e-Article
Experimental demonstration of adversarial examples in learning topological phases
Document Type
article
Author
Source
Nature Communications, Vol 13, Iss 1, Pp 1-8 (2022)
Subject
Language
English
ISSN
2041-1723
Abstract
Machine learning has been applied to problems in condensed matter physics, but its performance in an experimental setting needs testing. Zhang et al. study the effects of adversarial perturbations on a neural-network-based topological phase classifier, applied to experimental data from an NV center in diamond.