Very deep spectroscopy of the bright Saturn Nebula NGC 7009 -- I. Observations and plasma diagnostics

We present very deep CCD spectrum of the bright, medium-excitation planetary nebula NGC 7009, with a wavelength coverage from 3040 to 11000 A. Traditional emission line identification is carried out to identify all the emission features in the spectra, based on the available laboratory atomic transition data. Since the spectra are of medium resolution, we use multi-Gaussian line profile fitting to deblend faint blended lines, most of which are optical recombination lines (ORLs) emitted by singly ionized ions of abundant second-row elements such as C, N, O and Ne. Computer-aided emission-line identification, using the code EMILI developed by Sharpee et al., is then employed to further identify all the emission lines thus obtained. In total about 1200 emission features are identified, with the faintest ones down to fluxes 10^{-4} of H_beta. The flux errors for all emission lines, estimated from multi-Gaussian fitting, are presented. Plots of the whole optical spectrum, identified emission lines labeled, are presented along with the results of multi-Gaussian fits. Plasma diagnostics using optical forbidden line ratios are carried out. Also derived are electron temperatures and densities from the H I, He I and He II recombination spectrum.Comment: 66 pages, 16 figures, 7 tables, paper accepted by MNRAS in Marc

High-Order Dual-Port Quasi-Absorptive Microstrip Coupled-Line Bandpass Filters

In this article, we present the first demonstration of distributed and symmetrical all-band quasi-absorptive filters that can be designed to arbitrarily high orders. The proposed quasi-absorptive filter consists of a bandpass section (reflective-type coupled-line filter) and absorptive sections (a matched resistor in series with a shorted quarter-wavelength transmission line). Through a detailed analysis, we show that the absorptive sections not only eliminate out-of-band reflections but also determine the passband bandwidth (BW). As such, the bandpass section mainly determines the out-of-band roll-off and the order of the filter can be arbitrarily increased without affecting the filter BW by cascading more bandpass sections. A set of 2.45-GHz one-, two-, and three-pole quasi-absorptive microstrip bandpass filters are designed and measured. The filters show simultaneous input and output absorption across both the passband and the stopband. Measurement results agree very well with the simulation and validate the proposed design concept

Optical recombination lines as probes of conditions in planetary nebulae

Since the last IAU symposium on planetary nebulae (PNe), several deep spectroscopic surveys of the relatively faint optical recombination lines (ORLs) emitted by heavy element ions in PNe and H II regions have been completed. New diagnostic tools have been developed thanks to progress in the calculations of basic atomic data. Together, they have led to a better understanding of the physical conditions under which the various types of emission lines arise. The studies have strengthened the previous conjecture that nebulae contain another component of cold, high metallicity gas, which is too cool to excite any significant optical or UV CELs and is thus invisible via such lines. The existence of such a plasma component in PNe and possibly also in H II regions provides a natural solution to the long-standing problem in nebular astrophysics, i.e. the dichotomy of nebular plasma diagnostics and abundance determinations using ORLs and continua on the one hand and collisionally excited lines (CELs) on the other.Comment: 8 pages, 3 figures, review talk presented to the IAU Symposium #234, ``Planetary nebulae in our Galaxy and beyond'', held in Hawaii, USA, April 3-7 200

Exponential stabilization of a class of stochastic system with Markovian jump parameters and mode-dependent mixed time-delays

Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this technical note, the globally exponential stabilization problem is investigated for a general class of stochastic systems with both Markovian jumping parameters and mixed time-delays. The mixed mode-dependent time-delays consist of both discrete and distributed delays. We aim to design a memoryless state feedback controller such that the closed-loop system is stochastically exponentially stable in the mean square sense. First, by introducing a new Lyapunov-Krasovskii functional that accounts for the mode-dependent mixed delays, stochastic analysis is conducted in order to derive a criterion for the exponential stabilizability problem. Then, a variation of such a criterion is developed to facilitate the controller design by using the linear matrix inequality (LMI) approach. Finally, it is shown that the desired state feedback controller can be characterized explicitly in terms of the solution to a set of LMIs. Numerical simulation is carried out to demonstrate the effectiveness of the proposed methods.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation of Germany. Recommended by Associate Editor G. Chesi

Robust stability of two-dimensional uncertain discrete systems

Copyright [2003] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this letter, We deal with the robust stability problem for linear two-dimensional (2-D) discrete time-invariant systems described by a 2-D local state-space (LSS) Fornasini-Marchesini (1989) second model. The class of systems under investigation involves parameter uncertainties that are assumed to be norm-bounded. We first focus on deriving the sufficient conditions under which the uncertain 2-D systems keep robustly asymptotically stable for all admissible parameter uncertainties. It is shown that the problem addressed can be recast to a convex optimization one characterized by linear matrix inequalities (LMIs), and therefore a numerically attractive LMI approach can be exploited to test the robust stability of the uncertain discrete-time 2-D systems. We further apply the obtained results to study the robust stability of perturbed 2-D digital filters with overflow nonlinearities

A Bayesian network approach to explaining time series with changing structure

Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any model that is learnt from the data will average over the different dependency structures. Paradigms that try to explain underlying processes and observed events in multivariate time series must explicitly model these changes in order to allow non-experts to analyse and understand such data. In this paper we have developed a method for generating explanations in multivariate time series that takes into account changing dependency structure. We make use of a dynamic Bayesian network model with hidden nodes. We introduce a representa- tion and search technique for learning such models from data and test it on synthetic time series and real-world data from an oil refinery, both of which contain changing underlying structure. We compare our method to an existing EM-based method for learning structure. Results are very promising for our method and we include sample explanations, generated from models learnt from the refinery dataset

Inner product computation for sparse iterative solvers on\ud distributed supercomputer

Recent years have witnessed that iterative Krylov methods without re-designing are not suitable for distribute supercomputers because of intensive global communications. It is well accepted that re-engineering Krylov methods for prescribed computer architecture is necessary and important to achieve higher performance and scalability. The paper focuses on simple and practical ways to re-organize Krylov methods and improve their performance for current heterogeneous distributed supercomputers. In construct with most of current software development of Krylov methods which usually focuses on efficient matrix vector multiplications, the paper focuses on the way to compute inner products on supercomputers and explains why inner product computation on current heterogeneous distributed supercomputers is crucial for scalable Krylov methods. Communication complexity analysis shows that how the inner product computation can be the bottleneck of performance of (inner) product-type iterative solvers on distributed supercomputers due to global communications. Principles of reducing such global communications are discussed. The importance of minimizing communications is demonstrated by experiments using up to 900 processors. The experiments were carried on a Dawning 5000A, one of the fastest and earliest heterogeneous supercomputers in the world. Both the analysis and experiments indicates that inner product computation is very likely to be the most challenging kernel for inner product-based iterative solvers to achieve exascale

Is Optimal Monetary and Fiscal Policy in a Small Open Economy Time Consistent?

This paper studies optimal monetary and fiscal policy in a small open economy. Two forces in the economy impose orthogonal restrictions on financing costs across governments. The first force requires constant financing costs across governments to have time consistent optimal policy of hours. The second force always asks for time-varying financing costs across governments in order to have time consistency optimal policy of consumption and real money balances. Thus, optimal monetary and fiscal policy is time inconsistent. However, if preferences (and/or productivity) satisfy certain conditions, the former force disappears and optimal monetary and fiscal policy becomes time consistent. The results hold with both flexible exchange rate regimes and fixed exchange rate regimes. The latter indicates that a credible fixed exchange rate regime does not help render optimal policy time consistent.Time consistency; Optimal monetary and fiscal policy; Small open economy.

Effects of Rate Adaption on the Throughput of Random Ad Hoc Networks

The capacity of wireless ad hoc networks has been studied in an excellent treatise by Gupta and Kumar [1], assuming a fixed transmission rate. By contrast, in this treatise we investigate the achievable throughput improvement of rate adaptation in the context of random ad hoc networks, which have been studied in conjunction with a fixed transmission rate in [1]. Our analysis shows that rate adaptation has the potential of improving the achievable throughput compared to fixed rate transmission, since rate adaptation mitigates the effects of link quality fluctuations. However, even perfect rate control fails to change the scaling law of the per-node throughput result given in [1], regardless of the absence or presence of shadow fading. This result is confirmed in the context of specific adaptive modulation aided design examples