Chapter 3
Working with Quadratic Unconstrained Binary Optimization Problems
The universe cannot be read until we have learned the language and become familiar with the characters in which it is written.
— Galileo Galilei
Starting with this chapter, we will be studying different algorithms that have been proposed to solve optimization problems with quantum computers. We will work both with quantum annealers and with computers that implement the quantum circuit model. We will use methods such as the Quantum Approximate Optimization Algorithm (QAOA), Grover’s Adaptive Search (GAS), and the Variational Quantum Eigensolver (VQE). We will also learn how to adapt these algorithms to different types of problems, and how to run them on simulators and actual quantum computers.
But before we can do all that, we need a language in which we can state problems in a manner that makes it possible for a quantum computer to solve them. In this regard, with the Quadratic Unconstrained Binary...
