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We investigate the spatial distribution of Ly α-emitting galaxies (LAEs) at z ≈ 2.67, selected from the NOAO Deep Wide-Field Survey, using two-point statistics and topological diagnostics adopted from network science. We measure the clustering length, r 0 ≈ 4  h −1 Mpc, and the bias,   |$b_{\mathrm{ LAE}} = 2.2^{+0.2}_{-0.1}$|⁠. Fitting the clustering with halo occupation distribution (HOD) models results in two disparate possibilities: (1) where the fraction of central galaxies is <1 per cent in haloes of mass >1012 M⊙ and (2) where the fraction is ≈20 per cent. We refer to these two scenarios as the 'Dusty Core Scenario' for Model#1, since most of the central galaxies in massive haloes are dead in Ly α emission, and the 'Pristine Core Scenario' for Model#2, since the central galaxies are bright in Ly α emission. Traditional two-point statistics cannot distinguish between these disparate models given the current data sets. To overcome this degeneracy, we generate mock catalogues for each HOD model using a high-resolution N -body simulation and adopt a network statistics approach, which provides excellent topological diagnostics for galaxy point distributions. We find three topological anomalies from the spatial distribution of observed LAEs, which are not reproduced by the HOD mocks. We find that Model#2 matches better all network statistics than Model#1, suggesting that the central galaxies in >1012  h −1 M⊙ haloes at z ≈ 2.67 need to be less dusty to be bright as LAEs, potentially implying some replenishing channels of pristine gas such as the cold mode accretion. [ABSTRACT FROM AUTHOR]

We apply simple analyses techniques developed for the study of complex networks to the study of the cosmic web, the large-scale galaxy distribution. In this paper, we measure three network centralities (ranks of topological importance): degree centrality (DC), closeness centrality (CL), and betweenness centrality (BC) from a network built from the Cosmological Evolution Survey (COSMOS) catalogue. We define eight galaxy populations according to the centrality measures: void, wall, and cluster by DC; main branch and dangling leaf by BC; and kernel, backbone, and fracture by CL. We also define three populations by Voronoi tessellation density to compare these with the DC selection. We apply the topological selections to galaxies in the (photometric) redshift range 0.91 < z < 0.94 from the COSMOS survey, and explore whether the red and blue galaxy populations show differences in colour, star formation rate, and stellar mass in the different topological regions. Despite the limitations and uncertainties associated with using photometric redshift and indirect measurements of galactic parameters, the preliminary results illustrate the potential of network analysis. Future surveys will provide better statistical samples to test and improve this 'network cosmology'. [ABSTRACT FROM AUTHOR]

We present a physical model for the origin of dust-obscured galaxies (DOGs), a class of high-redshift ultraluminous infrared galaxies (ULIRGs) selected at 24 μm which are particularly optically faint . By combining N-body/smoothed particle hydrodynamic simulations of high-redshift galaxy evolution with 3D polychromatic dust radiative transfer models, we find that luminous DOGs (with mJy at ) are well modelled as extreme gas-rich mergers in massive haloes, with elevated star formation rates (SFR; ) and/or significant active galactic nuclei (AGN) growth , whereas less luminous DOGs are more diverse in nature. At final coalescence, merger-driven DOGs transition from being starburst dominated to AGN dominated, evolving from a ‘bump’ to a power-law (PL) shaped mid-IR (Infrared Array Camera, IRAC) spectral energy distribution (SED). After the DOG phase, the galaxy settles back to exhibiting a ‘bump’ SED with bluer colours and lower SFRs. While canonically PL galaxies are associated with being AGN dominated, we find that the PL mid-IR SED can owe both to direct AGN contribution and to a heavily dust obscured stellar bump at times that the galaxy is starburst dominated. Thus, PL galaxies can be either starburst or AGN dominated. Less luminous DOGs can be well-represented either by mergers or by massive secularly evolving gas-rich disc galaxies (with ). By utilizing similar models as those employed in the submillimetre galaxy (SMG) formation study of Narayanan et al., we investigate the connection between DOGs and SMGs. We find that the most heavily star-forming merger-driven DOGs can be selected as submillimetre galaxies, while both merger-driven and secularly evolving DOGs typically satisfy the BzK selection criteria. The model SEDs from the simulated galaxies match observed data reasonably well, though Mrk 231 and Arp 220 templates provide worse matches. Our models provide testable predictions of the physical masses, dust temperatures, CO linewidths and location on the relation of DOGs. Finally, we provide public SED templates derived from these simulations. [ABSTRACT FROM AUTHOR]

The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 108M☉. The two-point correlation function of these simulated galaxies follows a single power law, ξ (r) ∼ r-1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the two simulated galaxy point distributions have the same abundance and two-point correlation function, their spatial distributions are very different; most prominently, filamentary structures, absent in Lévy fractals. To quantify these missing topologies, we adopt network analysis tools and measure diameter, giant component, and transitivity from networks built by a conventional friends-of-friends recipe with various linking lengths. Unlike the abundance and two-point correlation function, these network quantities reveal a clear separation between the two simulated distributions; therefore, the galaxy distribution simulated by Illustris is not a Lévy fractal quantitatively. We find that the described network quantities offer an efficient tool for discriminating topologies and for comparing observed and theoretical distributions. [ABSTRACT FROM AUTHOR]