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Xiaohu, Yang

Publications and source records attributed to Xiaohu, Yang.

RECONSTRUCTING THE INITIAL DENSITY FIELD OF THE LOCAL UNIVERSE: METHODS AND TESTS WITH MOCK CATALOGS

Our research objective in this paper is to reconstruct an initial linear density field, which follows the multivariate Gaussian distribution with variances given by the linear power spectrum of the current cold dark matter model and evolves through gravitational instabilities to the present-day density field in the local universe. For this purpose, we develop a Hamiltonian Markov Chain Monte Carlo method to obtain the linear density field from a posterior probability function that consists of two components: a prior of a Gaussian density field with a given linear spectrum and a likelihood term that is given by the current density field. The present-day density field can be reconstructed from galaxy groups using the method developed in Wang et al. Using a realistic mock Sloan Digital Sky Survey DR7, obtained by populating dark matter halos in the Millennium simulation (MS) with galaxies, we show that our method can effectively and accurately recover both the amplitudes and phases of the initial, linear density field. To examine the accuracy of our method, we use N-body simulations to evolve these reconstructed initial conditions to the present day. The resimulated density field thus obtained accurately matches the original density field of the MS in the density range 0.3{approx}<{rho}/ {rho}-bar {approx}<20 without any significant bias. In particular, the Fourier phases of the resimulated density fields are tightly correlated with those of the original simulation down to a scale corresponding to a wavenumber of {approx}1 h Mpc{sup -1}, much smaller than the translinear scale, which corresponds to a wavenumber of {approx}0.15 h Mpc{sup -1}.

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CONSTRAINING THE STAR FORMATION HISTORIES IN DARK MATTER HALOS. I. CENTRAL GALAXIES

Using the self-consistent modeling of the conditional stellar mass functions across cosmic time by Yang et al., we make model predictions for the star formation histories (SFHs) of central galaxies in halos of different masses. The model requires the following two key ingredients: (1) mass assembly histories of central and satellite galaxies and (2) local observational constraints of the star formation rates (SFRs) of central galaxies as a function of halo mass. We obtain a universal fitting formula that describes the (median) SFH of central galaxies as a function of halo mass, galaxy stellar mass, and redshift. We use this model to make predictions for various aspects of the SFRs of central galaxies across cosmic time. Our main findings are the following. (1) The specific star formation rate at high z increases rapidly with increasing redshift [{proportional_to}(1 + z){sup 2.5}] for halos of a given mass and only slowly with halo mass ({proportional_to}M{sub h}{sup 0.12}) at a given z, in almost perfect agreement with the specific mass accretion rate of dark matter halos. (2) The ratio between the SFR in the main branch progenitor and the final stellar mass of a galaxy peaks roughly at a constant value, {approx}10{sup -9.3} h {sup 2} yr{sup -1}, independent of the halo mass or the final stellar mass of the galaxy. However, the redshift at which the SFR peaks increases rapidly with halo mass. (3) More than half of the stars in the present-day universe were formed in halos with 10{sup 11.1} h {sup -1} M{sub Sun} < M{sub h} < 10{sup 12.3} h {sup -1} M{sub Sun} in the redshift range 0.4 < z < 1.9. (4) The star formation efficiencies (SFEs) of central galaxies reveal a ''downsizing'' behavior, in that the halo ''quenching'' mass, at which the SFE peaks, shifts from {approx}10{sup 12.5} h {sup -1} M{sub Sun} at z {approx}> 3.5 to {approx}10{sup 11.3} h {sup -1} M{sub Sun} at z = 0. (5) At redshift z {approx}> 2.5 more than 99% of the stars in the progenitors of massive galaxies are formed in situ, and this fraction decreases as a function of redshift, becoming {approx}60% at z = 0. For a Milky-Way-sized halo of M{sub h} {approx} 10{sup 12} h {sup -1} M{sub Sun} more than 80% of all the stars are formed in situ, as opposed to having been accreted from satellite galaxies.

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BRIGHTEST SATELLITE GALAXY ALIGNMENT OF SLOAN DIGITAL SKY SURVEY GALAXY GROUPS

We study the alignment signal between the distribution of the brightest satellite galaxies (BSGs) and the major axes of their host groups using the Sloan Digital Sky Survey group catalog constructed by Yang et al. After correcting for the effect of group ellipticity, a statistically significant ({approx}5{sigma}) major-axis alignment is detected and the alignment angle is found to be 43. Degree-Sign 0 {+-} 0. Degree-Sign 4. More massive and richer groups show a stronger BSG alignment. The BSG alignment around blue brightest central galaxies (BCGs) is slightly stronger than that around red BCGs. Red BSGs have a much stronger major-axis alignment than blue BSGs. Unlike BSGs, other satellites do not show very significant alignment with their group's major axis. We further explore BSG alignment using the semi-analytic model (SAM) constructed by Guo et al. In general, we found good agreement of the model with observations: BSGs in the SAM show a strong major-axis alignment that depends on group mass and richness in the same way as in observations and none of the other satellites exhibit prominent alignment. However, a discrepancy also exists in that the SAM shows a BSG color dependence opposite of that in observations, which is most probably induced by a missing large-scale environment ingredient in the SAM. The combination of two popular scenarios can explain the BSG alignment we detected. First, satellites merged into the group along the surrounding filaments, which are strongly aligned with the major axis of the group. Second, BSGs entered their host group more recently than other satellites, so they have preserved more information about their assembling history and major-axis alignment. In the SAM, we found positive evidence for the second scenario in the fact that BSGs merged into groups statistically more recently than other satellites. We also found that most of the BSGs (80%) were BCGs before they merged into groups and earlier merging BSGs tend to be closer to their BCGs than other BSGs. On the other hand, although the BSG color dependence in observations is the opposite of that in the SAM, it might also indicate that the first scenario is a good explanation.

79 ASTRONOMY AND ASTROPHYSICS↗

BULK FLOW OF HALOS IN {Lambda}CDM SIMULATION

Analysis of the Pangu N-body simulation validates that the bulk flow of halos follows a Maxwellian distribution with variance that is consistent with the prediction of the linear theory of structure formation. We propose that the consistency between the observed bulk velocity and theories should be examined at the effective scale of the radius of a spherical top-hat window function yielding the same smoothed velocity variance in linear theory as the sample window function does. We compared some recently estimated bulk flows from observational samples with the prediction of the {Lambda}CDM model we used; some results deviate from expectation at a level of {approx}3{sigma}, but the discrepancy is not as severe as previously claimed. We show that bulk flow is only weakly correlated with the dipole of the internal mass distribution, that the alignment angle between the mass dipole and the bulk flow has a broad distribution peaked at {approx}30 Degree-Sign -50 Degree-Sign , and also that the bulk flow shows little dependence on the mass of the halos used in the estimation. In a simulation of box size 1 h {sup -1} Gpc, for a cell of radius 100 h {sup -1} Mpc the maximal bulk velocity is >500 km s{sup -1}; dipoles of the environmental mass outside the cell are not tightly aligned with the bulk flow, but are rather located randomly around it with separation angles {approx}20 Degree-Sign -40 Degree-Sign . In the fastest cell there is a slightly smaller number of low-mass halos; however, halos inside are clustered more strongly at scales {approx}> 20 h {sup -1} Mpc, which might be a significant feature since the correlation between bulk flow and halo clustering actually increases in significance beyond such scales.

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