# What models exist of Quantum Neural Networks?

There seem to be several research institutes around the world working on the concept of a quantum neural network, for instance Georgia Tech and Oxford University. Most however are reluctant to publish any of their work. This is probably because building a QNN is potentially much easier than an ordinary QC, and each institute wants to win the quantum race. Theoretically, it is simpler to build a QNN than a QC for one reason. Coherency. The superposition of many qubits decreases the resistance to noise in a QC, and noise can potentially collapse or decohere the superposition before a useful computation is achieved. However, since a QNN would not require very long periods or very many superpositions, per node, it would be less susceptible to noise, while still performing computation similar to, but many times faster (exponentially in fact) than a classical neural network. A QNN would presumably gain its exponential speed advantage through superposition of values entering and exiting a nod