Higher order derivatives of quantum neural networks with barren plateaus
Higher order derivatives of quantum neural networks with barren plateaus
Abstract Quantum neural networks (QNNs) offer a powerful paradigm for programming near-term quantum computers and have the potential to speed up applications ranging from data science to chemistry to materials science. However, a possible obstacle to realizing that speed-up is the barren plateau (BP) phenomenon, whereby the gradient vanishes exponentially …