Newton Howard

A Coherence Law for Trainability in Noisy Equivariant Quantum Neural Networks

Hassan Ugail, Newton Howard

Symmetry provides a quantum neural network structure, but on its own it does not keep the network trainable once noise is present. We ask which physical quantity decides whether the gradients of an equivariant circuit survive decoherence, and we answer with a compact training law…Read more