We examine the statistics of the low-redshift Lyman-alpha forest from smoothed particle hydrodynamic simulations in light of recent improvements in the estimated evolution of the cosmic ultraviolet background (UVB) and recent observations from the Co
smic Origins Spectrograph (COS). We find that the value of the metagalactic photoionization rate required by our simulations to match the observed properties of the low-redshift Lyman-alpha forest is a factor of 5 larger than the value predicted by state-of-the art models for the evolution of this quantity. This mismatch results in the mean flux decrement of the Lyman-alpha forest being underpredicted by at least a factor of 2 (a 10-sigma discrepancy with observations) and a column density distribution of Lyman-alpha forest absorbers systematically and significantly elevated compared to observations over nearly two decades in column density. We examine potential resolutions to this mismatch and find that either conventional sources of ionizing photons (galaxies and quasars) must be significantly elevated relative to current observational estimates or our theoretical understanding of the low-redshift universe is in need of substantial revision.
We examine the star formation histories (SFHs) of galaxies in smoothed particle hydrodynamics (SPH) simulations, compare them to parametric models that are commonly used in fitting observed galaxy spectral energy distributions, and examine the effica
cy of these parametric models as practical tools for recovering the physical parameters of galaxies. The commonly used tau-model, with SFR ~ exp(-t/tau), provides a poor match to the SFH of our SPH galaxies, with a mismatch between early and late star formation that leads to systematic errors in predicting colours and stellar mass-to-light ratios. A one-parameter lin-exp model, with SFR ~ t*exp(-t/tau), is much more successful on average, but it fails to match the late-time behavior of the bluest, most actively star-forming galaxies and the passive, red and dead galaxies. We introduce a 4-parameter model, which transitions from lin-exp to a linear ramp after a transition time, which describes our simulated galaxies very well. We test the ability of these parametrised models to recover (at z=0, 0.5, and 1) the stellar mass-to-light ratios, specific star formation rates, and stellar population ages from the galaxy colours, computed from the full SPH star formation histories using the FSPS code of Conroy et al. (2009). Fits with tau-models systematically overestimate M/L by ~ 0.2 dex, overestimate population ages by ~ 1-2 Gyr, and underestimate sSFR by ~ 0.05 dex. Fits with lin-exp are less biased on average, but the 4-parameter model yields the best results for the full range of galaxies. Marginalizing over the free parameters of the 4-parameter model leads to slightly larger statistical errors than 1-parameter fits but essentially removes all systematic biases, so this is our recommended procedure for fitting real galaxies.
We derive constraints on the matter density Om and the amplitude of matter clustering sig8 from measurements of large scale weak lensing (projected separation R=5-30hmpc) by clusters in the Sloan Digital Sky Survey MaxBCG catalog. The weak lensing si
gnal is proportional to the product of Om and the cluster-mass correlation function xicm. With the relation between optical richness and cluster mass constrained by the observed cluster number counts, the predicted lensing signal increases with increasing Om or sig8, with mild additional dependence on the assumed scatter between richness and mass. The dependence of the signal on scale and richness partly breaks the degeneracies among these parameters. We incorporate external priors on the richness-mass scatter from comparisons to X-ray data and on the shape of the matter power spectrum from galaxy clustering, and we test our adopted model for xicm against N-body simulations. Using a Bayesian approach with minimal restrictive priors, we find sig8(Om/0.325)^{0.501}=0.828 +/- 0.049, with marginalized constraints of Om=0.325_{-0.067}^{+0.086} and sig8=0.828_{-0.097}^{+0.111}, consistent with constraints from other MaxBCG studies that use weak lensing measurements on small scales (R<=2hmpc). The (Om,sig8) constraint is consistent with and orthogonal to the one inferred from WMAP CMB data, reflecting agreement with the structure growth predicted by GR for an LCDM cosmological model. A joint constraint assuming LCDM yields Om=0.298 +/- 0.020 and sig8=0.831 +/- 0.020. Our cosmological parameter errors are dominated by the statistical uncertainties of the large scale weak lensing measurements, which should shrink sharply with current and future imaging surveys.
Building on the legacy of the Sloan Digital Sky Survey (SDSS-I and II), SDSS-III is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the popul
ation of giant planets around other stars. In keeping with SDSS tradition, SDSS-III will provide regular public releases of all its data, beginning with SDSS DR8 (which occurred in Jan 2011). This paper presents an overview of the four SDSS-III surveys. BOSS will measure redshifts of 1.5 million massive galaxies and Lya forest spectra of 150,000 quasars, using the BAO feature of large scale structure to obtain percent-level determinations of the distance scale and Hubble expansion rate at z<0.7 and at z~2.5. SEGUE-2, which is now completed, measured medium-resolution (R=1800) optical spectra of 118,000 stars in a variety of target categories, probing chemical evolution, stellar kinematics and substructure, and the mass profile of the dark matter halo from the solar neighborhood to distances of 100 kpc. APOGEE will obtain high-resolution (R~30,000), high signal-to-noise (S/N>100 per resolution element), H-band (1.51-1.70 micron) spectra of 10^5 evolved, late-type stars, measuring separate abundances for ~15 elements per star and creating the first high-precision spectroscopic survey of all Galactic stellar populations (bulge, bar, disks, halo) with a uniform set of stellar tracers and spectral diagnostics. MARVELS will monitor radial velocities of more than 8000 FGK stars with the sensitivity and cadence (10-40 m/s, ~24 visits per star) needed to detect giant planets with periods up to two years, providing an unprecedented data set for understanding the formation and dynamical evolution of giant planet systems. (Abridged)
Recently Menard et al. detected a subtle but systematic change in the mean color of quasars as a function of their projected separation from foreground galaxies, extending to comoving separations of ~10Mpc/h, which they interpret as a signature of re
ddening by intergalactic dust. We present theoretical models of this remarkable observation, using SPH cosmological simulations of a (50Mpc/h)^3 volume. Our primary model uses a simulation with galactic winds and assumes that dust traces the intergalactic metals. The predicted galaxy-dust correlation function is similar in form to the galaxy-mass correlation function, and reproducing the MSFR data requires a dust-to-metal mass ratio of 0.24, about half the value in the Galactic ISM. Roughly half of the reddening arises in dust that is more than 100Kpc/h from the nearest massive galaxy. We also examine a simulation with no galactic winds, which predicts a much smaller fraction of intergalactic metals (3% vs. 35%) and therefore requires an unphysical dust-to-metal ratio of 2.18 to reproduce the MSFR data. In both models, the signal is dominated by sightlines with E(g-i)=0.001-0.1. The no-wind simulation can be reconciled with the data if we also allow reddening to arise in galaxies up to several x 10^10 Msun. The wind model predicts a mean visual extinction of A_V ~0.0133 mag out to z=0.5, with a sightline-to-sightline dispersion similar to the mean, which could be significant for future supernova cosmology studies. Reproducing the MSFR results in these simulations requires that a large fraction of ISM dust survive its expulsion from galaxies and its residence in the intergalactic medium. Future observational studies that provide higher precision and measure the dependence on galaxy type and environment will allow detailed tests for models of enriched galactic outflows and the survival of IG dust.
The shape of the primordial matter power spectrum Plin(k) encodes critical information on cosmological parameters. At large scales, the observable galaxy power spectrum Pobs(k) is expected to follow the shape of Plin(k), but on smaller scales the eff
ects of nonlinearity and galaxy bias make the ratio Pobs(k)/Plin(k) scale-dependent. We develop a method that can extend the dynamic range of the Plin(k) recovery by incorporating constraints on the galaxy halo occupation distribution (HOD) from the projected galaxy correlation function wp. We devise an analytic model to calculate Pobs(k) in real-space and redshift-space. Once HOD parameters are determined by matching wp for a given cosmological model, galaxy bias is completely specified, and our analytic model predicts both the shape and normalization of Pobs(k). Applying our method to SDSS main galaxy samples, we find that the real-space Pobs(k) follows the shape of the nonlinear matter power spectrum at the 1-2% level up to k=0.2 h/Mpc. When we apply our method to SDSS LRG samples, the linear bias approximation is accurate to 5% at k<0.08 h/Mpc, but the scale-dependence of LRG bias prevents the use of linear theory at k>0.08 h/Mpc. Our HOD model prediction is in good agreement with the recent SDSS LRG Pobs(k) measurements at all measured scales (k<0.2 h/Mpc), naturally explaining the shape of Pobs(k). The Q-model prescription is a poor description of galaxy bias for the LRG samples, and it can lead to biased cosmological parameter estimates when measurements at k>0.1 h/Mpc are included in the analysis. We quantify the potential bias and constraints on cosmological parameters that arise from applying linear theory and Q-model fitting, and we demonstrate the utility of HOD modeling of future high precision measurements of Pobs(k) on quasi-linear scales.
