ERC Consolidator Grant · 2023
New Frontiers in Optimal Adaptivity
The ultimate goal of any numerical method is to achieve maximal accuracy with minimal computational cost. This is also the driving motivation behind adaptive mesh refinement algorithms to approximate partial differential equations (PDEs). PDEs are the foundation of almost every simulation in computational physics (from classical mechanics to geophysics, astrophysics, hydrodynamics, and micromagnetism) and even in computational finance and machine learning. Without adaptive mesh refinement such simulations fail to reach significant accuracy even on the strongest computers before running out of memory or time. The goal of adaptivity is to achieve a mathematically guaranteed optimal accuracy…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.