The Comprehensive Guide To The Variational Quantum Eigensolver

Solving combinatorial optimization problems on a quantum computer

The Variational Quantum Eigensolver (VQE) is the most important quantum machine learning algorithm of today.

Yet, it is quantum machine learning’s stepchild. As such, the popular press belittles it, the hard-core enthusiasts neglect it, and the educators mention it only in passing.

But, this is going to change now! My new book, Hands-On Quantum Machine Learning With Python Volume 2: Combinatorial Optimization is all about the Variational Quantum Eigensolver and how it solves combinatorial optimization problems.

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Solving optimization problems is paramount in many industries.

Take the mobility sector, for example. The whole industry has long ceased to struggle with engineering problems. The construction of a car, an airplane, or even a spacecraft is no rocket science anymore. Humanity solved these problems decades ago.

Today, anybody can go anywhere — technically. If you have enough money, you can even go to space.

But, this doesn’t mean the mobility sector ran out of problems. On the contrary! Climate change, disrupted supply chains due to a global pandemic, and the resurrection of…