Relative periodic edge orbits in plane channel flow

A branch of genuine relative periodic orbits is found to be an edge state in plane Poiseuille flow in a periodic domain. These periodic solutions correspond to sinuous quasi-streamwise streaks periodically forced by sinuous quasi streamwise vortices in a self-sustained process. The rms-amplitude of the streaks is found to scale as ≈ Re-0.8, while that of the quasi-streamwise vortices scales like ≈ Re-1.6

Signals of Leptophilic Dark Matter at the ILC

Adopting a model independent approach, we constrain the various effective interactions of leptophilic DM particle with the visible world from the WMAP and Planck data. The thermally averaged indirect DM annihilation cross-section and the DM-electron direct-detection cross-section for such a DM candidate are observed to be consistent with the respective experimental data. We study the production of cosmologically allowed leptophilic DM in association with $Z\, (Z\to f\bar f)$, $f\equiv q,\,e^-,\, \mu^-$ at the ILC. We perform the $\chi^2$ analysis and compute the 99\% C.L. acceptance contours in the $m_\chi$ and $\Lambda$ plane from the two dimensional differential distributions of various kinematic observables obtained after employing parton showering and hadronization to the simulated data. We observe that the dominant hadronic channel provides the best kinematic reach of 2.62 TeV ($m_\chi$ = 25 GeV), which further improves to 3.13 TeV for polarized beams at $\sqrt{s} = 1$ TeV and an integrated luminosity of 1 ab$^{-1}$.Comment: 17 pages, 10 figures, 5 table

Large negative magnetoresistance in a ferromagnetic shape memory alloy : Ni_{2+x}Mn_{1-x}Ga

5% negative magnetoresistance (MR) at room temperature has been observed in bulk Ni_{2+x}Mn_{1-x}Ga. This indicates the possibility of using Ni_{2+x}Mn_{1-x}Ga as magnetic sensors. We have measured MR in the ferromagnetic state for different compositions (x=0-0.2) in the austenitic, pre-martensitic and martensitic phases. MR is found to increase with x. While MR for x=0 varies almost linearly in the austenitic and pre-martensitic phases, in the martensitic phase it shows a cusp-like shape. This has been explained by the changes in twin and domain structures in the martensitic phase. In the austenitic phase, which does not have twin structure, MR agrees with theory based on s-d scattering model.Comment: 3 pages, 3 figures, Appl. Phys. Lett 86, 202508 (2005

Fast algorithms for matching CCD images to a stellar catalogue

Two new algorithms are described for matching two dimensional coordinate lists of point sources that are signifcantly faster than previous methods. By matching rarely occurring triangles (or more complex shapes) in the two lists, and by ordering searches by decreasing probability of success, it is demonstrated that very few candidates need be considered to find a successful match. Moreover, by immediately testing the suitability of a potential match using an efficient mechanism, the need to process the entire candidate set is avoided, yielding considerable performance improvements. Triangles are described by a cosine metric that reduces the density of triangle space, permitting efficient searches. An alternative shape characterization method that reduces computational overhead in the construction phase is discussed. The algorithms are tested on a set of 10 063 wide-field survey images, with fields-of-view up to 4.8 x 3.6 deg, successfully matching 100% of the images in a mean elapsed time of 6 ms (2.4 GHz Athlon CPU). The elapsed time of the searching phase is shown to vary by less than 1 ms for list sizes between 10 and 200 points, demonstrating that fast, robust searches may be completed in nearly constant time, independent of list size.Comment: Accepted for publication in Publications of the Astronomical Society of Australi

VideoCapsuleNet: A Simplified Network for Action Detection

The recent advances in Deep Convolutional Neural Networks (DCNNs) have shown extremely good results for video human action classification, however, action detection is still a challenging problem. The current action detection approaches follow a complex pipeline which involves multiple tasks such as tube proposals, optical flow, and tube classification. In this work, we present a more elegant solution for action detection based on the recently developed capsule network. We propose a 3D capsule network for videos, called VideoCapsuleNet: a unified network for action detection which can jointly perform pixel-wise action segmentation along with action classification. The proposed network is a generalization of capsule network from 2D to 3D, which takes a sequence of video frames as input. The 3D generalization drastically increases the number of capsules in the network, making capsule routing computationally expensive. We introduce capsule-pooling in the convolutional capsule layer to address this issue which makes the voting algorithm tractable. The routing-by-agreement in the network inherently models the action representations and various action characteristics are captured by the predicted capsules. This inspired us to utilize the capsules for action localization and the class-specific capsules predicted by the network are used to determine a pixel-wise localization of actions. The localization is further improved by parameterized skip connections with the convolutional capsule layers and the network is trained end-to-end with a classification as well as localization loss. The proposed network achieves sate-of-the-art performance on multiple action detection datasets including UCF-Sports, J-HMDB, and UCF-101 (24 classes) with an impressive ~20% improvement on UCF-101 and ~15% improvement on J-HMDB in terms of v-mAP scores