In the search for dark matter (DM), one particular focus is on light and ultra-light dark matter, i.e. sub-GeV mass dark matter from a hidden dark sector with a new force interacting with the standard model or ultra-light DM with mass range from 10−22 eV to keV. The arguably most popular example of the latter class is the axion, invoked to solve the apparent absence of CP violation in Quantum Chromo Dynamics. Detection of these particles poses new challenges to potential sensor materials: very small energy depositions, magnetic properties and anisotropic response to particle interactions for example become crucial requirements. The challenge of finding suitable materials fits well with recent developments in solid state physics: Motivated by the exponential growth of computational power and the resulting data, we witness the rapid adoption of functional materials prediction within the framework of materials informatics. Here, methods adapted from computer science based on data-mining and machine learning are applied to identify materials with requested target properties.

The purpose of this winter school is to provide PHD students and young postdocs in the Nordic countries with introductory and advanced courses in a range of the most important topics in the field of theoretical cosmology. Furthermore, the school will provide a way to bring together students and young postdocs across different fields, research institutions and countries.

The question of how particles and droplets can grow in a turbulent environment is of great current interest in many fields, in astrophysics, cloud microphysics, in biology, and in the engineering sciences. For example, coagulation and condensation in turbulent clouds turn microscopic cloud droplets into rain drops. In astrophysics, planetesimals are thought to form by aggregation of microscopic dust grains in the turbulent environment surrounding a forming star. In both cases, turbulence is believed to be a crucial factor for particle growth. Yet the microscopic mechanisms determining this growth are far from understood. In the past few years there has been substantial progress in understanding the mechanisms that determine how particles move in turbulence, albeit mostly for simplified model systems. The challenge is now to understand how these mechanisms lead to rapid particle growth.