Quantum machine learning of graph-structured data

Understand

Graph structures are ubiquitous throughout the natural sciences.

• Here we consider graph-structured quantum data and describe how to carry out its quantum machine learning via quantum neural networks.
• In particular, we consider training data in the form of pairs of input and output quantum states associated with the vertices of a graph, together with edges encoding correlations between the vertices.
• We explain how to systematically exploit this additional graph structure to improve quantum learning algorithms.