D-Wave's newest quantum computer, Advantage, introduces a quantum processing unit (QPU) with a new architecture: the Pegasus family of topologies. This notebook explains the Pegasus topology and how it enables superior performance to previous generations of quantum computers.
The notebook has the following sections:
- The Pegasus Advantage demonstrates and explains the performance differences between the previous and new QPU architectures.
- Navigating the Topology describes the new topology and presents Ocean tools that help you use it.
- Example Problem: RANr solves a hard problem on an Advantage quantum computer.
The layout of the D-Wave QPU is critical to formulating an objective function in a format that a D-Wave annealing quantum computer can solve. Although Ocean software automates the mapping from the linear and quadratic coefficients of a quadratic model to qubit bias and coupling values set on the QPU, you should understand it if you are using QPU solvers directly because it has implications for the problem-graph size and solution quality.
The D-Wave QPU is a lattice of interconnected qubits. While some qubits connect to others via couplers, the D-Wave QPU is not fully connected. Instead, the qubits of D-Wave annealing quantum computers interconnect in one of the following topologies:
- Chimera for D-Wave 2000Q and earlier generations of QPUs
- Pegasus for Advantage QPUs
These topologies are described in D-Wave's system documentation.
You can run this example without installation in cloud-based IDEs that support the Development Containers specification (aka "devcontainers").
For development environments that do not support devcontainers
, install
requirements:
pip install -r requirements.txt
If you are cloning the repo to your local system, working in a virtual environment is recommended.
Your development environment should be configured to access Leap’s Solvers. You can see information about supported IDEs and authorizing access to your Leap account here.
The notebook can be opened by clicking on the
01-exploring-pegasus.ipynb
file in VS Code-based IDEs.
To run a locally installed notebook:
jupyter notebook
See LICENSE file.