Machine learning (ML) encompasses a broad range of algorithms and modeling tools used
for a vast array of data processing tasks, which has entered most scientific disciplines in …

Quantum matter, the research field studying phases of matter whose properties are
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …

The power of any kind of network approach lies in the ability to simplify a complex system so
that one can better understand its function as a whole. Sometimes it is beneficial, however …

A great variety of systems in nature, society and technology–from the web of sexual contacts
to the Internet, from the nervous system to power grids–can be modeled as graphs of …

In this book, we provide a comprehensive introduction to the most recent advances in the
application of machine learning methods in quantum sciences. We cover the use of deep …

Many biological and man-made networked systems are characterized by the simultaneous
presence of different sub-networks organized in separate layers, with links and nodes of …

Amorphous solids lack long-range order. Therefore identifying structural defects—akin to
dislocations in crystalline solids—that carry plastic flow in these systems remains a daunting …

Physical systems differing in their microscopic details often display strikingly similar
behaviour when probed at macroscopic scales. Those universal properties, largely …

Neutron and x-ray scattering represent two classes of state-of-the-art materials
characterization techniques that measure materials structural and dynamical properties with …

Many network systems are composed of interdependent but distinct types of interactions,
which cannot be fully understood in isolation. These different types of interactions are often …