Quantum mechanics is the fundamental theory in physics which studies any object at its smallest scale of energy levels like atoms and sub atoms. A quantum computer is a device that performs quantum computing using quantum mechanical phenomena such as superposition and entanglement. Traditional binary electronic computers perform computing using data which are binary encoded whereas the quantum computers use quantum bits also known as qubits.

Quantum computers might solve many problems much faster than the traditional machines that use binary computing. The most advanced algorithm that classical computers use is Shor’s algorithm might be outdone by algorithm of quantum computers. AlphaGo is a computer program that uses neural networks to recognize visual patterns, and they are capable of learning also.

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In a paper presented at the Max Plank Institute in Erlangen, it is demonstrated that the artificial neural networks with an AlphaGo inspired network are capable of learning and detecting any error efficiently using the quantum error correction technique. According to the thesis, with proper approach, quantum error detection technique will be able to outsmart the existing error detection techniques. Unlike the traditional computer which can adopt only states, quantum computers can adopt both these states and also the superposition of both these states. There are multiple qubits superimposed on each other, which makes the processing power of the quantum computers very fast. With this processing power, quantum computers can solve complex problems which the classic computers are doomed to fail. The only drawback of quantum computers is it’s high sensitivity with the environment. The researchers are planning to introduce an additional neural network that acts as a supervisor to the first network. This will enable the supervisor network to train the other network towards an effective quantum correction. The only catch is that the supervisor network needs to train itself of the quantum computer that is to be controlled.