Helical structures: The geometry of protein helices and nanotubes

In nature, helical structures arise when identical structural subunits combine sequentially, the orientational and translational relation between each unit and its predecessor remaining constant. A helical structure is thus generated by the repeated action of a screw transformation acting on a subunit. A plane hexagonal lattice wrapped round a cylinder provides a useful starting point for describing the helical conformations of protein molecules, for investigating the geometrical properties of carbon nanotubes, and for certain types of dense packings of equal spheres.

The γ-brass structure and the Boerdijk–Coxeter helix

The γ-brass structure was for a long time regarded as a modified bcc structure. It is more accurately described in terms of a 26-atom cluster consisting of four interpenetrating icosahedral clusters. An alternative description in terms of a 38-atom cluster is also illuminating. We discuss the γ-brass structure in terms of the packing of spheres and the packing of ‘almost regular’ tetrahedra and demonstrate a close relationship to the helical sphere packings investigated by Boerdijk, who considered the configuration of touching spheres centred at the vertices of a Coxeter helix, and extended it by adding an extra layer of spheres. Adding a further layer of spheres gives a rod-like structure in which every sphere of the original helix is surrounded by twelve others, configured as a somewhat distorted icosahedron. Thus each tetrahedron of the initial structure is then shared by four icosahedra. This 26-sphere cluster is a slightly distorted form of the 26-atom γ-brass cluster.

Grassmannian fusion frames and its use in block sparse recovery

Tight fusion frames which form optimal packings in Grassmannian manifolds are of interest in signal processing and communication applications. In this paper, we study optimal packings and fusion frames having a specific structure for use in block sparse recovery problems. The paper starts with a sufficient condition for a set of subspaces to be an optimal packing. Further, a method of using optimal Grassmannian frames to construct tight fusion frames which form optimal packings is given. Then, we derive a lower bound on the block coherence of dictionaries used in block sparse recovery. From this result, we conclude that the Grassmannian fusion frames considered in this paper are optimal from the block coherence point of view. (C) 2013 Elsevier B.V. All rights reserved.