Mantle viscosity inference: a comparison between Simulated Annealing and Neighbourhood Algorithm inversion methods

Abstract

Two direct search methods, simulated annealing and neighbourhood algorithm, are applied to the inversion of the viscosity profile of the mantle using relative sea level time-histories for the Hudson Bay region. In problems characterized by a low-dimensional model space (Nd = 2 in this study), the two inversion methods show comparable performances. When a larger number of dimensions is involved (specifically Nd = 6), we directly show that simulated annealing is less effective than neighbourhood algorithm in overcoming the obstacles that are found in the model space when our specific data set is employed. This study confirms that modifications of the conventional Monte Carlo inversion method, such as simulated annealing and neighbourhood algorithm, are viable tools to determine the viscosity profile of the mantle, which, until recently, has been mainly tackled by means of linearized techniques.