Adiabatic quantum computing (AQC) started as an approach to solving optimization
problems and has evolved into an important universal alternative to the standard circuit …

Many questions of fundamental interest in today's science can be formulated as inference
problems: some partial, or noisy, observations are performed over a set of variables and the …

In this paper we extend our previous work on the stochastic block model, a commonly used
generative model for social and biological networks, and the problem of inferring functional …

We present an asymptotically exact analysis of the problem of detecting communities in
sparse random networks generated by stochastic block models. Using the cavity method of …

In this review article we discuss connections between the physics of disordered systems,
phase transitions in inference problems, and computational hardness. We introduce two …

We consider the problem of coloring the vertices of a large sparse random graph with a
given number of colors so that no adjacent vertices have the same color. Using the cavity …

With current semiconductor technology reaching its physical limits, special-purpose
hardware has emerged as an option to tackle specific computing-intensive challenges …

Among various algorithms designed to exploit the specific properties of quantum computers
with respect to classical ones, the quantum adiabatic algorithm is a versatile proposition to …

We derive analytical solutions for p-spin models with finite connectivity at zero temperature.
These models are the statistical mechanics equivalent of p-XORSAT problems in theoretical …

We model a close-knit community of friends and enemies as a fully connected network with
positive and negative signs on its edges. Theories from social psychology suggest that …