Bootstrapping Vector Fields

Vector fields play an essential role in a large range of scientific applications. They are commonly generated through computer simulations. Such simulations may be a costly process since they usually require high computational time. When researchers want to quantify the uncertainty in such kind of applications, usually an ensemble of vector fields realizations are generated, making the process much more expensive. In this work, we propose the use of the Bootstrap technique jointly with the Helmholtz-Hodge Decomposition as a tool for stochastic generation of vector fields. Results show that this technique is capable of generating a variety of realizations that can be used to quantify the uncertainty in applications that use vector fields as an input.