ising

Quantum annealing, a special case of Adiabatic Quantum Computing, is a completely different approach for solving Ising problems.

And since so many important problems can be reduced to an Ising model, this is interesting.

Note that Ising computers are quite special-purpose machines and can't (easily) solve general purpose computing problems.

The probabilistic equations describing segmentation of on-object versus off-object regions are the same mathematically as the magnetic energy function of the Ising model.

No different to ising Slack and Zoom which is a very common combination.

Not everyone knows what the Ising model is, but everybody loves magnets.

The D-wave chip is just a very fast hardware-based Ising model solver.

This is true both because of the inherent limitations of the adiabatic algorithm, and because of specific concerns about the Ising spin graph problem.

Sometimes the LP relaxations give much better results, but they tend to be much, much, slower, for the Ising problem.

I think in the end ising a language you are most familiar with results in the most amount of enjoyable coding.

This is a standard physics model called an Ising model.

A classical super-efficient Ising Model solver is interesting enough.

It's a certain kind of binary optimization problem that comes up in models of magnetic media ("Ising model").

Then the problem it solves stated as "Ising model Hamiltonian using quantum computer" is fairly uninteresting given that it is cheaper and simpler to solve the "Ising model Hamiltonian using classical hardware".

The Ising model Hamiltonian that the D-Wave computer "evolves" almost directly maps to the energy equation you have to minimize to train a restricted Boltzmann machine.

But the rise in "recommendation engines" (Facebook, Tumblr, etc) and even "news aggregators" (yes, the irony) may indeed impart the provincial-ising effect you mentioned.

SAT or Ising) out of exotic hardware that does compute in memory.