How to quantify textures and random fields in astrophysics?

Extracting information from stochastic fields is a ubiquitous task in science. However, from cosmology to biology, it tends to be done either through a power spectrum analysis, which is often too limited, or the use of neural networks, which require large training sets and lack interpretability.
I will present a new powerful tool called the “scattering transform” which stands nicely between the two extremes, and recent updates to extend this idea. I will use various examples in astrophysics and beyond to demonstrate its power, interpretability, and its advantage over traditional statistics.

Dr. Sihao Cheng, Institute for Advanced Study at Princeton and Perimeter Institute
Shu Qi meeting room
Tuesday, December 26, 2023 - 1:30PM to Tuesday, December 26, 2023 - 2:30PM