Preferential concentration of inertial sub-kolmogorov particles. The roles of mass loading of particles, Stokes and Reynolds numbers

Turbulent flows laden with inertial particles present multiple open questions and are a subject of great interest in current research. Due to their higher density compared to the carrier fluid, inertial particles tend to form high concentration regions, i.e. clusters, and low concentration regions, i.e. voids, due to the interaction with the turbulence. In this work, we present an experimental investigation of the clustering phenomenon of heavy sub-Kolmogorov particles in homogeneous isotropic turbulent flows. Three control parameters have been varied over significant ranges: $Re_{\lambda} \in [170 - 450]$, $St\in [0.1 - 5]$ and volume fraction $\phi_v\in [2\times 10^{-6} - 2\times 10^{-5}]$. The scaling of clustering characteristics, such as the distribution of Vorono\"i areas and the dimensions of cluster and void regions, with the three parameters are discussed. In particular, for the polydispersed size distributions considered here, clustering is found to be enhanced strongly (quasi-linearly) by $Re_{\lambda}$ and noticeably (with a square-root dependency) with $\phi_v$, while the cluster and void sizes, scaled with the Kolmogorov lengthscale $\eta$, are driven primarily by $Re_{\lambda}$. Cluster length $\sqrt{\langle A_c \rangle}$ scales up to $\approx 100 {\eta}$, measured at the highest $Re_{\lambda}$, while void length $\sqrt{\langle A_v \rangle}$ scaled also with $\eta$ is typically two times larger ($\approx 200 {\eta}$). The lack of sensitivity of the above characteristics to the Stokes number lends support to the "sweep-stick" particle accumulation scenario. The non-negligible influence of the volume fraction, however, is not considered by that model and can be connected with collective effects

From patterned response dependency to structured covariate dependency: categorical-pattern-matching

Data generated from a system of interest typically consists of measurements from an ensemble of subjects across multiple response and covariate features, and is naturally represented by one response-matrix against one covariate-matrix. Likely each of these two matrices simultaneously embraces heterogeneous data types: continuous, discrete and categorical. Here a matrix is used as a practical platform to ideally keep hidden dependency among/between subjects and features intact on its lattice. Response and covariate dependency is individually computed and expressed through mutliscale blocks via a newly developed computing paradigm named Data Mechanics. We propose a categorical pattern matching approach to establish causal linkages in a form of information flows from patterned response dependency to structured covariate dependency. The strength of an information flow is evaluated by applying the combinatorial information theory. This unified platform for system knowledge discovery is illustrated through five data sets. In each illustrative case, an information flow is demonstrated as an organization of discovered knowledge loci via emergent visible and readable heterogeneity. This unified approach fundamentally resolves many long standing issues, including statistical modeling, multiple response, renormalization and feature selections, in data analysis, but without involving man-made structures and distribution assumptions. The results reported here enhance the idea that linking patterns of response dependency to structures of covariate dependency is the true philosophical foundation underlying data-driven computing and learning in sciences.Comment: 32 pages, 10 figures, 3 box picture

The Panchromatic Hubble Andromeda Treasury. Progression of Large-Scale Star Formation across Space and Time in M31

We investigate the clustering of early-type stars younger than 300 Myr on galactic scales in M31. Based on the stellar photometric catalogs of the Panchromatic Hubble Andromeda Treasury program that also provides stellar parameters derived from the individual energy distributions, our analysis is focused on the young stars in three star-forming regions, located at galactocentric distances of about 5, 10, and 15 kpc, corresponding to the inner spiral arms, the ring structure, and the outer arm, respectively. We apply the two-point correlation function to our selected sample to investigate the clustering behavior of these stars across different time- and length-scales. We find that young stellar structure survives across the whole extent of M31 longer than 300 Myr. Stellar distribution in all regions appears to be self-similar, with younger stars being systematically more strongly clustered than the older, which are more dispersed. The observed clustering is interpreted as being induced by turbulence, the driving source for which is probably gravitational instabilities driven by the spiral arms, which are stronger closer to the galactic centre.Comment: 10 pages, 5 figures. To appear in "LESSONS FROM THE LOCAL GROUP - A Conference in Honour of David Block and Bruce Elmegreen" eds. Freeman, K.C., Elmegreen, B.G., Block, D.L. & Woolway, M. (Springer: New York

Probing the Radio Loud/Quiet AGN dichotomy with quasar clustering

We investigate the clustering properties of 45441 radio-quiet quasars (RQQs) and 3493 radio-loud quasars (RLQs) drawn from a joint use of the Sloan Digital Sky Survey (SDSS) and Faint Images of the Radio Sky at 20 cm (FIRST) surveys in the range $0.3<z<2.3$. This large spectroscopic quasar sample allow us to investigate the clustering signal dependence on radio-loudness and black hole (BH) virial mass. We find that RLQs are clustered more strongly than RQQs in all the redshift bins considered. We find a real-space correlation length of $r_{0}=6.59_{-0.24}^{+0.33}\,h^{-1}\,\textrm{Mpc}$ and $r_{0}=10.95_{-1.58}^{+1.22}\,h^{-1}\,\textrm{Mpc}$ {\normalsize{}for} RQQs and RLQs, respectively, for the full redshift range. This implies that RLQs are found in more massive host haloes than RQQs in our samples, with mean host halo masses of $\sim4.9\times10^{13}\,h^{-1}\,M_{\odot}$ and $\sim1.9\times10^{12}\,h^{-1}\,M_{\odot}$, respectively. Comparison with clustering studies of different radio source samples indicates that this mass scale of $\gtrsim1\times10^{13}\,h^{-1}\,M_{\odot}$ is characteristic for the bright radio-population, which corresponds to the typical mass of galaxy groups and galaxy clusters. The similarity we find in correlation lengths and host halo masses for RLQs, radio galaxies and flat-spectrum radio quasars agrees with orientation-driven unification models. Additionally, the clustering signal shows a dependence on black hole (BH) mass, with the quasars powered by the most massive BHs clustering more strongly than quasars having less massive BHs. We suggest that the current virial BH mass estimates may be a valid BH proxies for studying quasar clustering. We compare our results to a previous theoretical model that assumes that quasar activityComment: 15 pages, 13 figures, A&A in pres

Measuring the growth of matter fluctuations with third-order galaxy correlations

Measurements of the linear growth factor $D$ at different redshifts $z$ are key to distinguish among cosmological models. One can estimate the derivative $dD(z)/d\ln(1+z)$ from redshift space measurements of the 3D anisotropic galaxy two-point correlation $\xi(z)$, but the degeneracy of its transverse (or projected) component with galaxy bias $b$, i.e. $\xi_{\perp}(z) \propto\ D^2(z) b^2(z)$, introduces large errors in the growth measurement. Here we present a comparison between two methods which break this degeneracy by combining second- and third-order statistics. One uses the shape of the reduced three-point correlation and the other a combination of third-order one- and two-point cumulants. These methods use the fact that, for Gaussian initial conditions and scales larger than $20$ $h^{-1}$Mpc, the reduced third-order matter correlations are independent of redshift (and therefore of the growth factor) while the third-order galaxy correlations depend on $b$. We use matter and halo catalogs from the MICE-GC simulation to test how well we can recover $b(z)$ and therefore $D(z)$ with these methods in 3D real space. We also present a new approach, which enables us to measure $D$ directly from the redshift evolution of second- and third-order galaxy correlations without the need of modelling matter correlations. For haloes with masses lower than $10^{14}$ $h^{-1}$M$_\odot$, we find $10$ deviations between the different estimates of $D$, which are comparable to current observational errors. At higher masses we find larger differences that can probably be attributed to the breakdown of the bias model and non-Poissonian shot noise.Comment: 24 pages, 20 figures, 2 tables, accepted for publication in MNRA