Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Test of gyrotropic constitutive relations by specular light reflection

Open Access Open Access

Abstract

Gyrotropic media are generally characterized by skew symmetric (electric) permittivity and (magnetic) permeability tensors. There is wide belief, however, as expressed In both expository and research literature, that only the permittivity takes a tensorial form for intrinsically nonmagnetic materials whose electrooptic behavior is of interest. I show that neglect or inclusion of light-induced magnetic anisotropy leads to qualitatively different physical predictions (even in the simplest case of an isotropic optically active medium) for gyrotropic effects manifested in specular reflection from the surface of the medium rather than in light propagation through the interior of the medium. In particular, differential reflection of circularly polarized light differs markedly as a function of incident angle, reaching peak value either beyond Brewster angle or near normal incidence, depending on whether a tensorial or scalar expression, respectively, relates vectors H and B. A scalar relation also leads to internal inconsistencies such as slight violations of energy conservation. The differences in constitutive relations are most significant on implementation of electromagnetic boundary conditions. This accounts for why light-induced magnetic anisotropy Influences differential light reflection but not optical rotation or circular dichroism.

© 1985 Optical Society of America

PDF Article
More Like This
Reflection vs transmission holograms in energy-related applications

J. Jannson, T. Jannson, and R. Winston
FH5 OSA Annual Meeting (FIO) 1985

Observing angular deviations in specular reflection of light

M. Merano, A. Aiello, M. P. van Exter, and J. P. Woerdman
CWI6 Conference on Lasers and Electro-Optics (CLEO:S&I) 2009

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.