Quantum Machine Learning - Quantum Neural Network Algorithm

Описание: Quantum Machine Learning: Implementation of Quantum Neural Network Algorithm.
So recently scientists from the University of Pavia, led by professor Tacchino have written a paper claiming that they have
created the first working quantum neural network algorithm that can run on a real quantum device.
They showed that their quantum model of a perceptron can be used as an nonlinear classifier of simple patterns.
So this is how the perceptron model looks like:

An input array labeled as i is processed with a weight vector labeled as w to produce output function.
And then in order to prove exponential speedup, they made a quantum algorithm that consists of a quantum circuit
filled with quantum gates.
It looks like this:

So they are using quantum gates like the Hadamard gate, which maps x to z and z to x. This gate is required for
making superposition. They are also using the Pauli z-gate which is pi-rotation around the z axis. It is known
as a phase flip.

Scientists simulated their quantum algorithm on IBM Q simulator using 2 and 4 quantum bits and basically they showed that
their quantum algorithms presents an exponential advantage over classical perceptron models by representing and
classifying 4 bits strings using 2 quantum bits and 16 bits strings using 4 quantum bits.

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