Causal vs Acausal Modeling By Example: Why Julia Scales (Chris Rackauckas, SciML)

is an acausal modeling language and its acuasal nature is one of the main tenants for why it has seen rapid adoption. But what even is “acausal modeling“ and why should you care? In this video we will dive into how Julia’s ModelingToolkit acausal modeling system differs from causal modeling systems like Simulink and why that helps one big large scale models with less human effort. We do this by showing examples of causal and acausal modeling on the RC circuit, demonstrating that (a) causal modeling is a subset of acausal modeling (b) acausal modeling allows for models to have more locality and (c) acausal models are much closer to the physical description and are thus easier to read and debug. Note that this video does not compare the differences between different acausal modeling systems. That will be a topic for a future video. Time Stamps: 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: Interested in improving the auto generated captions? Get involved here: