34 research outputs found

    The clustering of the first galaxy halos

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    We explore the clustering properties of high redshift dark matter halos, focusing on halos massive enough to host early generations of stars or galaxies at redshift 10 and greater. Halos are extracted from an array of dark matter simulations able to resolve down to the "mini-halo" mass scale at redshifts as high as 30, thus encompassing the expected full mass range of halos capable of hosting luminous objects and sources of reionization. Halo clustering on large-scales agrees with the Sheth, Mo & Tormen halo bias relation within all our simulations, greatly extending the regime where large-scale clustering is confirmed to be "universal" at the 10-20% level (which means, for example, that 3sigma halos of cluster mass at z=0 have the same large-scale bias with respect to the mass distribution as 3sigma halos of galaxy mass at z=10). However, on small-scales, the clustering of our massive halos (> ~10^9 Msun/h) at these high redshifts is stronger than expected from comparisons with small-scale halo clustering extrapolated from lower redshifts. This implies "non-universality" in the scale-dependence of halo clustering, at least for the commonly used parameterizations of the scale-dependence of bias that we consider. We provide a fit for the scale-dependence of bias in our results. This study provides a basis for using extraordinarily high redshift galaxies (redshift ~10) as a probe of cosmology and galaxy formation at its earliest stages. We show also that mass and halo kinematics are strongly affected by finite simulation volumes. This suggests the potential for adverse affects on gas dynamics in hydrodynamic simulations of limited volumes, such as is typical in simulations of the formation of the "first stars", though further study is warranted.Comment: MNRAS accepte

    Self-similarity, small-world, scale-free scaling, disassortativity, and robustness in hierarchical lattices

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    In this paper, firstly, we study analytically the topological features of a family of hierarchical lattices (HLs) from the view point of complex networks. We derive some basic properties of HLs controlled by a parameter qq. Our results show that scale-free networks are not always small-world, and support the conjecture that self-similar scale-free networks are not assortative. Secondly, we define a deterministic family of graphs called small-world hierarchical lattices (SWHLs). Our construction preserves the structure of hierarchical lattices, while the small-world phenomenon arises. Finally, the dynamical processes of intentional attacks and collective synchronization are studied and the comparisons between HLs and Barab{\'asi}-Albert (BA) networks as well as SWHLs are shown. We show that degree distribution of scale-free networks does not suffice to characterize their synchronizability, and that networks with smaller average path length are not always easier to synchronize.Comment: 26 pages, 8 figure

    Canonical correlation analysis of infant's size at birth and maternal factors: a study in rural northwest Bangladesh.

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    This analysis was conducted to explore the association between 5 birth size measurements (weight, length and head, chest and mid-upper arm [MUAC] circumferences) as dependent variables and 10 maternal factors as independent variables using canonical correlation analysis (CCA). CCA considers simultaneously sets of dependent and independent variables and, thus, generates a substantially reduced type 1 error. Data were from women delivering a singleton live birth (n = 14,506) while participating in a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural Bangladesh. The first canonical correlation was 0.42 (P<0.001), demonstrating a moderate positive correlation mainly between the 5 birth size measurements and 5 maternal factors (preterm delivery, early pregnancy MUAC, infant sex, age and parity). A significant interaction between infant sex and preterm delivery on birth size was also revealed from the score plot. Thirteen percent of birth size variability was explained by the composite score of the maternal factors (Redundancy, RY/X = 0.131). Given an ability to accommodate numerous relationships and reduce complexities of multiple comparisons, CCA identified the 5 maternal variables able to predict birth size in this rural Bangladesh setting. CCA may offer an efficient, practical and inclusive approach to assessing the association between two sets of variables, addressing the innate complexity of interactions
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