To my knowledge, it is an open challenge to find real-world problem instances where existing quantum annealers outperform state-of-the-art classical alternatives. It's even hard to find _extremely contrived families of instances_ where practical computational benefits can be observed with quantum annealing. I recently contributed to one such benchmarking manuscript [1], which may indicate future promise as the number of qubits in quantum annealers continues to increase.Anyway, as a result of that experience, I'm skeptical of the benchmarking efforts that led these two companies to the conclusion that quantum annealing is more cost-effective than dropping in a classical alternative as the inner optimization solver. D-Wave even has some reasonably efficient, open-source algorithms that can be used as a point of comparison (e.g., [2]). I'd be interested in reading more about the companies' benchmarks, as this article is very light on details.
[1] https://arxiv.org/pdf/2210.04291.pdf
[2] https://github.com/dwavesystems/dwave-neal
analog31|3 years ago
But every time GaAs cleared another hurdle, silicon also moved forward, kind of like the tortoise and the hare. There are certainly uses for GaAs, such as microwave amplifiers, but no GaAs computers yet that I'm aware of.
IvyMike|3 years ago
https://en.wikipedia.org/wiki/Cray-3
ThrowawayTestr|3 years ago
Dylan16807|3 years ago
It's hard to even demonstrate how quantum annealing scales at all.
pinewurst|3 years ago