Computer Algorithms for Detecting Polarization Maps for Polymer Homogeneity Control in Printing Industry

This scientific paper presents, in a concise and systematic way, new results for traditional laser polarization introspection methods of investigating the polycrystalline architectonics of phase-inhomogeneous polymer layers, which, in addition to linear and circular birefringence, also possess optically anisotropic absorption. Such optically anisotropic mechanisms include linear and circular dichroism. The presence of such mechanisms results in phase shifts between orthogonally (linearly and circularly) polarized components of complex laser emission amplitudes. This results in diagnostic ambiguity in the differentiation of polarization manifestations of birefringence and dichroism mechanisms. We propose a new algorithm for differential Mueller matrix reconstruction of linear and circular dichroism parameters by analytical decomposition of the Mueller polarization matrix in the basis of polarization (1st order differential matrix) and depolarization (2nd order differential matrix) components. This work is aimed at generalization of laser polarimetry methods to the case of partially depolarizable optically anisotropic methyl acrylate layers. A method of experimental determination of the specified partial matrix operators and a statistical evaluation of reconstructed coordinate distributions of random values of amplitude anisotropy parameters have been developed. On this theoretical-experimental basis the method of differential mapping of Mueller matrix for reproduction of linear and circular birefringence and dichroism parameter distributions of partially depolarized methyl acrylate layers has been proposed and experimentally proved. Within the framework of the statistical approach the most sensitive diagnostic parameters are determined - the statistical moments of higher pore moments, which characterize the asymmetry and excess of the Mueller matrix coordinate distributions of the linear and circular dichroism parameter distributions.