In the last episode #17, we saw how optimization problems can be turned into physics problems. By carefully designing a Hamiltonian, we let a quantum system relax into its ground state, which encodes the optimal solution we were looking for. This idea is known as adiabatic quantum computation.
There is a big secret I quietly swept under the rug last time. Adiabatic quantum computing is universal. This means it is computationally equivalent to the circuit based model of quantum computing, the one used by Google and IBM, and also to measurement based quantum computing (MBQC), pursued by companies like PsiQuantum and Xanadu.
Universal is a strong word. It means that all these are built to solve various types of problems. Just like modern laptops, they are general purpose machines.
But general purpose is not always what we want.
Think about the computers inside ATM machines or supermarket checkout counters. They are not designed to browse the web or edit photos and watch videos. They do one thing and they do it well. They handle payments and nothing more.
This raises a natural question.
Do quantum computers also have specialized versions, machines built to excel at a specific task rather than everything at once?
As you might have guessed, the answer is yes.
Let me introduce you to the close cousin of adiabatic quantum computing, one that is even more inspired by real physical processes. It is called quantum annealing which is used for more specific optimization problems (like the packet delivery problem we discussed in episode #1).
To understand it, we first need to take a short detour into metallurgy, cooking, and everyday frustration.
