annealing

It's got properties that lend it to easy junction doping and easy annealing.

Yes, I think it is a lot like simulated annealing, with rounds of the following:0. internal stresses exist = mutter "look at all these contradictions and warts"; start rethinking assumptions1.

Seems like simulated annealing would be a pretty good fit, where you perturb the word spacing on each iteration and the energy function is the total river length.

I watched this happen over and over again with genetic algorithms, simulated annealing, and other learning algorithms.

From Scott Aaronson:> If one considers only the ~10% of instances on which the D-Wave machine does best, then the machine does do slightly better on those instances than simulated annealing does.

The D-Wave machine is more limited, however; it only does quantum annealing, and the thing about quantum annealing is that it gracefully degrades into classical annealing.

Apparently it appears for r=1, but disappears for r=3 and r=7—thereby heightening one’s suspicion that we’re dealing with an artifact of the minimum annealing time or something like that, rather than a genuine speedup.

A really long time ago when I was in grad school playing with genetic algorithms and simulated annealing, I implemented something that seems awfully similar to quantum adiabatic annealing.

I understand that the place and route algorithm is based upon simulated annealing, in which you make small random perturbations to the current layout configuration, measure whether it is better or worse, and sometimes retain the new configuration, and sometimes roll back.

They found that the performance characteristics -- which problems are easier to solve and which harder, and by how much -- match up well between D-Wave's machine and the simulation of the quantum process it's meant to be an implementation of, whereas classical simulated annealing doesn't match at all well.