[kale]

I'm not an expert in the field, but I do annealing work on occasion (simulated annealing, which is kind of like copying polymer annealing).

Simulated annealing is just an optimization. I use it for modelling human motion. You have the position and acceleration of each bone in the legs and feet. You start by deciding on a variable (say, reducing energy expenditure for gait), and then letting the algorithm alter variables and attempt to minimize a variable.

So if quantum annealing is anything like simulated annealing, you aren't "solving" for a single, correct answer, but getting a solution that minimizes or maximizes an outcome faster than brute force.

So a quantum computer could solve "What is the factorization of this huge number?", while quantum annealing could solve "Given these 30 different engine configurations, which combination of intake pressure, fuel flow rate, turbocharger performance curve, and engine timing would result in the best fuel efficiency?"

[Ar-Curunir]

Optimisation and Search problems are not fundamentally different; one can usually translate a problem from one world to another. For instance, take your optimisation problem and rephrase it as:

Here's a value of the fuel efficiency; find me a setting of the parameters that achieves a fuel efficiency better than that.

It's now a search problem. To find the best fuel efficiency, just binary search over possible values of the efficiency.

Where D-Wave differs is that you can only solve a particular kind of optimisation problem, and this kind of problem can't encode general computation. General quantum computers can solve general computation problems, not just the simulated annealing of D-Wave QC.

[sp332]

The advantage of a quantum annealer is in cases where there is a large, narrow spike in the way of moving to a good solution. The quantum optimizer has a chance of "tunneling" through the spike to find a better solution. A classical version of simulated annealing would have to "climb" over the spike, or more likely just be stuck on the wrong side.