Quantum neural network for generating quantum states

Quantum machine learning has become a research focus in quantum computation nowadays. One direction of quantum machine learning is developing quantum neural network based on parametrized quantum circuits. However, previous works of quantum neural network based on parameterized quantum circuits provide few systemic and general ways to introduce non-linear activation function. In the meantime, non-linear activation function is one of the most important parts in classical neural network as it makes the multi-layer neural network not work as a single layer. In this work, we give a new contruction of quantum neural network to introduce non-linear activation functions. To demonstrate the new approach, we present results of using the quantum neural network to generate ground states as well as excited states for different quantum chemistry systems. The generated states approximate exact states closely, which not only show the potential of the new construction of quantum neural network, but also may be a new approach to solve quantum chemistry problems.