Effectively compressing and optimizing tensor networks requires reliable methods for fixing
the latent degrees of freedom of the tensors, known as the gauge. Here we introduce a new …

Applications of drone technology are gradually becoming widespread all over the world.
Remote medical support, commodities transportation within due time, live-action movies …

Networks and network computations have become a primary mathematical tool for analyzing
the structure of many kinds of complex systems, ranging from the Internet and transportation …

Spectral methods offer a tractable, global framework for clustering in graphs via eigenvector
computations on graph matrices. Hypergraph data, in which entities interact on edges of …

Hypergraphs are higher-order networks that capture the interactions between two or more
nodes. Hypergraphs can always be represented by factor graphs, ie, bipartite networks …

The progress in high-performance computing makes it increasingly possible to build
detailed models to investigate spreading processes on complex networks. However, current …

Extended-range percolation is a robust percolation process that has relevance for quantum
communication problems. In extended-range percolation nodes can be trusted or untrusted …

Source inference aims at revealing the seed of the misinformation spreading on social
networks, and attracted great attention in the field of network science and cybersecurity …

We study tensor network states defined on an underlying graph which is sparsely
connected. Generic sparse graphs are expander graphs with a high probability, and one can …

Understanding the relationship between the heterogeneous structure of complex networks
and cooperative phenomena occurring on them remains a key problem in network science …