Galaxies in LCDM with Halo Abundance Matching: luminosity-velocity relation, baryonic mass-velocity relation, velocity function and clustering

It has long been regarded as difficult for a cosmological model to account simultaneously for the galaxy luminosity, mass, and velocity distributions. We revisit this issue using a modern compilation of observational data along with the best available large-scale cosmological simulation of dark matter. We find that the standard cosmological model, used in conjunction with halo abundance matching (HAM) and simple dynamical corrections, fits all basic statistics of galaxies with circular velocities Vcirc > 80 km/s. Our observational constraint is the luminosity-velocity relation which allows all types of galaxies to be included. We have compiled data for a variety of galaxies ranging from dwarf irregulars to giant ellipticals. The data present a clear monotonic luminosity-velocity relation from 50 km/s to 500 km/s, with a bend below 80 km/s and a systematic offset between late- and early-type galaxies. For comparison to theory, we employ our LCDM "Bolshoi" simulation of dark matter, which has unprecedented mass and force resolution. We use halo abundance matching to assign rank-ordered galaxy luminosities to the dark matter halos. The resulting predictions for the luminosity-velocity relation are in excellent agreement with the available data on both early-type and late-type galaxies for the luminosity range from Mr = -14-22. We also compare our predictions for the "cold" baryon mass (i.e., stars and cold gas) of galaxies as a function of circular velocity with the available observations, again finding a very good agreement. The predicted circular velocity function is in agreement with the galaxy velocity function for 80-400 km/s. However, we find that the dark matter halos with Vcirc < 80 km/s are much more abundant than observed galaxies with the same Vcirc . We find that the two-point correlation function of galaxies in our model matches very well the results from the SDSS.Comment: 40 pages, 18 figures, published in Ap

Heavy particle concentration in turbulence at dissipative and inertial scales

Spatial distributions of heavy particles suspended in an incompressible isotropic and homogeneous turbulent flow are investigated by means of high resolution direct numerical simulations. In the dissipative range, it is shown that particles form fractal clusters with properties independent of the Reynolds number. Clustering is there optimal when the particle response time is of the order of the Kolmogorov time scale $\tau_\eta$. In the inertial range, the particle distribution is no longer scale-invariant. It is however shown that deviations from uniformity depend on a rescaled contraction rate, which is different from the local Stokes number given by dimensional analysis. Particle distribution is characterized by voids spanning all scales of the turbulent flow; their signature in the coarse-grained mass probability distribution is an algebraic behavior at small densities.Comment: 4 RevTeX pgs + 4 color Figures included, 1 figure eliminated second part of the paper completely revise

Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology

Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data. In particular, we perform the first study that involves more than two datasets. We discuss the algorithmic issues required to convert the approach into a practical computational tool and apply the technique to new gene expression data quantifying the molecular changes in four tissue types due to different dosages of an experimental panPPAR agonist in mouse. This study is of interest in toxicology because, whilst PPARs form potential therapeutic targets for diabetes, it is known that they can induce serious side-effects. Our results show that the practical simultaneous non-negative matrix factorization developed here can add value to the data analysis. In particular, we find that factorizing the data as a single object allows us to distinguish between the four tissue types, but does not correctly reproduce the known dosage level groups. Applying our new approach, which treats the four tissue types as providing distinct, but related, datasets, we find that the dosage level groups are respected. The new algorithm then provides separate gene list orderings that can be studied for each tissue type, and compared with the ordering arising from the single factorization. We find that many of our conclusions can be corroborated with known biological behaviour, and others offer new insights into the toxicological effects. Overall, the algorithm shows promise for early detection of toxicity in the drug discovery process

Interlinkages and structural changes in cross-border liabilities: a network approach

We study the international interbank market through a geometrical and a topological analysis of empirical data. The geometrical analysis of the time series of cross-country liabilities shows that the systematic information of the interbank international market is contained in a space of small dimension, from which a topological characterization could be conveniently carried out. Weighted and complete networks of financial linkages across countries are developed, for which continuous clustering, degree centrality and closeness centrality are computed. The behavior of these topological coefficients reveals an important modification acting in the financial linkages in the period 1997-2011. Here we show that, besides the generalized clustering increase, there is a persistent increment in the degree of connectivity and in the closeness centrality of some countries. These countries seem to correspond to critical locations where tax policies might provide opportunities to shift debts. Such critical locations highlight the role that specific countries play in the network structure and helps to situates the turbulent period that has been characterizing the global financial system since the Summer 2007 as the counterpart of a larger structural change going on for a more than one decade.Comment: 24 pages, 11 figure

The Tully-Fisher and mass-size relations from halo abundance matching

The Tully-Fisher relation (TFR) expresses the connection between rotating galaxies and the dark matter haloes they inhabit, and therefore contains a wealth of information about galaxy formation. We construct a general framework to investigate whether models based on halo abundance matching are able to reproduce the observed stellar mass TFR and mass-size relation (MSR), and use the data to constrain galaxy formation parameters. Our model tests a range of plausible scenarios, differing in the response of haloes to disc formation, the relative angular momentum of baryons and dark matter, the impact of selection effects, and the abundance matching parameters. We show that agreement with the observed TFR puts an upper limit on the scatter between galaxy and halo properties, requires weak or reversed halo contraction, and favours selection effects that preferentially eliminate fast-rotating galaxies. The MSR constrains the ratio of the disc to halo specific angular momentum to be approximately in the range 0.6-1.2. We identify and quantify two problems that models of this nature face. (1) They predict too large an intrinsic scatter for the MSR, and (2) they predict too strong an anticorrelation between the TFR and MSR residuals. We argue that resolving these problems requires introducing a correlation between stellar surface density and enclosed dark matter mass. Finally, we explore the expected difference between the TFRs of central and satellite galaxies, finding that in the favoured models this difference should be detectable in a sample of ~700 galaxies.Comment: 27 pages, 10 figures; revised to match published MNRAS versio

Semi-empirical catalog of early-type galaxy-halo systems: dark matter density profiles, halo contraction and dark matter annihilation strength

With SDSS galaxy data and halo data from up-to-date N-body simulations we construct a semi-empirical catalog (SEC) of early-type systems by making a self-consistent bivariate statistical match of stellar mass (M_star) and velocity dispersion (sigma) with halo virial mass (M_vir). We then assign stellar mass profile and velocity dispersion profile parameters to each system in the SEC using their observed correlations with M_star and sigma. Simultaneously, we solve for dark matter density profile of each halo using the spherical Jeans equation. The resulting dark matter density profiles deviate in general from the dissipationless profile of NFW or Einasto and their mean inner density slope and concentration vary systematically with M_vir. Statistical tests of the distribution of profiles at fixed M_vir rule out the null hypothesis that it follows the distribution predicted by N-body simulations for M_vir ~< 10^{13.5-14.5} M_solar. These dark matter profiles imply that dark matter density is, on average, enhanced significantly in the inner region of halos with M_vir ~< 10^{13.5-14.5} M_solar supporting halo contraction. The main characteristics of halo contraction are: (1) the mean dark matter density within the effective radius has increased by a factor varying systematically up to ~ 3-4 at M_vir = 10^{12} M_solar, and (2) the inner density slope has a mean of ~ 1.3 with rho(r) ~ r^{-alpha} and a halo-to-halo rms scatter of rms(alpha) ~ 0.4-0.5 for 10^{12} M_solar ~< M_vir ~< 10^{13-14} M_solar steeper than the NFW profile (alpha=1). Based on our results we predict that halos of nearby elliptical and lenticular galaxies can, in principle, be promising targets for gamma-ray emission from dark matter annihilation.Comment: 43 pages, 20 figures, JCAP, revised and accepted versio