138 research outputs found

    The effect of AGN feedback on the halo mass function

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    [Abridged.] We investigate baryon effects on the halo mass function (HMF), with emphasis on the role played by AGN feedback. Halos are identified with both Friends-of-Friends (FoF) and Spherical Overdensity (SO) algorithms. We embed the standard SO algorithm into a memory-controlled frame program and present the {\bf P}ython spher{\bf I}c{\bf A}l {\bf O}verdensity code --- {\small PIAO}. For both FoF and SO halos, the effect of AGN feedback is that of suppressing the HMFs to a level even below that of Dark Matter simulations. The ratio between the HMFs in the AGN and in the DM simulations is ∼0.8\sim 0.8 at overdensity Δc=500\Delta_c=500, a difference that increases at higher overdensity Δc=2500\Delta_c=2500, with no significant redshift and mass dependence. A decrease of the halo masses ratio with respect to the DM case induces the decrease of the HMF in the AGN simulation. The shallower inner density profiles of halos in the AGN simulation witnesses that mass reduction is induced by the sudden displacement of gas induced by thermal AGN feedback. We provide fitting functions to describe halo mass variations at different overdensities, which can recover the HMFs with a residual random scatter <5\lt 5 per cent for halo masses larger than 1013 h−1M⊙10^{13} ~h^{-1}{\rm M_\odot}.Comment: 16 pages, 11 figures. Matches to MNRAS published version, typo corrected in the fitting functio

    Nonlinearities in modified gravity cosmology. II. Impacts of modified gravity on the halo properties

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    The statistics of dark matter halos is an essential component of understanding the nonlinear evolution in modified gravity cosmology. Based on a series of modified gravity N-body simulations, we investigate the halo mass function, concentration and bias. We model the impact of modified gravity by a single parameter \zeta, which determines the enhancement of particle acceleration with respect to GR, given the identical mass distribution (\zeta=1 in GR). We select snapshot redshifts such that the linear matter power spectra of different gravity models are identical, in order to isolate the impact of gravity beyond modifying the linear growth rate. At the baseline redshift corresponding to z_S=1.2 in the standard \Lambda CDM, for a 10% deviation from GR(|\zeta-1|=0.1), the measured halo mass function can differ by about 5-10%, the halo concentration by about 10-20%, while the halo bias differs significantly less. These results demonstrate that the halo mass function and/or the halo concentration are sensitive to the nature of gravity and may be used to make interesting constraints along this line.Comment: 8 pages, 7 figures, accepted for publication in Physical Review

    The source-lens clustering effect in the context of lensing tomography and its self-calibration

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    Cosmic shear can only be measured where there are galaxies. This source-lens clustering (SLC) effect has two sources, intrinsic source clustering and cosmic magnification (magnification/size bias). Lensing tomography can suppress the former. However, this reduction is limited by the existence of photo-z error and nonzero redshift bin width. Furthermore, SLC induced by cosmic magnification cannot be reduced by lensing tomography. Through N-body simulations, we quantify the impact of SLC on the lensing power spectrum in the context of lensing tomography. We consider both the standard estimator and the pixel-based estimator. We find that none of them can satisfactorily handle both sources of SLC. (1) For the standard estimator, SLC induced by both sources can bias the lensing power spectrum by O(1)-O(10)%. Intrinsic source clustering also increases statistical uncertainties in the measured lensing power spectrum. However, the standard estimator suppresses intrinsic source clustering in the cross-spectrum. (2) In contrast, the pixel-based estimator suppresses SLC through cosmic magnification. However, it fails to suppress SLC through intrinsic source clustering and the measured lensing power spectrum can be biased low by O(1)-O(10)%. In short, for typical photo-z errors (sigma_z/(1+z)=0.05) and photo-z bin sizes (Delta_z^P=0.2), SLC alters the lensing E-mode power spectrum by 1-10%, with ell~10^3$ and z_s~1 being of particular interest to weak lensing cosmology. Therefore the SLC is a severe systematic for cosmology in Stage-IV lensing surveys. We present useful scaling relations to self-calibrate the SLC effect.Comment: 13 pages, 10 figures, Accepted by AP

    The Impact of Baryons on the Large-Scale Structure of the Universe

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    Numerical simulations play an important role in current astronomy researches. Previous dark-matter-only simulations have represented the large-scale structure of the Universe. However, nowadays, hydro-dynamical simulations with baryonic models, which can directly present realistic galaxies, may twist these results from dark-matter-only simulations. In this chapter, we mainly focus on these three statistical methods: power spectrum, two-point correlation function and halo mass function, which are normally used to characterize the large-scale structure of the Universe. We review how these baryon processes influence the cosmology structures from very large scale to quasi-linear and non-linear scales by comparing dark-matter-only simulations with their hydro-dynamical counterparts. At last, we make a brief discussion on the impacts coming from different baryon models and simulation codes

    Gaussianizing the non-Gaussian lensing convergence field I: the performance of the Gaussianization

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    Motivated by recent works of Neyrinck et al. 2009 and Scherrer et al. 2010, we proposed a Gaussianization transform to Gaussianize the non-Gaussian lensing convergence field κ\kappa. It performs a local monotonic transformation κ→y\kappa\rightarrow y pixel by pixel to make the unsmoothed one-point probability distribution function of the new variable yy Gaussian. We tested whether the whole yy field is Gaussian against N-body simulations. (1) We found that the proposed Gaussianization suppresses the non-Gaussianity by orders of magnitude, in measures of the skewness, the kurtosis, the 5th- and 6th-order cumulants of the yy field smoothed over various angular scales relative to that of the corresponding smoothed κ\kappa field. The residual non-Gaussianities are often consistent with zero within the statistical errors. (2) The Gaussianization significantly suppresses the bispectrum. Furthermore, the residual scatters around zero, depending on the configuration in the Fourier space. (3) The Gaussianization works with even better performance for the 2D fields of the matter density projected over \sim 300 \mpch distance interval centered at z∈(0,2)z\in(0,2), which can be reconstructed from the weak lensing tomography. (4) We identified imperfectness and complexities of the proposed Gaussianization. We noticed weak residual non-Gaussianity in the yy field. We verified the widely used logarithmic transformation as a good approximation to the Gaussianization transformation. However, we also found noticeable deviations.Comment: 13 pages, 15 figures, accepted by PR

    How baryons affect haloes and large-scale structure: a unified picture from the Simba simulation

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    Using the state-of-the-art suite of hydrodynamic simulations Simba, as well as its dark-matter-only counterpart, we study the impact of the presence of baryons and of different stellar/AGN feedback mechanisms on large-scale structure, halo density profiles, and on the abundance of different baryonic phases within halos and in the intergalactic medium (IGM). The unified picture that emerges from our analysis is that the main physical drivers shaping the distribution of matter at all scales are star formation-driven galactic outflows at z>2z>2 for lower mass halos and AGN jets at z<2z<2 in higher mass halos. Feedback suppresses the baryon mass function with time relative to the halo mass function, and it even impacts the halo mass function itself at the ~20% level, particularly evacuating the centres and enhancing dark matter just outside halos. At early epochs baryons pile up in the centres of halos, but by late epochs and particularly in massive systems gas has mostly been evacuated from within the inner halo. AGN jets are so efficient at such evacuation that at low redshifts the baryon fraction within ∼1012−1013 M⊙\sim 10^{12}-10^{13} \, \rm M_{\odot} halos is only 25% of the cosmic baryon fraction, mostly in stars. The baryon fraction enclosed in a sphere around such halos approaches the cosmic value Ωb/Ωm\Omega_{\rm b}/\Omega_{\rm m} only at 10-20 virial radii. As a result, 87% of the baryonic mass in the Universe lies in the IGM at z=0z=0, with 67% being in the form of warm-hot IGM (T>105 KT>10^5 \, \rm K).Comment: submitted to MNRA

    How does our choice of observable influence our estimation of the centre of a galaxy cluster? Insights from cosmological simulations

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    Galaxy clusters are an established and powerful test-bed for theories of both galaxy evolution and cosmology. Accurate interpretation of cluster observations often requires robust identification of the location of the centre. Using a statistical sample of clusters drawn from a suite of cosmological simulations in which we have explored a range of galaxy formation models, we investigate how the location of this centre is affected by the choice of observable - stars, hot gas, or the full mass distribution as can be probed by the gravitational potential. We explore several measures of cluster centre: the minimum of the gravitational potential, which would expect to define the centre if the cluster is in dynamical equilibrium; the peak of the density; the centre of BCG; and the peak and centroid of X-ray luminosity. We find that the centre of BCG correlates more strongly with the minimum of the gravitational potential than the X-ray defined centres, while AGN feedback acts to significantly enhance the offset between the peak X-ray luminosity and minimum gravitational potential. These results highlight the importance of centre identification when interpreting clusters observations, in particular when comparing theoretical predictions and observational data.Comment: 11 pages, 6 figures, MNRAS accepte
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