Information field theory (IFT) is information theory, the logic of reasoning under uncertainty, applied to fields. A field can be any quantity defined over some space, e.g. the air temperature over Europe, the magnetic field strength in the Milky Way, or the matter density in the Universe. IFT describes how data and knowledge can be used to infer field properties. Mathematically it is a statistical field theory and exploits many of the tools developed for such. Practically, it is a framework for signal processing and image reconstruction.
The IFT research group at MPA
- develops the conceptual and mathematical framework of IFT
- derives generic and targeted imaging algorithms within IFT
- develops the computational tools required for IFT algorithms
- applies IFT to measurement problems in cosmology, high energy astrophysics, and other areas.
Research on IFT requires an excellent mathematical training and/or good programming skills. More information can be found at the
IFT group page and the
