On the use of rotational splitting asymmetries to probe the internal rotation profile of stars: Application to beta Cephei stars

Rotationally-split modes can provide valuable information about the internal rotation profile of stars. This has been used for years to infer the internal rotation behavior of the Sun. The present work discusses the potential additional information that rotationally splitting asymmetries may provide when studying the internal rotation profile of stars. We present here some preliminary results of a method, currently under development, which intends: 1) to understand the variation of the rotational splitting asymmetries in terms of physical processes acting on the angular momentum distribution in the stellar interior, and 2) how this information can be used to better constrain the internal rotation profile of the stars. The accomplishment of these two objectives should allow us to better use asteroseismology as a test-bench of the different theories describing the angular momentum distribution and evolution in the stellar interiors. (C) 2010 WILEY-VCH Verlag GmbH&Co. KGaA, Weinheim

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

The Oscillations of Tau Pegasi

We present extensive spectroscopic time series observations of the multiperiodic, rapidly rotating, delta Scuti star tau Pegasi. Information about the oscillations is contained within the patterns of line-profile variation of the star's blended absorption-line spectrum. We introduce the new technique of Doppler deconvolution with which to extract these patterns by modeling the intrinsic stellar spectrum and the broadening functions for each spectrum in the time series. Frequencies and modes of oscillation are identified from the variations using the technique of Fourier-Doppler imaging and a two-dimensional least-squares cleaning algorithm. We find a rich mode spectrum with degrees up to l = 20 and with frequencies below about 35 cycles day-1. Those modes with the largest amplitudes have frequencies that lie within a narrow band. We conclude that the observed spectrum can be explained if the modes of tau Peg propagate in the prograde direction with l ~= |m| and with frequencies that are about equal in the corotating frame of the star. We discuss the implications of these results for the prospect of delta Scuti seismology.

High-resolution spectroscopy of globular cluster post-Asymptotic Giant Branch stars

We present model atmosphere analyses of high resolution Keck and VLT optical spectra for three evolved stars in globular clusters, viz. ZNG-1 in M 10, ZNG-1 in M 15 and ZNG-1 in NGC 6712. The derived atmospheric parameters and chemical compositions confirm the programme stars to be in the post- Asymptotic Giant Branch (post-AGB) evolutionary phase. Differential abundance analyses reveal CNO abundance patterns in M 10 ZNG-1, and possibly M 15 ZNG-1, which Suggest that both objects may have evolved off the AGB before the third dredge-up occurred. The abundance pattern of these stars is similar to the third class of optically, bright post-AGB objects discussed by van Winckel (1997). Furthermore, M 10 ZNG-1 exhibits a large C underabundance (with Delta[C/O] similar to -1.6 dex), typical of other hot post-AGB objects. Differential Delta[alpha/Fe] abundance ratios in both M 10 ZNG-1 and NGC 6712 ZNG-1 are found to be approximately 0.0 dex, with the Fe abundance of the former being in disagreement with the cluster metallicity of M 10. Given that the Fe absorption features in both M 10 ZNG-1 and NGC6712 ZNG-1 are well observed and reliably modelled, we believe that these differential Fe abundance estimates to be secure. However, our Fe abundance is difficult to explain in terms of previous evolutionary processes that Occur oil both the Horizontal Branch and the AGB.

CaIIKinterstellar observations towards early-type disc and halo stars, abundances and distances of intermediate- and high-velocity clouds

We present Ca II K (lambda(air) = 3933.661 angstrom) interstellar observations towards 20 early-type stars, to place lower distance limits to intermediate- and high-velocity clouds (IHVCs) in their lines of sight. The spectra are also employed to estimate the Ca abundance in the low-velocity gas towards these objects, when combined with Leiden-Dwingeloo 21-cm HI survey data of spatial resolution 0 degrees.5. Nine of the stars, which lie towards IHVC complexes H, K and gp, were observed with the intermediate dispersion spectrograph on the Isaac Newton Telescope at a resolution R = lambda/Delta lambda of 9000 (similar to 33 km s(-1)) and signal-to-noise ratio (S/N) per pixel of 75-140. A further nine objects were observed with the Utrecht Echelle Spectrograph on the William Herschel Telescope at R = 40 000 (similar to 7.5 km s(-1)) and S/N per pixel of 10-25. Finally, two objects were observed in both Ca II K and Na I D lines using the 2D COUDE on the McDonald 2.7-m telescope at R = 35 000 (similar to 8.5 km s(-1)). The abundance of Ca II K {log(10)(A) = log(10)[N(Ca II K)]-log(10)[N(HI)]} plotted against HI column density for the objects in the current sample with heights above the Galactic plane (z) exceeding 1000 pc is found to obey the Wakker & Mathis (2000) relation. Also, the reduced column density of Ca II K as function of z is consistent with the larger sample taken from Smoker et al. (2003). Higher S/N observations than those previously taken towards HVC complex H stars HD 13256 and HILT 190 reinforce the assertion that this lies at a distance exceeding 4000 pc. No obvious absorption is detected in observations of ALS 10407 and HD 357657 towards IVC complex gp. The latter star has a spectroscopically estimated distance of similar to 2040 pc, although this was derived assuming the star lies on the main sequence and without any reddening correction being applied. Finally, no Ca II K absorption is detected towards two stars along the line of sight to complex K, namely PG 1610+529 and PG 1710+490. The latter is at a distance of similar to 700 pc, hence placing a lower distance limit to this complex, where previously only an upper distance limit of 6800 pc was available.

Robust video stabilisation algorithm using feature point selection and delta optical flow

In this study, the authors propose a novel video stabilisation algorithm for mobile platforms with moving objects in the scene. The quality of videos obtained from mobile platforms, such as unmanned airborne vehicles, suffers from jitter caused by several factors. In order to remove this undesired jitter, the accurate estimation of global motion is essential. However it is difficult to estimate global motions accurately from mobile platforms due to increased estimation errors and noises. Additionally, large moving objects in the video scenes contribute to the estimation errors. Currently, only very few motion estimation algorithms have been developed for video scenes collected from mobile platforms, and this paper shows that these algorithms fail when there are large moving objects in the scene. In this study, a theoretical proof is provided which demonstrates that the use of delta optical flow can improve the robustness of video stabilisation in the presence of large moving objects in the scene. The authors also propose to use sorted arrays of local motions and the selection of feature points to separate outliers from inliers. The proposed algorithm is tested over six video sequences, collected from one fixed platform, four mobile platforms and one synthetic video, of which three contain large moving objects. Experiments show our proposed algorithm performs well to all these video sequences.

Multi-criteria ranking and receptor modelling of airborne fine particles at three sites in the Pearl River Delta region of China

The multi-criteria decision making methods, Preference METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site > urban site > roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8 ± 8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region.

Stars are made of glass : children as capable and creative communicators

This booklet is the third in the Research in Practice Series, designed to complement Belonging, being & becoming: The Early Years Learning Framework for Australia (DEEWR, 2009). It focuses on Learning Outcome 5 of the Early Years Learning Framework (EYLF): Children are effective communicators (DEEWR, 2009).

The delta-phase spectrum with application to voice activity detection and speaker recognition

For several reasons, the Fourier phase domain is less favored than the magnitude domain in signal processing and modeling of speech. To correctly analyze the phase, several factors must be considered and compensated, including the effect of the step size, windowing function and other processing parameters. Building on a review of these factors, this paper investigates a spectral representation based on the Instantaneous Frequency Deviation, but in which the step size between processing frames is used in calculating phase changes, rather than the traditional single sample interval. Reflecting these longer intervals, the term delta-phase spectrum is used to distinguish this from instantaneous derivatives. Experiments show that mel-frequency cepstral coefficients features derived from the delta-phase spectrum (termed Mel-Frequency delta-phase features) can produce broadly similar performance to equivalent magnitude domain features for both voice activity detection and speaker recognition tasks. Further, it is shown that the fusion of the magnitude and phase representations yields performance benefits over either in isolation.

Realisation of ternary sigma-delta modulated arithmetic processing modules

Sigma-delta modulated systems have a number of very appealing properties and are, therefore, heavily used in analog to digital converters, amplifiers, and modulators. This paper presents new results which indicate that they may also have significant potential for general purpose arithmetic processing.