Study of QCD generalized ghost dark energy in FRW universe

A phenomenological generalized ghost dark energy model has been studied under the framework of FRW universe. In ghost dark energy model the energy density depends linearly on Hubble parameter (H) but in this dark energy model, the energy density contains a the sub-leading term which is depends on $\mathcal{O} (H^2)$, so the energy density takes the form $\rho_D=\alpha H+ \beta H^2$, where $\alpha$ and $\beta$ are the constants. The solutions of the Friedman equation of our model leads to a stable universe. We have fitted our model with the present observational data including Stern data set. With the help of best fit results we find the adiabatic sound speed remains positive throughout the cosmic evolution, that claims the stability of the model. The flipping of the signature of deceleration parameter at the value of scale factor $a=0.5$ indicates that the universe is at the stage of acceleration i.e. de Sitter phase of the universe at late time. Our model shows that the acceleration of the universe begin at redshift $z_{ace}\approx 0.617$ and the model is also consistent with the current observational data.Comment: 9 pages, 9 figure

Compact stars in f(R,T)f(R,T) gravity

In the present paper we generate a set of solutions describing the interior of a compact star under $f(R,T)$ theory of gravity which admits conformal motion. We consider the equation of state (EOS) $p=\omega\rho$ with $0<\omega<1$ for the fluid distribution consisting normal matter, $\omega$ being the EOS parameter. We therefore explore several aspects of the model analytically along with graphical representations to check the physical validity as well as acceptability of it within specified observational constraint in connection to a dozen of the compact star candidates. It is shown from the presented model that these objects are nothing but radiating compact stars.Comment: 16 pages, 6 figures, 1 table, substantial modification based on referee repor

Anisotropic stars with non-static conformal symmetry

We have proposed a model for relativistic compact star with anisotropy and analytically obtained exact spherically symmetric solutions describing the interior of the dense star admitting non-static conformal symmetry. Several features of the solutions including drawbacks of the model have been explored and discussed. For this purpose we have provided the energy conditions, TOV-equations and other physical requirements and thus thoroughly investigated stability, mass-radius relation and surface redshift of the model. It is observed that most of the features are well matched with the compact stars, like quark/strange stars.Comment: 18 pages, 14 figure

Randomized Composable Core-sets for Distributed Submodular Maximization

An effective technique for solving optimization problems over massive data sets is to partition the data into smaller pieces, solve the problem on each piece and compute a representative solution from it, and finally obtain a solution inside the union of the representative solutions for all pieces. This technique can be captured via the concept of {\em composable core-sets}, and has been recently applied to solve diversity maximization problems as well as several clustering problems. However, for coverage and submodular maximization problems, impossibility bounds are known for this technique \cite{IMMM14}. In this paper, we focus on efficient construction of a randomized variant of composable core-sets where the above idea is applied on a {\em random clustering} of the data. We employ this technique for the coverage, monotone and non-monotone submodular maximization problems. Our results significantly improve upon the hardness results for non-randomized core-sets, and imply improved results for submodular maximization in a distributed and streaming settings. In summary, we show that a simple greedy algorithm results in a $1/3$-approximate randomized composable core-set for submodular maximization under a cardinality constraint. This is in contrast to a known $O({\log k\over \sqrt{k}})$ impossibility result for (non-randomized) composable core-set. Our result also extends to non-monotone submodular functions, and leads to the first 2-round MapReduce-based constant-factor approximation algorithm with $O(n)$ total communication complexity for either monotone or non-monotone functions. Finally, using an improved analysis technique and a new algorithm $\mathsf{PseudoGreedy}$, we present an improved $0.545$-approximation algorithm for monotone submodular maximization, which is in turn the first MapReduce-based algorithm beating factor $1/2$ in a constant number of rounds

Charged anisotropic strange stars in Finslerian geometry

We investigate a simplified model for the strange stars in the framework of Finslerian spacetime geometry, composed of charged fluid. It is considered that the fluid consisting of three flavor quarks including a small amount of non-interacting electrons to maintain the chemical equilibrium and assumed that the fluid is compressible by nature. To obtain the simplified form of charged strange star we considered constant flag curvature. Based on geometry, we have developed the field equations within the localized charge distribution. We considered that the strange quarks distributed within the stellar system are compiled with the MIT bag model type of equation of state (EOS) and the charge distribution within the system follows a power law. We represent the exterior spacetime by the Finslerian Ressiner-Nordstr{\"o}m space-time. The maximum anisotropic stress is obtained at the surface of the system. Whether the system is in equilibrium or not, has been examined with respect to the Tolman-Oppenheimer-Volkoff (TOV) equation, Herrera cracking concept, different energy conditions and adiabatic index. We obtain that the total charge is of the order of 10$^{20}$ C and the corresponding electric field is of around 10$^{22}$ V/m. The central density and central pressure vary inversely with the charge. Varying the free parameter (charge constant) of the model, we find the generalized mass-radius variation of strange stars and determine the maximum limited mass with the corresponding radius. Furthermore, we also considered the variation of mass and radius against central density respectively.Comment: 21 pages, 13 figures, 4 table

Understanding Genomic Evolution of Olfactory Receptors through Fractal and Mathematical Morphology

Fractals and Mathematical Morphology are immensely used to study many problems in different branches of science and technology including the domain of Biology. There are many more unrevealed facts and figures of genes and genome in Computational Biology. In this paper, our objective is to explore how the evolutionary network is associated among Human, Chimpanzee and Mouse with regards to their genomic information. We are about to explore their genomic evolution through the quantitative measures of fractals and morphology. We have considered olfactory receptors for our case study. These olfactory receptors do function in different species with subtle differences in the structures of DNA sequences. Those subtle differences can be exposed through intricate details of Fractals and Mathematical Morphology

Simultaneous Inference of User Representations and Trust

Inferring trust relations between social media users is critical for a number of applications wherein users seek credible information. The fact that available trust relations are scarce and skewed makes trust prediction a challenging task. To the best of our knowledge, this is the first work on exploring representation learning for trust prediction. We propose an approach that uses only a small amount of binary user-user trust relations to simultaneously learn user embeddings and a model to predict trust between user pairs. We empirically demonstrate that for trust prediction, our approach outperforms classifier-based approaches which use state-of-the-art representation learning methods like DeepWalk and LINE as features. We also conduct experiments which use embeddings pre-trained with DeepWalk and LINE each as an input to our model, resulting in further performance improvement. Experiments with a dataset of $\sim$356K user pairs show that the proposed method can obtain an high F-score of 92.65%.Comment: To appear in the proceedings of ASONAM'17. Please cite that versio