Astrophysical Configurations with Background Cosmology: Probing Dark Energy at Astrophysical Scales

We explore the effects of a positive cosmological constant on astrophysical and cosmological configurations described by a polytropic equation of state. We derive the conditions for equilibrium and stability of such configurations and consider some astrophysical examples where our analysis may be relevant. We show that in the presence of the cosmological constant the isothermal sphere is not a viable astrophysical model since the density in this model does not go asymptotically to zero. The cosmological constant implies that, for polytropic index smaller than five, the central density has to exceed a certain minimal value in terms of the vacuum density in order to guarantee the existence of a finite size object. We examine such configurations together with effects of $\Lambda$ in other exotic possibilities, such as neutrino and boson stars, and we compare our results to N-body simulations. The astrophysical properties and configurations found in this article are specific features resulting from the existence of a dark energy component. Hence, if found in nature would be an independent probe of a cosmological constant, complementary to other observations.Comment: 23 pages, 11 figures, 2 tables. Reference added. Mon. Not. Roy. Astro. Soc in prin

Symmetron with a non-minimal kinetic term

We investigate the compatibility of the Symmetron with dark energy by introducing a non-minimal kinetic term associated with the Symmetron. In this new model, the effect of the friction term appearing in the equation of motion of the Symmetron field becomes more pronounced due to the non-minimal kinetic term appearing in the action and, under specific conditions after symmetry breaking, the universe experiences an accelerating phase which, in spite of the large effective mass of the scalar field, lasts as long as the Hubble time $H_{0}$.Comment: 12 pages, 4 figures, to appear in JCA

Domain wall description of superconductivity

In the present work we shall address the issue of electrical conductivity in superconductors in the perspective of superconducting domain wall solutions in the realm of field theory. We take our set up made out of a dynamical complex scalar field coupled to gauge field to be responsible for superconductivity and an extra scalar real field that plays the role of superconducting domain walls. The temperature of the system is interpreted through the fact that the soliton following accelerating orbits is a Rindler observer experiencing a thermal bath.Comment: 9 pages, 5 figures, Latex. Version to appear in PL

Distributed Optimization With Local Domains: Applications in MPC and Network Flows

In this paper we consider a network with $P$ nodes, where each node has exclusive access to a local cost function. Our contribution is a communication-efficient distributed algorithm that finds a vector $x^\star$ minimizing the sum of all the functions. We make the additional assumption that the functions have intersecting local domains, i.e., each function depends only on some components of the variable. Consequently, each node is interested in knowing only some components of $x^\star$, not the entire vector. This allows for improvement in communication-efficiency. We apply our algorithm to model predictive control (MPC) and to network flow problems and show, through experiments on large networks, that our proposed algorithm requires less communications to converge than prior algorithms.Comment: Submitted to IEEE Trans. Aut. Contro

D-ADMM: A Communication-Efficient Distributed Algorithm For Separable Optimization

We propose a distributed algorithm, named Distributed Alternating Direction Method of Multipliers (D-ADMM), for solving separable optimization problems in networks of interconnected nodes or agents. In a separable optimization problem there is a private cost function and a private constraint set at each node. The goal is to minimize the sum of all the cost functions, constraining the solution to be in the intersection of all the constraint sets. D-ADMM is proven to converge when the network is bipartite or when all the functions are strongly convex, although in practice, convergence is observed even when these conditions are not met. We use D-ADMM to solve the following problems from signal processing and control: average consensus, compressed sensing, and support vector machines. Our simulations show that D-ADMM requires less communications than state-of-the-art algorithms to achieve a given accuracy level. Algorithms with low communication requirements are important, for example, in sensor networks, where sensors are typically battery-operated and communicating is the most energy consuming operation.Comment: To appear in IEEE Transactions on Signal Processin

Distributed Basis Pursuit

We propose a distributed algorithm for solving the optimization problem Basis Pursuit (BP). BP finds the least L1-norm solution of the underdetermined linear system Ax = b and is used, for example, in compressed sensing for reconstruction. Our algorithm solves BP on a distributed platform such as a sensor network, and is designed to minimize the communication between nodes. The algorithm only requires the network to be connected, has no notion of a central processing node, and no node has access to the entire matrix A at any time. We consider two scenarios in which either the columns or the rows of A are distributed among the compute nodes. Our algorithm, named D-ADMM, is a decentralized implementation of the alternating direction method of multipliers. We show through numerical simulation that our algorithm requires considerably less communications between the nodes than the state-of-the-art algorithms.Comment: Preprint of the journal version of the paper; IEEE Transactions on Signal Processing, Vol. 60, Issue 4, April, 201

Studies on the use of purified CBH I for oligosaccharide synthesis

The importance of biologically active carbohydrates has been recognized over the last decade. The availability of cheap oligosaccharides for biological activity studies is very reduced. The isolation of these compounds from natural sources is almost impossible, because of their very high specific activity. and consequently very low concentration in nature. As chemical synthesis is a difficult and time consuming, the enzymatic synthesis has been regarded over the last years as a very attractive methodology for oligosaccharide production. The main approach when utilizing glycanases for di- or trisaccharides synthesis has been the transglycosylation reaction. However, the isolation of products is quite complicated. On the other hand, the condensation reaction by reversed hydrolysis activity, which in many cases requires cheaper substrates. has a very low yield. In this work, a purified exoglucanase CBH I from the fungus Trichoderma reesei was analyzed for its reversed hydrolysis activity. The enzyme was purified by conventional methodologies (preparative isoelectric focusing, gel filtration on Sephacryl 100 HR, anionic exchange on a Mono Q column and cationic exchange on a Mono S column), from a commercial cellulase, Cellulast, from Novo. The activity of the purified enzyme on a large set of substrates, such as lichenan, laminarin, filter paper, acid swollen Avicel, xylan and carboxymethylcellulose was characterized, suggesting that it is basically free of contaminant activities. The enzyme was incubated in aqueous media with high sugar concentrations. Several mono- and disaccharides were used, in order to study the enzyme specificity. The obtained products were analyzed in a Dionex chromatographer using a CarboPac PA-100 column. The separated reaction products were analysed by NMR. The yields of the condensation reaction were in several cases considerably high