---
id: dwave-graphs
version: "1.0.0"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# dwave-graphs — A package providing graphs and algorithms for working with D-Wave quantum computers.

License: permissive · Maintenance: active · Downloads: 77.5K/mo

## What it is and what it does

dwave-graphs is a Python library for representing and manipulating quantum processor topologies, particularly the Pegasus topology used by D-Wave's Advantage quantum computers. It wraps graph structures and provides algorithms designed to work with binary quadratic model (BQM) samplers on D-Wave hardware and other compatible systems.

The package sits in the D-Wave Ocean SDK ecosystem and depends on networkx for graph operations, numpy for numerical work, and dimod for BQM handling. It is primarily useful for researchers and developers building quantum annealing applications who need to understand or work directly with QPU connectivity constraints, or who are implementing graph-based algorithms for quantum optimization.

Use it for:

- Generate and inspect Pegasus topology graphs to understand D-Wave Advantage QPU connectivity constraints.
- Implement graph-theory algorithms optimized for quantum annealing on D-Wave hardware.
- Map classical optimization problems to QPU topology when designing BQM formulations.
- Prototype quantum annealing solutions that must respect hardware topology limitations.
- Research quantum processor architecture and topology-aware algorithm design.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides graph representations and algorithms for D-Wave quantum processors, including topology graphs like Pegasus and tools for working with binary quadratic model samplers.

Yes, if you are working with D-Wave quantum computers or researching quantum annealing. The package is actively maintained, has no known vulnerabilities, low install friction, and a permissive license. It is a specialized tool with a narrow audience—install only if you need QPU topology graphs or D-Wave-specific graph algorithms.

## Install

pip install dwave-graphs
uv add dwave-graphs
poetry add dwave-graphs

## Installing dwave-graphs

Before you install: Low install friction with a pure Python wheel and three common dependencies (dimod, networkx, numpy). Active maintenance with a recent release and no known vulnerabilities.

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions, typical for D-Wave's open-source quantum software ecosystem.

Quickstart:

pip install dwave-graphs

import dwave.graphs
graph = dwave.graphs.pegasus_graph(16)

Requires Python 3.10 or later (3.14.1 excluded); depends on dimod, networkx, and numpy being installed.

Verify before relying:

- Whether pegasus_graph(16) is the correct size parameter for Advantage QPUs or if other sizes are commonly used.
- What specific graph-theory algorithms beyond topology representation are included in the package.
- Performance characteristics when working with large-scale QPU topologies.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 77.5K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

quantum processor topology graphs, D-Wave QPU graph tools, Pegasus graph generation, quantum computer graph algorithms, BQM sampler graph utilities, quantum annealing topology, D-Wave Advantage graphs, quantum-computing, graph-algorithms, D-Wave

[View on SkillFed](https://skillfed.io/packages/dwave-graphs) · [View on PyPI](https://pypi.org/project/dwave-graphs/)