Quantum information processing relies on the precise control of non-classical states in the
presence of many uncontrolled environmental degrees of freedom. The interactions …

These are exciting times for quantum physics as new quantum technologies are expected to
soon transform computing at an unprecedented level. Simultaneously network science is …

The assumption that quantum systems relax to a stationary state in the long-time limit
underpins statistical physics and much of our intuitive understanding of scientific …

In the last years, a number of theoretical and numerical tools have been developed by a
thriving community formed by people coming from different backgrounds—condensed …

We define the topological Dirac equation describing the evolution of a topological wave
function on networks or on simplicial complexes. On networks, the topological wave function …

Complexity of patterns is key information for human brain to differ objects of about the same
size and shape. Like other innate human senses, the complexity perception cannot be easily …

The quantification of the entanglement present in a physical system is of paramount
importance for fundamental research and many cutting-edge applications. Now, achieving …

The study of phase transitions using data-driven approaches is challenging, especially
when little prior knowledge of the system is available. Topological data analysis is an …

Network science provides very powerful tools for extracting information from interacting data.
Although recently the unsupervised detection of phases of matter using machine learning …

In this review we discuss the latest results concerning development of the machine learning
algorithms for characterization of the magnetic skyrmions that are topologically-protected …