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Center for Nonlinear Studies |
For decades now demonstration of truly useful large scale quantum computing, with all its tantalizing possibilities, has been "ten years" away. There are four major obstacles: algorithm construction; scaleup; noise; and decoherence. In this talk I will show that a quantum system, acting as a neural network, can construct its own algorithms by learning; that scaleup can be accomplished through "bootstrapping"; and that these systems, and their learning algorithms, are robust to noise and decoherence.
Host: Yigit Subasi