exact solver for problems with low treewidth.

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dwave-system: D-Wave samplers and composites.

Basic API for easily incorporating the D-Wave quantum computer as a sampler in the Ocean software stack.

It includes the DWaveSampler sampler, a dimod sampler that accepts and passes system parameters such as system identification and authentication down the stack. It also includes several useful composites—layers of pre- and post-processing—that can be used with this sampler to handle minor-embedding, optimize chain strength, etc.

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minorminer: Minor-embeds graphs.

A tool for finding graph minor-embedding, developed to embed Ising problems onto quantum annealing (QA) quantum computers.

While it can be used to find minors in arbitrary graphs, it is particularly geared towards the state of the art in QA: problem graphs of a few to a few hundred variables, and hardware graphs of a few thousand qubits.

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penaltymodel: Maps constraints to binary quadratic models.

An approach to solve a constraint satisfaction problem (CSP) using an Ising model or a QUBO, is to map each individual constraint in the CSP to a “small” Ising model or QUBO.

Includes a local cache for penalty models and a factory that generates penalty models using SMT solvers.

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