Comment on "Vortex Liquid Crystal in Anisotropic Type II Superconductors"

This is a Comment on "Vortex Liquid Crystal in Anisotropic Type II Superconductors" by E. W. Carlson et al. in PRL, vol.90, 087001 (2003) [cond-mat/0209175].Comment: 2 pages, 1 figure, revised versio

Possible Dynamic States in Inductively Coupled Intrinsic Josephson Junctions of Layered High-TcT_c Superconductors

Based on computer simulations and theoretical analysis, a new dynamic state is found in inductively coupled intrinsic Josephson junctions in the absence of an external magnetic field. In this state, the plasma oscillation is uniform along the c axis and there are $(2m+1)\pi$ phase kinks, with $m$ being an integer, periodic and thus non-uniform in the $c$ direction. In the IV characteristics, the state manifests itself as current steps occurring at all cavity modes. Inside the current steps, the plasma oscillation becomes strong, which generates several harmonics in frequency spectra at a given voltage. The recent experiments on terahertz radiations from the mesa of a BSCCO single crystal can be explained in terms of this state.Comment: 4 pages, 5 figures; to appear in Phys. Rev. Lett.

Instance and Output Optimal Parallel Algorithms for Acyclic Joins

Massively parallel join algorithms have received much attention in recent years, while most prior work has focused on worst-optimal algorithms. However, the worst-case optimality of these join algorithms relies on hard instances having very large output sizes, which rarely appear in practice. A stronger notion of optimality is {\em output-optimal}, which requires an algorithm to be optimal within the class of all instances sharing the same input and output size. An even stronger optimality is {\em instance-optimal}, i.e., the algorithm is optimal on every single instance, but this may not always be achievable. In the traditional RAM model of computation, the classical Yannakakis algorithm is instance-optimal on any acyclic join. But in the massively parallel computation (MPC) model, the situation becomes much more complicated. We first show that for the class of r-hierarchical joins, instance-optimality can still be achieved in the MPC model. Then, we give a new MPC algorithm for an arbitrary acyclic join with load O ({\IN \over p} + {\sqrt{\IN \cdot \OUT} \over p}), where \IN,\OUT are the input and output sizes of the join, and $p$ is the number of servers in the MPC model. This improves the MPC version of the Yannakakis algorithm by an O (\sqrt{\OUT \over \IN} ) factor. Furthermore, we show that this is output-optimal when \OUT = O(p \cdot \IN), for every acyclic but non-r-hierarchical join. Finally, we give the first output-sensitive lower bound for the triangle join in the MPC model, showing that it is inherently more difficult than acyclic joins