Scientists and engineers use computer models to study input/output relationships in complex physical systems. But thorough parameter studies are challenging—if not impossible—when the simulation is expensive and the model has several inputs. To enable such studies, the engineer may attempt to reduce the dimension of the model’s input space.
Active subspaces are an emerging set of dimension reduction tools that identify important directions in the parameter space. Reducing the dimension can enable otherwise infeasible parameter studies.