Uploaded May 2026 | Updated September 2026, 3 weeks ago
Recorded 18 May 2026. Florian Schaefer of New York University presents "Information geometric regularization for sensitivities of flows with shocks" at IPAM's Multi-Fidelity Methods to Enable Robust Optimization and Real-Time Control of Fusion Processes Workshop.
Abstract: Shock waves in high-speed gas dynamics cause severe numerical difficulties for classical solvers and scientific machine learning. They are fundamentally a multiscale problem: While viscous effects ensure smoothness on microscopic scales, shocks manifest as macroscopic discontinuities. This talk begins with the observation that shock formation arises from the flow map reaching the boundary of the manifold of diffeomorphisms. We modify its geometry such that geodesics approach but never reach the boundary. The resulting information geometric regularization (IGR) has smooth solutions while avoiding the excessive dissipation of viscous regularizations, accelerating and simplifying the simulation of flows with shocks. Being a PDE-based regularization, IGR admits a continuous adjoint equation. Thus, it enables the efficient computation of sensitivities for design optimization and uncertainty quantification.
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-iv-multi-fidelity-methods-to-enable-robust-optimization-and-real-time-control-of-fusion-processes/?tab=overview
Recorded 18 May 2026. Florian Schaefer of New York University presents "Information geometric regularization for sensitivities of flows with shocks" at IPAM's Multi-Fidelity Methods to Enable Robust Optimization and Real-Time Control of Fusion Processes Workshop.
Abstract: Shock waves in high-speed gas dynamics cause severe numerical difficulties for classical solvers and scientific machine learning. They are fundamentally a multiscale problem: While viscous effects ensure smoothness on microscopic scales, shocks manifest as macroscopic discontinuities. This talk begins with the observation that shock formation arises from the flow map reaching the boundary of the manifold of diffeomorphisms. We modify its geometry such that geodesics approach but never reach the boundary. The resulting information geometric regularization (IGR) has smooth solutions while avoiding the excessive dissipation of viscous regularizations, accelerating and simplifying the simulation of flows with shocks. Being a PDE-based regularization, IGR admits a continuous adjoint equation. Thus, it enables the efficient computation of sensitivities for design optimization and uncertainty quantification.
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-iv-multi-fidelity-methods-to-enable-robust-optimization-and-real-time-control-of-fusion-processes/?tab=overview
