Scientists from quantum computing company D-Wave have demonstrated that, using a method called quantum annealing, they could simulate some materials up to three million times faster than it would take with corresponding classical methods.
Together with researchers from Google, the scientists set out to measure the speed of simulation in one of D-Wave's quantum annealing processors, and found that performance increased with both simulation size and problem difficulty, to reach a million-fold speedup over what could be achieved with a classical CPU.
The calculation that D-Wave and Google's teams tackled is a real-world problem; in fact, it has already been resolved by the 2016 winners of the Nobel Prize in Physics, Vadim Berezinskii, J. Michael Kosterlitz and David Thouless, who studied the behavior of so-called "exotic magnetism", which occurs in quantum magnetic systems.
[...] In contrast, D-Wave's latest experiment resolved a meaningful problem that scientists are interested in independent of quantum computing. The findings have already attracted the attention of scientists around the world.
Journal Reference:
Andrew D. King, Jack Raymond, Trevor Lanting, et al. Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets [open], Nature Communications (DOI: 10.1038/s41467-021-20901-5)
(Score: 5, Informative) by Thexalon on Monday March 08 2021, @02:20PM
My understanding is that the research into quantum computing has been focused on problems where the solution can be verified quickly using "standard" computation, but cannot be developed quickly using those tools. So you use the analog methods to get to an alleged solution that you can check, and then check it.
This would be incredibly useful for solving whole classes of problems computers can't handle right now, and currently depend on the even less reliable wetware.
The only thing that stops a bad guy with a compiler is a good guy with a compiler.