Using approximate secant equations in limited memory methods for multilevel unconstrained optimization

International audienceThe properties of multilevel optimization problems defined on a hierarchy of discretization grids can be used to define approximate secant equations, which describe the second-order behavior of the objective function. Following earlier work by Gratton and Toint (2009) we introduce a quasi-Newton method (with a linesearch) and a nonlinear conjugate gradient method that both take advantage of this new second-order information. We then present numerical experiments with these methods and formulate recommendations for their practical use

Numerical Methods for the Inverse Nonlinear Fourier Transform

We introduce a new numerical method for the computation of the inverse nonlinear Fourier transform and compare its computational complexity and accuracy to those of other methods available in the literature. For a given accuracy, the proposed method requires the lowest number of operationsComment: To be presented at the Tyrrhenian International Workshop on Digital Communications (TIWDC) 201