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> Furthermore, real optimization problems have high connectivity, high weight cost function terms, and require higher precision than available. Have you seen t

> Furthermore, real optimization problems have high connectivity, high weight cost function terms, and require higher precision than available. Have you seen their hybrid system they just released? https://www.zdnet.com/article/this-cloud-service-lets-you-use-quantum-and-classical-computing-together-to-solve-big-problems/ https://www.zdnet.com/article/this-cloud-service-lets-you-us... Looks like it's a strong contender for people who have bigger, higher-connectivity problems that want to get ready for when the quantum processors are bigger.

s1dev 7y ago
You can't get thousands of variables with all to all connectivity on a quantum annealer. The noise will kill it. I.e. you will never have such a device with reasonable coupler precision. The techniques for decomposing a problem and solving the sub problems are a big (exponential) overhead because of frustration effects which require you to look at the entire problem at once. And for context the PUBO -> QUBO mapping (high order to low order) + topology embedding can blow up the number of variables by an order of magnitude or more. The solution space scales exponentially with the number of variables so a naive solver will again deal with a messy overhead.