Projected alignment of non-sphericities of stellar, gas, and dark matter distributions in galaxy clusters: analysis of the Horizon-AGN simulation

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY(2018)

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摘要
While various observations measured ellipticities of galaxy clusters and alignments between orientations of the brightest cluster galaxies and their host clusters, there are only a handful of numerical simulations that implement realistic baryon physics to allow direct comparisons with those observations. Here, we investigate ellipticities of galaxy clusters and alignments between various components of them and the central galaxies in the state-of-the-art cosmological hydrodynamical simulation Horizon-AGN, which contains dark matter, stellar, and gas components in a large simulation box of (100h(-1) Mpc)(3) with high spatial resolution (similar to 1 kpc). We estimate ellipticities of total matter, dark matter, stellar, gas surface mass density distributions, X-ray surface brightness, and the Compton y-parameter of the Sunyaev-Zel'dovich effect, as well as alignments between these components and the central galaxies for 120 projected images of galaxy clusters with masses M-200 > 5 x 10(13) M-circle dot. Our results indicate that the distributions of these components are well aligned with the major axes of the central galaxies, with the root-mean-square value of differences of their position angles of similar to 20 degrees, which vary little from inner to the outer regions. We also estimate alignments of these various components with total matter distributions, and find tighter alignments than those for central galaxies with the root-mean-square value of similar to 15 degrees. We compare our results with previous observations of ellipticities and position angle alignments and find reasonable agreements. The comprehensive analysis presented in this paper provides useful prior information for analysing stacked lensing signals as well as designing future observations to study ellipticities and alignments of galaxy clusters.
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methods: numerical,galaxies: clusters: general,dark matter
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