Selime Gurol: June 8, 2012
Preconditioning and globalizing Krylov subspace methods in dual space for nonlinear least-squares problems
Selime GUROL, CERFACS
Friday, June 8, 10:30 a.m. in the CERFACS conference room
Abstract:
The problem considered in this talk is the data assimilation problem arising in weather forecasting
and oceanography, which consists in estimating the initial condition of a dynamical system whose
future behaviour is to be predicted. More specifically, new optimization techniques will be discussed
for the iterative solution of the particular nonlinear least-squares formulation of this inverse problem
known under the name of 4DVAR, for four-dimensional data assimilation.
These new methods are designed to decrease the computational cost in applications where the number
of variables involved is expected to exceed $109$. They involve the exploitation of the problem’s underlying
geometrical structure in reformulating standard trust-region techniques into
significantly cheaper variants. Adapted preconditioning issues for the
considered systems of equations will be discussed, which also depend on the problem’s geometrical
structure and which exploit limited-memory techniques in a novel way.
and oceanography, which consists in estimating the initial condition of a dynamical system whose
future behaviour is to be predicted. More specifically, new optimization techniques will be discussed
for the iterative solution of the particular nonlinear least-squares formulation of this inverse problem
known under the name of 4DVAR, for four-dimensional data assimilation.
These new methods are designed to decrease the computational cost in applications where the number
of variables involved is expected to exceed $109$. They involve the exploitation of the problem’s underlying
geometrical structure in reformulating standard trust-region techniques into
significantly cheaper variants. Adapted preconditioning issues for the
considered systems of equations will be discussed, which also depend on the problem’s geometrical
structure and which exploit limited-memory techniques in a novel way.
