A Topologically-informed Hyperstreamline Seeding Method for Alignment Tensor Fields

Abstract: A topologically-informed method is presented for seeding of hyperstreamlines for visualization of alignment tensor fields. The method is inspired by and applied to visualization of nematic liquid crystal (LC) reorientation dynamics simulations. The method distributes hyperstreamlines along domain boundaries and edges of a nearest-neighbor graph whose vertices are degenerate regions of the alignment tensor field, which correspond to orientational defects in a nematic LC domain. This is accomplished without iteration while conforming to a user-specified spacing between hyperstreamlines and avoids possible failure modes associated with hyperstreamline integration in the vicinity of degeneracies of alignment (orientational defects). It is shown that the presented seeding method enables automated hyperstreamline-based visualization of a broad range of alignment tensor fields which enhances the ability of researchers to interpret these fields and provides an alternative to using glyph-based techniques.