Quantum Neural Networks(QNN) is composed of several quantum neurons in a certain topological structure. It is a method that attempts to combine the artificial neural network model with the advantages of quantum information. It is still in the research stage.

QNN Purpose of the study

In big data applications, traditional neural network models are difficult to train, so researchers are trying to use the characteristics of quantum computing as a resource.

The ontological explanation of quantum and the complete theory of perceptron brain processes have the same mathematical structure, The dynamic equations of both processes involve a field, and the quantum process based on quantum potential and the brain process based on neural potential have striking similarities, which also promotes the integration of the two.

The main research directions of QNN

1. Use the connection concept of neural network to construct quantum computers, and use neural network models to study problems in quantum computing;
2. Construct neural networks based on quantum computers or quantum devices, and use the ultra-high speed, ultra-parallelism, and exponential capacity of quantum computing to improve the structure and performance of neural networks;
3. As a hybrid intelligent optimization algorithm implemented on a conventional computer;
4. This will allow for in-depth research into brain science and cognitive science.

The main research directions of QNN

(1) Use the connection concept of neural networks to construct quantum computers and use neural network models to study problems in quantum computing;

(2) Constructing neural networks based on quantum computers or quantum devices, and using the ultra-high speed, ultra-parallelism, and exponential capacity of quantum computing to improve the structure and performance of neural networks;

(3) As a hybrid intelligent optimization algorithm implemented on a conventional computer;

(4) To conduct in-depth research on brain science and cognitive science.

Potential advantages of QNNs

The research on quantum neural computing (QNC) based on quantum neural networks is still in its infancy, but it has the following advantages over traditional neural computing:

1. Exponential memory capacity and recall speed;
2. Smaller network size and simpler network topology;
3. Better stability and effectiveness;
4. the ability to learn quickly, learn all at once, and process information at high speed;
5. Eliminate the potential for catastrophic amnesia.

Related words: quantum, neural network, quantum computing