How to Implement Dwave QBSOLVE in Python

Date:

Share post:

D-Wave’s qbsolv is a Python package for solving Quadratic Unconstrained Binary Optimization (QUBO) problems. It is an approximate solver that uses a hybrid approach combining a classical optimization algorithm with a D-Wave quantum annealer. The package is designed to be used as a fallback solver when a problem is too large to be solved directly on a D-Wave quantum annealer or when an exact solution is not required.

qbsolv can be used to solve QUBO problems with up to thousands of variables. It takes as input a QUBO matrix or an Ising Hamiltonian, and returns an approximate solution to the problem in the form of a binary vector that minimizes the energy of the QUBO or Ising model. The solution can be further post-processed to extract relevant information such as the optimal value of the objective function and the variables that are set to 1 in the solution.

qbsolv can be called directly from Python using a simple API, and can also be integrated into larger workflows involving other optimization tools or databases. It is available as an open-source package under the Apache 2.0 license, and can be installed using pip.

To implement D-Wave’s qbsolve in Python, you can follow these steps:

  • Install the qbsolve package:

Import the necessary packages in your Python code:

Define your problem as a QUBO or Ising model. Here is an example of a simple QUBO proble

Call qbsolv to solve the problem:

Process the response to get the solution:

Here is the complete code:

import dwave_qbsolv as qbsolv

Q = {(0,0): -1, (1,1): -1, (0,1): 2}

response = qbsolv.QBSolv().sample_qubo(Q)

solution = response.sampl

es()[0]

print(solution)

This should output the solution to the QUBO problem. Note that qbsolve is an approximate solver, so the solution may not be exact.

Method 2

Use the following code if 1st method is not working

import dwave_qbsolv as qbsolv h = {0: 0.5, 1: -1.0, 2: 0.0} J = {(0, 1): -1.0, (1, 2): 0.5, (0, 2): -1.5} response = qbsolv.QBSolv().sample_ising(h, J) solution = response.samples()[0] print(solution)

Hope you will find it well for implement dwave qbsolve in python. In this article, Ezine news express the method to implement D-Wave’s qbsolve in Python

LEAVE A REPLY

Please enter your comment!
Please enter your name here

spot_img

Related articles

Tips For Choosing A Good Personal Injury Lawyer

Your life might be drastically altered shortly due to a tragic incident. To hold the party accountable for...

Advantages Of Purchasing An Engagement Ring In The Digital Age

As you may well know, the current phase of the COVID-19 pandemic is unprecedented globally. The jewellery sector...

4 Various Benefits Of SIL Services In Australia

The NDIS in Australia provides various services to assist people with disabilities who don't have any other means...

Get yourself the best scrubs

Whether you're a first-time buyer or a seasoned vet, several important details to remember when selecting your scrubs....