Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution

Modeling symmetry breaking is essential for understanding the fundamental changes in the behaviors and properties of physical systems, from microscopic particle interactions to macroscopic phenomena like fluid dynamics and cosmic structures. Thus, identifying sources of asymmetry is an important tool for understanding physical systems. In this paper, we focus on learning asymmetries of data using relaxed group convolutions. We provide both theoretical and empirical evidence that this flexible convolution technique allows the model to maintain the highest level of equivariance …

breaking convolution cs.ai cs.lg dynamics fluid dynamics focus interactions modeling paper symmetry systems tool understanding