AR-2019-2020

Figure 8: Correlations between internal halo properties, tidal environment and large-scale bias. (Left Panel:) Spearman rank correlation coefficients, for haloes in bins of mass M vir , between tidal anisotropy and other halo properties. In the legend, each coefficient γ ab is represented by the symbol a ↔ b. (Middle Panel:) Assembly bias trends seen using Spearman rank correlation coefficients γ bc between halo bias b and each internal property c . (Right Panel:) Conditional correlation coefficients γ b 1 c | α for each internal property c . Note that the vertical axis in the middle and right panels is zoomed in by a factor ∼ 3 as compared to the left panel. The right panel shows the main result of this work: each conditional coefficient γ b 1 c | α is substantially smaller in magnitude than the corresponding unconditional coefficient γ b 1 c in the middle panel. Thus, conditioning on tidal anisotropy α largely accounts for the assembly bias trend of all internal halo properties. physics as well as the nature of dark matter and dark energy. Halo assembly bias and cosmic web tidal anisotropy In the hierarchical Λ CDM universe paradigm, galaxies are believed to form within virialized dark matter haloes which merge to form larger ones. Understanding the properties of haloes is, therefore, crucial when one makes predictions for galaxy formation and infer the cosmology from observations. Galaxies and their host haloes are embedded in the large scale structure of the universe known as the cosmic web. This refers to the accumulation of matter into nodes, sheets and filament-like structures leaving behind vast expanses of underdense voids. The web environment of these haloes plays an important role in determining its late-time properties like angular momentum, shape and spin. This could be because haloes experience strong tidal forces and mass inflow rates in anisotropic environments like filaments as compared to more isotropic ones like the centre of a node, thereby affecting their internal properties. The web environment of a halo is quantified in this work by tidal anisotropy α , which is constructed with the tidal tensor. The clustering also seem to correlate with halo properties like formation time, concentration, sub-structure content, spin, shape, velocity dispersion and anisotropy. The dependence of halo clustering on a second property of the halo in addition to mass is now generally referred to as Assembly Bias (AB). The AB is interesting to look at for several reasons. It would help in understanding the physics of structure formation. In the context of galaxy formation, the simplest empirical models link galaxy properties to halo masses alone, so it is interesting to look at what imprints AB leaves on galaxy properties. AB tells us that the large scale clustering some how determines the smaller scale internal properties of the halo. Here, Sujatha Ramakrishnan , Aseem Paranjape , Oliver Hahn and Ravi Sheth question whether this could be because of their mutual dependence on a third intermidiary scale property. This is done by taking the example of a few halo properties, and statistically show that halo AB is largely caused due to tidal anisotropy of the environment. This is done with the help of analysing N-body simulations and measuring halo properties such as shape, dispersion and anisotropy in velocity, spin and concentration. Then, the correlations which exist between halo internal properties and large scale clustering properties are studied to find that it is possible to statistically reduce this correlation when the anisotropy of the tidal environment is kept fixed. Fig. 8 summarises the main result. From this, Ramakrishnan , Paranjape and