Geometric analysis of metric spaces is a vibrant research area at the interface of analysis, geometry and topology. It examines the intrinsic structure of spaces endowed with a notion of distance, ...

The study of diffeomorphism groups equipped with Sobolev metrics has emerged as a powerful framework for understanding the intricate interplay between infinite‐dimensional geometry and nonlinear ...

The newly developed Huber mean provides a more stable and reliable way to compute averages for data lying on curved geometric spaces, or Riemannian manifolds. By combining the strengths of ...

Saksman's research deals with several mathematical problem areas that involve probabilistic questions in various setups. These include probabilistic methods in mathematical physics, analysis and ...

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design. In addition, Nature has recently ...

Guillaume Aubrun and I wrote a book focused on the interface between mathematical aspects of Quantum Information Theory and local theory of Banach spaces, a field which studies the properties of (very ...

Geometric optics is a confusing subject for many physics students, who often first encounter the subject in introductory college physics classes. Traditional instruction in geometric optics is not as ...

Learn how the geometric mean measures portfolio performance, focusing on compounding effects to provide a more accurate average return than the arithmetic mean.