Ionizing radiation in smoothed particle hydrodynamics

A new method for the inclusion of ionizing radiation from uniform radiation fields into 3D smoothed particle hydrodynamics (SPHI) simulations is presented. We calculate the optical depth for the Lyman continuum radiation from the source towards the SPHI particles by ray-tracing integration. The time-dependent ionization rate equation is then solved locally for the particles within the ionizing radiation field. Using test calculations, we explore the numerical behaviour of the code with respect to the implementation of the time-dependent ionization rate equation. We also test the coupling of the heating caused by the ionization to the hydrodynamical part of the SPHI code.     

Isotropic wavelets: a powerful tool to extract point sources from cosmic microwave background maps

It is the aim of this paper to introduce the use of isotropic wavelets to detect and determine the flux of point sources appearing in cosmic microwave background (CMB) maps. The most suitable wavelet to detect point sources filtered with a Gaussian beam is the 'Mexican Hat'. An analytical expression of the wavelet coefficient obtained in the presence of a point source is provided and used in the detection and flux estimation methods presented. For illustration the method is applied to two simulations (assuming Planck mission characteristics) dominated by CMB (100 GHz) and dust (857 GHz), as these will be the two signals dominating at low and high frequencies respectively in the Planck channels. We are able to detect bright sources above 1.58 Jy at 857 GHz (82 per cent of all sources) and above 0.36 Jy at 100 GHz (100 per cent of all), with errors in the flux estimation below 25 per cent. The main advantage of this method is that nothing has to be assumed about the underlying field, i.e. about the nature and properties of the signal plus noise present in the maps. This is not the case in the detection method presented by Tegmark & Oliveira-Costa. Both methods are compared, producing similar results.     

The analysis of indexed astronomical time series – VI. Covariances of amplitude ratios and phase differences estimated from multicolour photometry of a pulsating star

One of the tools used to identify the pulsation modes of stars is a comparison of the amplitudes and phases as observed photometrically at different wavelengths. Proper application of the method requires that the errors on the measured quantities, and the correlations between them, be known (or at least estimated). It is assumed that contemporaneous measurements of the light intensity of a pulsating star are obtained in several wavebands. It is also assumed that the measurements are regularly spaced in time, although there may be missing observations. The amplitude and phase of the pulsation are estimated separately for each of the wavebands, and amplitude ratios and phase differences are calculated. A general scheme for estimating the covariance matrix of the amplitude ratios and phase differences is described. The first step is to fit a time series to the residuals after pre-whitening the observations by the best-fitting sinusoid. The residuals are then cross-correlated to study the interdependence between the errors in the different wavebands. Once the multivariate time-series structure can be modelled, the covariance matrix can be found by bootstrapping. An illustrative application is described in detail.     

Non-parametric star formation histories for four dwarf spheroidal galaxies of the Local Group

We use recent Hubble Space Telescope colour–magnitude diagrams of the resolved stellar populations of a sample of local dSph galaxies (Carina, Leo I, Leo II and Ursa Minor) to infer the star formation histories of these systems, SFR ( t ). Applying a new variational calculus maximum likelihood method, which includes a full Bayesian analysis and allows a non-parametric estimate of the function one is solving for, we infer the star formation histories of the systems studied. This method has the advantage of yielding an objective answer, as one need not assume a priori the form of the function one is trying to recover. The results are checked independently using Saha's W statistic. The total luminosities of the systems are used to normalize the results into physical units and derive SN type II rates. We derive the luminosity-weighted mean star formation history of this sample of galaxies.     

Magnetic and optical spiral arms in the galaxy NGC 6946

The spiral pattern in the nearby spiral galaxy NGC 6946 has been studied using the wavelet transformation technique, applied to galaxy images in polarized and total non-thermal radio emission at λλ 3.5 and 6.2 cm, in broadband red light, in the λ 21.1 cm H  i line and in the optical Hα line. Well-defined, continuous spiral arms are visible in polarized radio emission and red light, where we can isolate a multi-armed pattern in the range of galactocentric distances 1.5–12 kpc, consisting of four long arms and one short spiral segment. The 'magnetic arms' (visible in polarized radio emission) are localized almost precisely between the optical arms. Each magnetic arm is similar in length and pitch angle to the preceding optical arm (in the sense of galactic rotation) and can be regarded as its phase-shifted image. Even details like a bifurcation of an optical arm have their phase-shifted counterparts in the magnetic arms. The average relative amplitude of the optical spiral arms (the stellar density excess over the azimuthal average) grows with galactocentric radius up to 0.3–0.7 at r ≃5 kpc, decreases by a factor of two at r =5–6 kpc and remains low at 0.2–0.3 in the outer parts of the galaxy. By contrast, the magnetic arms have a constant average relative amplitude (the excess in the regular magnetic field strength over the azimuthal average) of 0.3–0.6 in a wide radial range r =1.5–12 kpc. We briefly discuss implications of our findings for theories of galactic magnetic fields.     

The statistics of weak lensing at small angular scales: probability distribution function

Weak gravitational lensing surveys have the potential to probe mass density fluctuation in the Universe directly. Recent studies have shown that it is possible to model the statistics of the convergence field at small angular scales by modelling the statistics of the underlying density field in the highly non-linear regime. We propose a new method to model the complete probability distribution function of the convergence field as a function of smoothing angle and source redshift. The model relies on a hierarchical ansatz for the behaviour of higher order correlations of the density field. We compare our results with ray-tracing simulations and find very good agreement over a range of smoothing angles. Whereas the density probability distribution function is not sensitive to the cosmological model, the probability distribution function for the convergence can be used to constrain both the power spectrum and cosmological parameters.     

A stochastic Monte Carlo approach to model real star cluster evolution – II. Self-consistent models and primordial binaries

The new approach outlined in Paper I to follow the individual formation and evolution of binaries in an evolving, equal point-mass star cluster is extended for the self-consistent treatment of relaxation and close three- and four-body encounters for many binaries (typically a few per cent of the initial number of stars in the cluster mass). The distribution of single stars is treated as a conducting gas sphere with a standard anisotropic gaseous model. A Monte Carlo technique is used to model the motion of binaries, their formation and subsequent hardening by close encounters, and their relaxation (dynamical friction) with single stars and other binaries. The results are a further approach towards a realistic model of globular clusters with primordial binaries without using special hardware. We present, as our main result, the self-consistent evolution of a cluster consisting of 300 000 equal point-mass stars, plus 30 000 equal-mass binaries over several hundred half-mass relaxation times, well into the phase where most of the binaries have been dissolved and evacuated from the core. The cluster evolution is about three times slower than found by Gao et al. Other features are rather comparable. At every moment we are able to show the individual distribution of binaries in the cluster.     

Neural networks and the separation of cosmic microwave background and astrophysical signals in sky maps

We implement an independent component analysis (ICA) algorithm to separate signals of different origin in sky maps at several frequencies. Owing to its self-organizing capability, it works without prior assumptions on either the frequency dependence or the angular power spectrum of the various signals; rather, it learns directly from the input data how to identify the statistically independent components, on the assumption that all but, at most, one of the components have non-Gaussian distributions.
We have applied the ICA algorithm to simulated patches of the sky at the four frequencies (30, 44, 70 and 100 GHz) used by the Low Frequency Instrument of the European Space Agency's Planck satellite. Simulations include the cosmic microwave background (CMB), the synchrotron and thermal dust emissions, and extragalactic radio sources. The effects of the angular response functions of the detectors and of instrumental noise have been ignored in this first exploratory study. The ICA algorithm reconstructs the spatial distribution of each component with rms errors of about 1 per cent for the CMB, and 10 per cent for the much weaker Galactic components. Radio sources are almost completely recovered down to a flux limit corresponding to ≃0.7 σ _CMB, where σ _CMB is the rms level of the CMB fluctuations. The signal recovered has equal quality on all scales larger than the pixel size. In addition, we show that for the strongest components (CMB and radio sources) the frequency scaling is recovered with per cent precision. Thus, algorithms of the type presented here appear to be very promising tools for component separation. On the other hand, we have been dealing here with a highly idealized situation. Work to include instrumental noise, the effect of different resolving powers at different frequencies and a more complete and realistic characterization of astrophysical foregrounds is in progress.     

Testing the Gaussianity of the COBE DMR data with spherical wavelets

We investigate the Gaussianity of the 4-yr COBE DMR data (in HEALPix pixelization) using an analysis based on spherical Haar wavelets. We use all the pixels lying outside the Galactic cut and compute the skewness, kurtosis and scale–scale correlation spectra for the wavelet coefficients at each scale. We also take into account the sensitivity of the method to the orientation of the input signal. We find a detection of non-Gaussianity at >99 per cent level in just one of our statistics. Taking into account the total number of statistics computed, we estimate that the probability of obtaining such a detection by chance for an underlying Gaussian field is 0.69. Therefore, we conclude that the spherical wavelet technique shows no strong evidence of non-Gaussianity in the COBE DMR data.