5692175
Effects of correlation between merging steps on the global halo formation
The excursion set theory of halo formation is modified by adopting the fractional Brownian motion, to account for possible correlation between merging steps. We worked out analytically the conditional mass function, halo merging rate and formation time distribution in the spherical collapse model. We also developed an approximation for the ellipsoidal collapse model and applied it to the calculation of the conditional mass function and the halo formation time distribution. For models in which the steps are positively correlated, the halo merger rate is enhanced when the accreted mass is less than similar to 25M*, while for the negatively correlated case this rate is reduced. Compared with the standard model in which the steps are uncorrelated, the models with positively correlated steps produce more aged population in small mass haloes and more younger population in large mass haloes, while for the models with negatively correlated steps the opposite is true. An examination of simulation results shows that a weakly positive correlation between successive merging steps appears to fit best. We have also found a systematic effect in the measured mass function due to the finite volume of simulations. In future work, this will be included in the halo model to accurately predict the three-point correlation function estimated from simulations.
2020440
The Distribution of Two-dimensional Eccentricity of Sunyaev-Zel'dovich Effect and X-Ray Surface Brightness Profiles
With the triaxial density profile of dark matter halos and the corresponding equilibrium gas distribution, we derive two-dimensional Sunyaev-Zel'dovich (SZ) effect and X-ray surface brightness profiles for clusters of galaxies. It is found that the contour map of these observables can be well approximated by a series of concentric ellipses with scale-dependent eccentricities. The statistical distribution of their eccentricities (or, equivalently, axial ratios) is analyzed by taking into account the orientation of clusters with respect to the line of sight and the distribution of the axial ratios and the concentration parameters of dark matter halos. For clusters of mass 1013 h-1 M☉ at redshift z = 0, the axial ratio is peaked at η ~ 0.9 for both SZ and X-ray profiles. For larger clusters, the deviation from circular distributions is more apparent, with η peaked at η ~ 0.85 for M = 1015 h-1 M☉. To be closer to observations, we further study the axial-ratio distribution for mass-limited cluster samples with the number distribution of clusters at different redshifts described by a modified Press-Schechter model. For a mass limit of value Mlim = 1014 h-1 M☉, the average axial ratio is η ~ 0.84, with a tail extended to η ~ 0.6. With the fast advance of high-quality imaging observations of both SZ effect and X-ray emissions, our analyses provide a useful way to probe cluster halo profiles and therefore to test theoretical halo formation models.
125646338
Alignment between the host and the nearest neighbor Groups
We measure four different types of alignment signals using the galaxy groups of the Sloan Digital Sky Survey Data Release 4 to probe the impact of large scale environment on the distribution of satellite galaxies, on the the orientation of the central and satellite galaxies: (1) the alignment between the distributions of the satellites relative to the direction of the nearest neighbor group (NNG); (2) the alignment between the major axis direction of the central galaxy of the host group (HG) and the direction of the NNG; (3) the alignment between the two major axes of the central galaxies of the HG and NNG; and (4) the alignment between the major axes of the satellites of the HG and the direction of the NNG. We find strong alignment signals of satellite distribution and orientation of central galaxy relative to the direction of the NNG even when the NNG locates beyond $3r_{\rm vir}$ of the host group. The alignment signals are stronger for groups that are more massive and with early type central galaxies. For the orientation of satellite galaxies, however, we do not find any significant alignment signals relative to the direction of the NNG. From these four types of the alignment measures, we conclude that the large scale environment traced by the nearby group mainly impacts the shape of the host dark matter halo, hence impacts the distribution of satellite galaxies and the orientation of central galaxies. Apart from these, there is additional impacts by the large scale environment directly onto the distribution of satellite galaxies.
119170453
A new model for the Milky Way bar
We use Schwarzschild's orbit-superposition technique to construct self-consistent models of the Galactic bar. Using χ2 minimization, we find that the best-fitting Galactic bar model has a pattern speed Ωp = 60 km s−1 kpc−1, disc mass Md = 1.0 × 1011 M⊙ and bar angle θbar = 20° for an adopted bar mass Mbar = 2 × 1010 M⊙. The model can reproduce not only the three-dimensional and projected density distributions but also velocity and velocity dispersion data from the Bulge Radial Velocity Assay (BRAVA) survey. We also predict the proper motions in the range l = [−12°, 12°], b = [−10°, 10°], which appear to be higher than observations in the longitudinal direction. The model is stable within a time-scale of 0.5 Gyr, but appears to deviate from steady state on longer time-scales. Our model can be further tested by future observations such as those from GAIA.
118660680
Canny Algorithm: A New Estimator for Primordial Non-Gaussianities
We utilize the Canny edge detection algorithm as an estimator for primordial non-Gaussianities. In preliminary tests on simulated sky patches with a window size of 57 degrees and multipole moments $l$ up to 1024, we find a $3\sigma$ distinction between maps with local non-Gaussianity $f_{NL}=350$ (or $f_{NL}=-700$) and Gaussian maps. We present evidence that high resolution CMB studies will strongly enhance the sensitivity of the Canny algorithm to non-Gaussianity, making it a promising technique to estimate primordial non-Gaussianity.
17261464
Black hole to bulge mass correlation in Active Galactic Nuclei: a test for the simple unified formation scheme
A mass correlation of central black holes and their spheroids similar to 0.002 (within a factor of three) is suggested by Hubble Space Telescope (HST) and various ground-based CCD photometries of early type galaxies. The near-IR images of quasar hosts and the emission line measurements of Broad Line Region for bright QSOs present a similar correlation, which supports the speculation of an evolutionary linkage between the early active QSO phase and the central black holes in normal galaxies. On the other hand, recent reverberation mapping of a sample of Seyferts shows a broad distribution of black hole to bulge mass ratio with a mean of similar to 10(-3.5), about one magnitude lower than the value in early type galaxies and bright QSOs. Adopting a simple unified formation scheme for QSOs and Seyferts, we will discuss in this letter the dependence of the black hole to bulge mass ratio in Active Galactic Nuclei (AGNs) on the environmental parameters of the host galaxies. We show a broad distribution of the mass correlation could be due to different velocity dispersion of the accreting gas from different Formation mechanism, and the mass ratio in normal galaxies and bright QSOs is probably a limit case of black hole evolution by merger enhanced accretion close to Eddington limit.
125751010
Energy and centrality dependence of the contribution from leading particles to charged-particle pseudorapidity distribution
12882522
THE CLUSTERING OF SDSS GALAXY GROUPS: MASS AND COLOR DEPENDENCE
We use a large sample of galaxy groups selected from the SDSS data release 4 with an adaptive halo-based group finder to probe how the clustering strength of groups depends on their masses and colors. In particular, we determine the relative biases of groups of different masses, as well as that of groups with the same mass but with different colors. In agreement with previous studies, we find that more massive groups are more strongly clustered, and the inferred mass dependence of the halo bias is in good agreement with predictions for the ΛCDM concordance cosmology. Regarding the color dependence, we find that groups with red centrals are more strongly clustered than groups of the same mass but with blue centrals. Similar results are obtained when the color of a group is defined to be the total color of its member galaxies. The color dependence is more prominent in less massive groups and becomes insignificant in groups with masses 1014 h−1 M☉. These results are consistent with those obtained by Yang et al. from an analysis of the 2dFGRS, but inconsistent with those obtained by Berlind et al., who also used an SDSS group catalog. We construct a mock galaxy redshift survey from the large Millennium N-body simulation. Applying our group finder to this mock survey, and analyzing the mock data in exactly the same way as the true data, we are able to accurately recover the intrinsic mass and color dependencies of the halo bias in the model. Interestingly, the semianalytical model reveals the same color dependence of the halo bias as we find in our group catalog. We discuss these results in light of the assembly bias of dark matter halos and the star formation histories of galaxies.
119199394
Modified Chaplygin gas as a unified dark matter and dark energy model and cosmic constraints
A modified Chaplygin gas model (MCG), ρMCG/ρMCG0=[Bs+(1−Bs)a−3(1+B)(1+α)]1/(1+α), as a unified dark matter model and dark energy model, is constrained by using current available cosmic observational data points which include type Ia supernovae, baryon acoustic oscillation and the 7-year full WMAP data points. As a contrast to the consideration in the literature, we do not separate the MCG into two components, i.e. dark mater and dark energy component, but we take it as a whole energy component—a unified dark sector. By using a Markov Chain Monte Carlo method, a tight constraint is obtained: $\alpha= 0.000727_{- 0.00140- 0.00234}^{+ 0.00142+ 0.00391}$, $B=0.000777_{- 0.000302- 0.000697}^{+ 0.000201+ 0.000915}$ and $B_{s}= 0.782_{- 0.0162- 0.0329}^{+ 0.0163+ 0.0307}$.