# What is Quantum Convolutional Neural Network?

I just came through the TensorFlow Quantum library they introduced Quantum Convolutional Neural Network.

• What is Quantum Convolutional Neural Network?
• What is the difference between CNN vs QCNN?

The circuit's input is an unknown quantum state $$\rho_{\text{in}}$$. A convolution layer applies a single quasi-local unitary ($$U_i$$) in a translationally-invariant manner for finite depth. For pooling, a fraction of qubits are measured, and their outcomes determine unitary rotations ($$V_j$$) applied to nearby qubits. Hence, nonlinearities in QCNN arise from reducing the number of degrees of freedom. Convolution and pooling layers are performed until the system size is sufficiently small; then, a fully connected layer is applied as a unitary $$F$$ on the remaining qubits. Finally, the outcome of the circuit is obtained by measuring a fixed number of output qubits. As in the classical case, circuit structures (i.e. QCNN hyperparameters) such as the number of convolution and pooling layers are fixed, and the unitaries themselves are learned.