April 25, 2014 15:00 〜 16:30
CiNet 1F Conference Room B
Principles of Informatics Research Division, National Institutes of Informatics
She will give both introduction and front line of quantum computation, and then possibly touch on its relationship with the brain computation.
Optimization problems are well known computationally hard problems in our modern life such as weather forecast, protein holding problems, stock price prediction, travelling salesman problems, and so on. Even supercomputer cannot solve those problems exactly because the required computational time scales exponentially as the growth of their problem size. Those optimization problems are classified into as NP-complete/ hard problems. The quantum computing is one of the possibilities to solve those computationally hard problems efficiently. Recently new type of quantum computing called as quantum annealing machine has gotten a lot of attention recently.
We recently proposed a coherent Ising machine to solve NP-hard 3D Ising models efficiently using a laser network which could be implemented by semiconductor lasers, optical parametric oscillators or fiber mode locked lasers. The algorithm of coherent computer is quite new and different from existing quantum computing or quantum annealing, based on the minimum gain principle of a laser network. The numerical results we performed so far reasonably suggest the effective computational power of the proposed a coherent Ising machine. We also show our recent experimental result of four -site Ising model implementation.