3 papers
math.CA2021
Dynamically learning the parameters of a chaotic system using partial observations
Elizabeth Carlson, Joshua Hudson, Adam Larios +3
Motivated by recent progress in data assimilation, we develop an algorithm to dynamically learn the parameters of a chaotic system from partial observations. Under reasonable assum…
math.AP2020
Sensitivity Analysis for the 2D Navier-Stokes Equations with Applications to Continuous Data Assimilation
Adam Larios, Elizabeth Carlson
We rigorously prove the well-posedness of the formal sensitivity equations with respect to the Reynolds number corresponding to the 2D incompressible Navier-Stokes equations. Moreo…
math.AP2018
Parameter Recovery and Sensitivity Analysis for the 2D Navier-Stokes Equations Via Continuous Data Assimilation
Elizabeth Carlson, Joshua Hudson, Adam Larios
We study a continuous data assimilation algorithm proposed by Azouani, Olson, and Titi (AOT) in the context of an unknown Reynolds number. We determine the large-time error between…