A Quantum Machine Learning Story
The Hamiltonian
Yesterday, I published the next update on Hands-On Quantum Machine Learning With Python Volume 2: Combinatorial Optimization.
In the new chapter 8, we embark on a search—a search for the ground state. The ground state is that particular state of a system with the lowest energy. It is important because it represents the solution to the optimization problems we aim to solve.
Another important aspect we build upon in our search for the ground state is the Hamiltonian. The Hamiltonian is a quantum operator that describes the possible energies of a physical system. Doesn’t it sound like a big deal? But it is. Because if we know the Hamiltonian, we can calculate the system's behavior. Therefore, we shed some light on the Hamiltonian in today’s blog post: The Hamiltonian — A quantum machine learning story
The Hamiltonian is of such importance that you will encounter it in almost all technical papers on quantum computing and quantum machine learning. Of course, it is something physicists usually talk about. So, it is not a beginner-friendly concept. However, in the post and in my book, I try to explain it in an accessible way. Moreover, in chapter 7, we learn how to decompose the Hamiltonian practically to use it in a quantum circuit.
I have researched a lot for my book. Many posts, books, and other resources explain only parts of the Hamiltonian, its decomposition, and how to use it to find the ground state. So, I dare to claim that you won’t find a more comprehensible coverage of this topic anywhere else.
You can still join the Early Access Program of Hands-On Quantum Machine Learning With Python Volume 2: Combinatorial Optimization. More than 170 pages are already waiting for you!
Furthermore, if you haven’t yet claimed your copy of Volume 1, you can save 10% by buying the eBook bundle. It contains the complete Volume 1 and the Early Access of Volume 2.
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