Effects of noise on the overparametrization of quantum neural networks

arXiv:2302.05059v2 Announce Type: replace-cross
Abstract: Overparametrization is one of the most surprising and notorious phenomena in machine learning. Recently, there have been several efforts to study if, and how, Quantum Neural Networks (QNNs) acting in the absence of hardware noise can be overparametrized. In particular, it has been proposed that a QNN can be defined as overparametrized if it has enough parameters to explore all available directions in state space. That is, if the rank of the Quantum Fisher Information …

abstract acting arxiv cs.lg effects hardware machine machine learning networks neural networks noise quant-ph quantum quantum neural networks stat.ml study type