In the past years, network theory has successfully characterized the interaction among the
constituents of a variety of complex systems, ranging from biological to technological, and …

We provide Ising formulations for many NP-complete and NP-hard problems, including all of
Karp's 21 NP-complete problems. This collects and extends map**s to the Ising model …

Do neural networks, trained on well-understood algorithmic tasks, reliably rediscover known
algorithms? Several recent studies, on tasks ranging from group operations to in-context …

The combination of the compactness of networks, featuring small diameters, and their
complex architectures results in a variety of critical effects dramatically different from those in …

Understanding the molecular determinants of specificity in protein–protein interaction is an
outstanding challenge of postgenome biology. The availability of large protein databases …

About sixty years ago, the anomalous magnetic response of certain magnetic alloys drew
the attention of theoretical physicists. It soon became clear that understanding these …

Today's computer–human interfaces are typically designed with the assumption that they are
going to be used by an able-bodied person, who is using a typical set of input and output …

Quantum annealing is a generic name of quantum algorithms that use quantum-mechanical
fluctuations to search for the solution of an optimization problem. It shares the basic idea …

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 …

Discovering the conditions under which an optimization algorithm or search heuristic will
succeed or fail is critical for understanding the strengths and weaknesses of different …