16,571 research outputs found

    Simulated X-ray Cluster Temperature Maps

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    Temperature maps are presented of the 9 largest clusters in the mock catalogues of Muanwong et al. for both the Preheating and Radiative models. The maps show that clusters are not smooth, featureless systems, but contain a variety of substructure which should be observable. The surface brightness contours are generally elliptical and features that are seen include cold clumps, hot spiral features, and cold fronts. Profiles of emission-weighted temperature, surface brightness and emission-weighted pressure across the surface brightness discontinuities seen in one of the bimodal clusters are consistent with the cold front in Abell 2142 observed by Markevitch et al.Comment: Submitted to Monthly Notices Royal Astronomical Societ

    The baseline intracluster entropy profile from gravitational structure formation

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    The radial entropy profile of the hot gas in clusters of galaxies tends to follow a power law in radius outside of the cluster core. Here we present a simple formula giving both the normalization and slope for the power-law entropy profiles of clusters that form in the absence of non-gravitational processes such as radiative cooling and subsequent feedback. It is based on seventy-one clusters drawn from four separate cosmological simulations, two using smoothed-particle hydrodynamics (SPH) and two using adaptive-mesh refinement (AMR), and can be used as a baseline for assessing the impact of non-gravitational processes on the intracluster medium outside of cluster cores. All the simulations produce clusters with self-similar structure in which the normalization of the entropy profile scales linearly with cluster temperature, and these profiles are in excellent agreement outside of 0.2 r_200. Because the observed entropy profiles of clusters do not scale linearly with temperature, our models confirm that non-gravitational processes are necessary to break the self-similarity seen in the simulations. However, the core entropy levels found by the two codes used here significantly differ, with the AMR code producing nearly twice as much entropy at the centre of a cluster.Comment: Accepted to MNRAS, 8 pages, 9 figure

    Mixed mode pattern in Doublefoot mutant mouse limb - Turing reaction-diffusion model on a growing domain during limb development

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    It has been suggested that the Turing reaction–diffusion model on a growing domain is applicable during limb development, but experimental evidence for this hypothesis has been lacking. In the present study, we found that in Doublefoot mutant mice, which have supernumerary digits due to overexpansion of the limb bud, thin digits exist in the proximal part of the hand or foot, which sometimes become normal abruptly at the distal part. We found that exactly the same behaviour can be reproduced by numerical simulation of the simplest possible Turing reaction–diffusion model on a growing domain. We analytically showed that this pattern is related to the saturation of activator kinetics in the model. Furthermore, we showed that a number of experimentally observed phenomena in this system can be explained within the context of a Turing reaction–diffusion model. Finally, we make some experimentally testable predictions

    Hadamard States and Adiabatic Vacua

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    Reversing a slight detrimental effect of the mailer related to TeXabilityComment: 10pages, LaTeX (RevTeX-preprint style

    Correction of non-linearity effects in detectors for electron spectroscopy

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    Using photoemission intensities and a detection system employed by many groups in the electron spectroscopy community as an example, we have quantitatively characterized and corrected detector non-linearity effects over the full dynamic range of the system. Non-linearity effects are found to be important whenever measuring relative peak intensities accurately is important, even in the low-countrate regime. This includes, for example, performing quantitative analyses for surface contaminants or sample bulk stoichiometries, where the peak intensities involved can differ by one or two orders of magnitude, and thus could occupy a significant portion of the detector dynamic range. Two successful procedures for correcting non-linearity effects are presented. The first one yields directly the detector efficiency by measuring a flat-background reference intensity as a function of incident x-ray flux, while the second one determines the detector response from a least-squares analysis of broad-scan survey spectra at different incident x-ray fluxes. Although we have used one spectrometer and detection system as an example, these methodologies should be useful for many other cases.Comment: 13 pages, 12 figure
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