March 2023
Intermediate to advanced
680 pages
13h 44m
English
book
A Practical Guide to Quantum Machine Learning and Quantum Optimization
by Elías F. Combarro, Samuel González-Castillo
Content preview from A Practical Guide to Quantum Machine Learning and Quantum Optimization
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Chapter 5 QAOA: Quantum Approximate Optimization Algorithm
True optimization is the revolutionary contribution of modern research to decision processes. — George Dantzig
The techniques that we have introduced in the two previous chapters already allow us to solve combinatorial optimization problems on quantum computers. Specifically, we have studied how to write problems using the QUBO formalism and how to use quantum annealers to sample approximate solutions. This is an important approach to quantum optimization, but it is not the only one.
In this chapter, we are going to show how the ideas that we have already explored can also be used on digital quantum computers. We will be using our beloved quantum circuits — with all their qubits, quantum ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.