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And XMM- Newton/GAIA THE ISM AS SEEN IN X-RAY OBSERVATIONS Efraín Gatuzz1, Javier A. García2, Timothy R. Kallman3, S. Rezaei. Kh4 and J. Wilms5 1 Max Planck Institute for Extraterrestrial Physics , Garching, Germany 2 Cahill Center for Astronomy and Astrophysics, California Institute of Technology, Pasadena, CA 91125, USA 3 NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA 4 Department of Space, Earth and Environment, Chalmers University of Technology SE-412 96 Gothenburg, Sweden 5 Dr. Karl Remeis-Observatory and Erlangen Centre for Astroparticle Physics, Universität Erlangen-Nürnberg, Sternwartstr. 7, D-96049 Bamberg, Germany ABSTRACT The interstellar medium (ISM), gas and dust between stars, is an important constituent of galaxies, affecting star formation and their overall evolution. A powerful technique to study such environment is through X-ray observations because, due to their high energy, X-ray photons can trace simultaneously the cold-warm-hot phases of the ISM, including molecular and solid components. Here, we report on the 3D mapping of the neutral X-ray absorption in the ISM using X-ray data from both Chandra and XMM-Newton, in combination with distances obtained with the GAIA observatory. THE SOURCES SAMPLE In order to create the galactic sample we use the following catalogues: - To obtain X-ray spectra: The XMM-Newton source catalog (3XMM-DR8) and the Chandra Source Catalog (CSC 2.0) - To obtain source distances: the GAIA catalog (GAIA DR2) - To select only stars: the guide star catalog II (GSC II) The cross-matching between the three catalogues has been done using the NWAY code (Salvato et al. 2018). NWAY is an statistics based algorithm which extends previous distance and sky density based association methods and, using one or more priors "p_i" versus "p_any" distribution for the correct counterparts to the Chandra/GAIA (left panel) and XMM- (e.g. colours, magnitudes), weights the probability Newton/GAIA (right panel) sources (red points) and for the candidate counterpart to the same sources after that sources from two or more catalogues are randomizing their position (grey). Sources with "p_any<0.1" for Chandra and "p_any<0.2" for XMM-Newton and simultaneously associated on the basis of their with ambiguous detection (i.e. match_flag==2) were not included in the cross-matching sample. After the observable characteristics. crossmatching between GAIA and the X-ray catalogues we have identified 31244 Chandra unique sources and 52129 XMM-Newton unique sources. 1e4 Chandra 5000 Chandra XMM-Newton XMM-Newton X-RAY FITTING PROCEDURE 2000 1000 1000 We used EPIC-pn and ACIS data for XMM- 500 Newton and Chandra, respectively. Each spectrum 200 100 has been rebinned to have, at least, 1 count per 100 # Sources channel. The fits are done in the 0.5-10 keV energy # Sources 50 band. For each source, in the case of multiple 20 observations, the spectra with highest number of 10 counts is fitted. 10 5 We fitted the spectra using multiple models (in 1 2 XSPEC nomenclature): 1e-14 1e-12 1e-10 1e-8 1e-6 1e-4 0.01 1 100 1e-14 1e-12 1e-10 1e-8 1e-6 1e-4 0.01 1 100 Nh(powerlaw) Nh(bbody) - tbabs∗powerlaw powerlaw 5000 Chandra 5000 Chandra - tbabs bbody XMM-Newton XMM-Newton ∗powerlaw 2000 2000 - tbabs∗powerlaw apec 1000 1000 500 The solar abundance is set to (Wilms et al. 2000). 500 200 200 and the initial parameter for Nh is the 21 cm value 100 from (Kalberla et al. 2005). Finally, Cash statistic 50 100 # Sources # Sources (Cash 1979) is used in the spectral fits. 50 20 10 20 5 3D MAPPING OF THE NEUTRAL X-RAY 10 ABSORPTION IN THE ISM 2 5 1 1e-14 1e-12 1e-10 1e-8 1e-6 1e-4 0.01 1 100 1e-14 1e-12 1e-10 1e-8 1e-6 1e-4 0.01 1 100 The gas distribution in the ISM, using the Nh Nh(apec) Nh(best-fits) column densities obtained from the fits, can be modelled according to the integral: Figure shows the distribution of Nh for the powerlaw model (top left panel), the blackbody model (top right panel), the apec model (bottom left panel) and for the best-fit results (i.e. the fits with the best statistic, bottom 22 −2 s right panel). Nh is shown in units of 10 cm N =∫ n (r)dr 100 i o i 2 Chandra Chandra XMM-Newton 1 XMM-Newton Where r is the distance along the i l.o.s between 10 the observer (o) and the source (s) and ni(r) is the 0.5 density profile. We will use the method explained in 1 0.2 Rezaei Kh. et al. (2017) and Gatuzz et al. (2018), to 0.1 infer Hydrogen densities. The method uses a Nh (21cm) Bayesian approach to predict the most probable Nh (21cm) 0.1 0.05 distribution of the density at any arbitrary point, even 0.02 for line of sights along which there are no initial 0.01 0.01 observations. 0.001 0.005 100 1000 1e4 1e5 1e6 -90 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90 Galactic latitude (b) Galactic latitude (b) 100 REFERENCES Chandra XMM-Newton Left top panel: distribution of Nh for the best-fit - Cash W., 2979, ApJ, 228, 939 10 models as function of the number of counts in the - Gatuzz et al. 2018, MNRAS, 479, 3715 0.5-10 keV keV energy regions. - Kalberla et al. 2005, A&A, 440, 775 1 Left bottom panel: Distribution of Nh for the best- - Rezaei Kh S. et al. 2017, A&A, 598, A125 fit models as function of the 21 cm measurements. - Salvato et al. 2018, MNRAS, 473, 4937 The solid black line indicates the case when Nh (21cm) 0.1 - Wilms et al. 2000, ApJ, 542, 914 Nh(fits)=Nh(21cm). Right top panel: distribution of Nh(21cm) 0.01 measurements. 0.001 0.005 0.01 0.02 0.05 0.1 0.2 0.5 1 2 Galactic latitude (b).
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