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Register a new userNarrow Band X-ray Photometry as a Tool for Studying Galaxy and Cluster Mass Distributions
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We explore the utility of narrow band X-ray surface photometry as a tool for making fully Bayesian, hydrostatic mass measurements of clusters of galaxies, groups and early-type galaxies. We demonstrate that it is sufficient to measure the surface photometry with the Chandra X-ray observatory in only three (rest frame) bands (0.5--0.9 keV, 0.9--2.0 keV and 2.0--7.0 keV) in order to constrain the temperature, density and abundance of the hot interstellar medium (ISM). Adopting parametrized models for the mass distribution and radial entropy profile and assuming spherical symmetry, we show that the constraints on the mass and thermodynamic properties of the ISM that are obtained by fitting data from all three bands simultaneously are comparable to those obtained by fitting similar models to the temperature and density profiles derived from spatially resolved spectroscopy, as is typically done. We demonstrate that the constraints can be significantly tightened when exploiting a recently derived, empirical relationship between the gas fraction and the entropy profile at large scales, eliminating arbitrary extrapolations at large radii. This Scaled Adiabatic Model (ScAM) is well suited to modest signal-to-noise data, and we show that accurate, precise measurements of the global system properties are inferred when employing it to fit data from even very shallow, snapshot X-ray observations. The well-defined asymptotic behaviour of the model also makes it ideally suited for use in Sunyaev-Zeldovich studies of galaxy clusters.
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The cosmological constraining power of modern galaxy cluster catalogs can be improved by obtaining low-scatter mass proxy measurements for even a small fraction of sources. In the context of large upcoming surveys that will reveal the cluster population down to the group scale and out to high redshifts, efficient strategies for obtaining such mass proxies will be valuable. In this work, we use high-quality weak lensing and X-ray mass estimates for massive clusters in current X-ray selected catalogs to revisit the scaling relations of the projected, center-excised X-ray luminosity ($L_{ce}$), which previous work suggests correlates tightly with total mass. Our data confirm that this is the case, with $L_{ce}$ having an intrinsic scatter at fixed mass comparable to that of gas mass, temperature or $Y_X$. Compared to these other proxies, however, $L_{ce}$ is less susceptible to systematic uncertainties due to background modeling, and can be measured precisely with shorter exposures. This opens up the possibility of using $L_{ce}$ to estimate masses for large numbers of clusters discovered by new X-ray surveys (e.g. eROSITA) directly from the survey data, as well as for clusters discovered at other wavelengths, with relatively short follow-up observations. We describe a simple procedure for making such estimates from X-ray surface brightness data, and comment on the spatial resolution required to apply this method as a function of cluster mass and redshift. We also explore the potential impact of Chandra and XMM-Newton follow-up observations over the next decade on dark energy constraints from new cluster surveys.
We present a parametric analysis of the intracluster medium and gravitating mass distribution of a statistical sample of 20 galaxy clusters using the phenomenological cluster model of Ascasibar and Diego. We describe an effective scheme for the estimation of errors on model parameters and derived quantities using bootstrap resampling. We find that the model provides a good description of the data in all cases and we quantify the mean fractional intrinsic scatter about the best-fit density and temperature profiles, finding this to have median values across the sample of 2 and 5 per cent, respectively. In addition, we demonstrate good agreement between r500 determined directly from the model and that estimated from a core-excluded global spectrum. We compare cool core and non-cool core clusters in terms of the logarithmic slopes of their gas density and temperature profiles and the distribution of model parameters and conclude that the two categories are clearly separable. In particular, we confirm the effectiveness of the logarithmic gradient of the gas density profile measured at 0.04 r500 in differentiating between the two types of cluster.
We study the consistency of the physical properties of galaxies retrieved from SED-fitting as a function of spectral resolution and signal-to-noise ratio (SNR). Using a selection of physically motivated star formation histories, we set up a control sample of mock galaxy spectra representing observations of the local universe in high-resolution spectroscopy, and in 56 narrow-band and 5 broad-band photometry. We fit the SEDs at these spectral resolutions and compute their corresponding the stellar mass, the mass- and luminosity-weighted age and metallicity, and the dust extinction. We study the biases, correlations, and degeneracies affecting the retrieved parameters and explore the r^ole of the spectral resolution and the SNR in regulating these degeneracies. We find that narrow-band photometry and spectroscopy yield similar trends in the physical properties derived, the former being considerably more precise. Using a galaxy sample from the SDSS, we compare more realistically the results obtained from high-resolution and narrow-band SEDs (synthesized from the same SDSS spectra) following the same spectral fitting procedures. We use results from the literature as a benchmark to our spectroscopic estimates and show that the prior PDFs, commonly adopted in parametric methods, may introduce biases not accounted for in a Bayesian framework. We conclude that narrow-band photometry yields the same trend in the age-metallicity relation in the literature, provided it is affected by the same biases as spectroscopy; albeit the precision achieved with the latter is generally twice as large as with the narrow-band, at SNR values typical of the different kinds of data.
Our aim in this work is to answer, using simulated narrow-band photometry data, the following general question: What can we learn about galaxies from these new generation cosmological surveys? For instance, can we estimate stellar age and metallicity distributions? Can we separate star-forming galaxies from AGN? Can we measure emission lines, nebular abundances and extinction? With what precision? To accomplish this, we selected a sample of about 300k galaxies with good S/N from the SDSS and divided them in two groups: 200k objects and a template library of 100k. We corrected the spectra to $z = 0$ and converted them to filter fluxes. Using a statistical approach, we calculated a Probability Distribution Function (PDF) for each property of each object and the library. Since we have the properties of all the data from the {sc starlight}-SDSS database, we could compare them with the results obtained from summaries of the PDF (mean, median, etc). Our results shows that we retrieve the weighted average of the log of the galaxy age with a good error margin ($sigma approx 0.1 - 0.2$ dex), and similarly for the physical properties such as mass-to-light ratio, mean stellar metallicity, etc. Furthermore, our main result is that we can derive emission line intensities and ratios with similar precision. This makes this method unique in comparison to the other methods on the market to analyze photometry data and shows that, from the point of view of galaxy studies, future photometric surveys will be much more useful than anticipated.
We used magnetohydrodynamic (MHD) simulations of interstellar turbulence to study the probability distribution functions (PDFs) of increments of density, velocity, and magnetic field. We found that the PDFs are well described by a Tsallis distribution, following the same general trends found in solar wind and Electron MHD studies. We found that the PDFs of density are very different in subsonic and supersonic turbulence. In order to extend this work to ISM observations we studied maps of column density obtained from 3D MHD simulations. From the column density maps we found the parameters that fit to Tsallis distributions and demonstrated that these parameters vary with the sonic and Alfven Mach numbers of turbulence. This opens avenues for using Tsallis distributions to study the dynamical and perhaps magnetic states of interstellar gas.
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