[scruffups]

My understanding is that the D-Wave quantum computer uses quantum spin-glass annealing (by tapping into these physical effects) to solve combinatorial optimization problems faster than classical computers, including simulated (thermodynamic) annealing.

I believe this research work is going in the direction of building quantum annealers. Reinventing what D-Wave had done, or improving on it. Not a condensed matter physicist nor an optimization theory nerd, so I can't tell you much more, but that's my gut feeling.

From 2015 via Google AI:

"We found that for problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 10^8 times faster than simulated annealing running on a single core. We also compared the quantum hardware to another algorithm called Quantum Monte Carlo. This is a method designed to emulate the behavior of quantum systems, but it runs on conventional processors. While the scaling with size between these two methods is comparable, they are again separated by a large factor sometimes as high as 10^8."

https://ai.googleblog.com/2015/12/when-can-quantum-annealing...

[andbberger]

Maybe you should read the paper.

[scruffups]

Maybe you could explain where the paper contradicts the above?