This is a quantum machine learning project in which we apply artificial neural networks to quantum states. In quantum physics, every system is described by a state, i.e. a matrix made of complex numbers and enclosing physical information about the physical quantities of the system.
The state of a system made of two entities such as particles can be entangled or separable. When it is entangled, we cannot know completely either one of the two entities independently from the other. Someway, we could figuratively say that the single parties of this system behave as a whole one. When this does not happen, the state is separable or unentangled.
Let us now suppose to have the numerical expression of a matrix corresponding to a quantum state. The question we address in this project is: can we feed an artificial neural network with such matrix, in order to obtain the prediction entangled state/separable state?