Non-Destructive Discrimination of arbitrary set of orthogonal quantum states by NMR using Quantum Phase Estimation

An algorithm based on quantum phase estimation, which discriminates quantum states nondestructively within a set of arbitrary orthogonal states, is described and experimentally verified by a NMR quantum information processor. The procedure is scalable and can be applied to any set of orthogonal states. Scalability is demonstrated through Matlab simulation

Singlet state creation and Universal quantum computation in NMR using Genetic Algorithm

Experimental implementation of a quantum algorithm requires unitary operator decomposition. Here we treat the unitary operator decomposition as an optimization problem and use Genetic Algorithm, a global optimization method inspired by nature's evolutionary process for operator decomposition. As an application, we apply this to NMR Quantum Information Processing and find a probabilistic way of doing universal quantum computation using global hard pulses. We also demonstrate efficient creation of singlet state (as a special case of Bell state) directly from thermal equilibrium using an optimum sequence of pulses

Turbulent flow in graphene

We demonstrate the possibility of a turbulent flow of electrons in graphene in the hydrodynamic region, by calculating the corresponding turbulent probability density function. This is used to calculate the contribution of the turbulent flow to the conductivity within a quantum Boltzmann approach. The dependence of the conductivity on the system parameters arising from the turbulent flow is very different from that due to scattering.Comment: 4 pages, Latex file, Journal versio

Sufficient Conditions for Starlike Functions Associated with the Lemniscate of Bernoulli

Let -1\leq B<A\leq 1. Condition on \beta, is determined so that 1+\beta zp'(z)/p^k(z)\prec(1+Az)/(1+Bz)\;(-1<k\leq3) implies p(z)\prec \sqrt{1+z}. Similarly, condition on \beta is determined so that 1+\beta zp'(z)/p^n(z) or p(z)+\beta zp'(z)/p^n(z)\prec\sqrt{1+z}\;(n=0, 1, 2) implies p(z)\prec(1+Az)/(1+Bz) or \sqrt{1+z}. In addition to that condition on \beta is derived so that p(z)\prec(1+Az)/(1+Bz) when p(z)+\beta zp'(z)/p(z)\prec\sqrt{1+z}. Few more problems of the similar flavor are also considered

VEWS: A Wikipedia Vandal Early Warning System

We study the problem of detecting vandals on Wikipedia before any human or known vandalism detection system reports flagging potential vandals so that such users can be presented early to Wikipedia administrators. We leverage multiple classical ML approaches, but develop 3 novel sets of features. Our Wikipedia Vandal Behavior (WVB) approach uses a novel set of user editing patterns as features to classify some users as vandals. Our Wikipedia Transition Probability Matrix (WTPM) approach uses a set of features derived from a transition probability matrix and then reduces it via a neural net auto-encoder to classify some users as vandals. The VEWS approach merges the previous two approaches. Without using any information (e.g. reverts) provided by other users, these algorithms each have over 85% classification accuracy. Moreover, when temporal recency is considered, accuracy goes to almost 90%. We carry out detailed experiments on a new data set we have created consisting of about 33K Wikipedia users (including both a black list and a white list of editors) and containing 770K edits. We describe specific behaviors that distinguish between vandals and non-vandals. We show that VEWS beats ClueBot NG and STiki, the best known algorithms today for vandalism detection. Moreover, VEWS detects far more vandals than ClueBot NG and on average, detects them 2.39 edits before ClueBot NG when both detect the vandal. However, we show that the combination of VEWS and ClueBot NG can give a fully automated vandal early warning system with even higher accuracy.Comment: To appear in Proceedings of the 21st ACM SIGKDD Conference of Knowledge Discovery and Data Mining (KDD 2015

Synthesis and superconductivity of new BiS2 based superconductor PrO0.5F0.5BiS2

We report synthesis and superconductivity at 3.7K in PrO0.5F0.5BiS2. The newly discovered material belongs to the layered sulfide based REO0.5F0.5BiS2 compounds having ZrCuSiAs type structure. The bulk polycrystalline compound is synthesized by vacuum encapsulation technique at 7800C in single step. Detailed structural analysis has shown that the as synthesized PrO0.5F0.5BiS2 is crystallized in tetragonal P4/nmm space group with lattice parameters a = 4.015(5) {\AA}, c = 13.362(4) {\AA}. Bulk superconductivity is observed in PrO0.5F0.5BiS2 below 4K from magnetic and transport measurements. Electrical transport measurements showed superconducting transition temperature (Tc) onset at 3.7K and Tc ({\rho}=0) at 3.1K. Hump at Tc related to superconducting transition is not observed in heat capacity measurement and rather a Schottky-type anomaly is observed at below ~6K. The compound is slightly semiconducting in normal state. Isothermal magnetization (MH) exhibited typical type II behavior with lower critical field (Hc1) of around 8Oe.Comment: Short note 10 pages text+figs. First report on PrO.5F.5BiS2 Su