Improving the calibration of Type Ia supernovae using late-time light curves
The use of Type la supernovae (SNe Ia) as cosmological standard candles is a key to solving the mystery of dark energy. Improving the calibration of SNe Ia increases their power as cosmological standard candles. We find tentative evidence for a correlation between the late-time light-curve slope and the peak luminosity of SNe Ia in the B band; brighter SNe Ia seem to have shallower light-curve slopes between 100 and 150 d from maximum light. Using a Markov Chain Monte Carlo (MCMC) analysis in calibrating SNe Ia, we are able to simultaneously take into consideration the effect of dust extinction, the luminosity and light-curve width correlation (parametrized by Δm 15 ), and the luminosity and late-time light-curve slope correlation. For the available sample of 11 SNe Ia with well-measured late-time light curves, we find that correcting for the correlation between luminosity and late-time light-curve slope of the SNe Ia leads to an intrinsic dispersion of 0.12 mag in the Hubble diagram. Our results have significant implications for future supernova surveys aimed to illuminate the nature of dark energy.

title: Wavelets and WMAP non-Gaussianity
abstract: We study the statistical properties of the first-year Wilkinson Microwave Anisotropy Probe (WMAP) data on different scales using the spherical Mexican hat wavelet transform. Consistent with the 2004 results of Vielva et al., we find a deviation from Gaussianity in the form of kurtosis of wavelet coefficients on 3-4 scales in the southern Galactic hemisphere. This paper extends the work of Vielva et al. as follows: We find that the non-Gaussian signal shows up more strongly in the form of a larger than expected number of cold pixels and also in the form of scale-scale correlations among wavelet coefficients. We establish the robustness of the non-Gaussian signal under more wide-ranging assumptions regarding the Galactic mask applied to the data and the noise statistics. This signal is unlikely to be due to the usual quadratic term parameterized by the nonlinearity parameter fNL. We use the skewness of the spherical Mexican hat wavelet coefficients to constrain fNL with the first-year WMAP data. Our results constrain fNL to be 50+/-80 at 68% confidence and less than 280 at 99% confidence.

title: A robust distance measurement and dark energy constraints from the spherically averaged correlation function of Sloan Digital Sky Survey luminous red Galaxies
abstract: We measure the effective distance to z = 0.26, DV (0.26), and mh 2 from the overall shape of the spherically-averaged two-point correlati on function of the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) volume-limited luminous red galaxy (LRG) sample, without assuming a dark energy model or a flat Universe. We giv e the mean and covariance matrix of DV (0.26), mh 2 , bh 2 , and ns. We show that these provide an efficient and accurate summary of the volume-limited LRG data. With flat priors on bh 2 and ns (7σWMAP7), we find mh 2 = 0.131 ± 0.020, and rs/DV (0.26) = 0.1466 +0.0068 0.0073 (the ratio of the sound horizon at the drag epoch to the effective distance to z = 0.26). We find that measurements of mh 2 or m are biased low if flux-limited (instead of volume-limited) L RG sample is used. By scaling the spherically-averaged correlation fun ction, we find the Hubble parameter H(0.26) = 79 +12 13 km s 1 Mpc 1 and the angular diameter distance DA(0.26) = 848 +86 88 Mpc. Combining our results with the cosmic microwave background and supernova data, we obtain k = 0.0059 +0.0092 0.0093 andw = 1.023 +0.054 0.053 (assuming a constant dark energy equation of state). We use LasDamas SDSS mock catalogs to compute the covariance matrix of the correlation function, and investigate the use of lognormal catal ogs as an alternative. We find that the input correlation function can be accurately recovered from lognormal catalogs, although they give larger errors on all scales (especially on small sc ales) compared to the mock catalogs derived from cosmological N-body simulations.

title: Dark Energy Search with Supernovae
abstract: To determine the nature of dark energy from observational data, it is important that we use model-independent and optimal methods. We should probe dark energy using its density (allowed to be a free function of cosmic time) instead of its equation of state. We should minimize gravitational lensing effect on supernovae by flux-averaging. We need to include complementary data (for example, from the cosmic microwave background (CMB) and large scale structure (LSS)) in a consistent manner to help break the degeneracy between the dark energy density and the matter density fraction. We should push for ambitious future supernova surveys that can observe a large number of supernovae at the highest possible redshifts. I discuss these and other issues that will be important in our quest to unravel the mystery of the nature of dark energy. Current supernova, CMB, and LSS data already rule out dark energy models with dark energy densities that vary greatly with time; with the cosmological constant model providing an excellent fit to the data. A precise measurement of dark energy density as a free function of cosmic time will have a fundamental impact on particle physics and cosmology.

title: Constraints on generalized extended inflationary models.
abstract: We study the physical constraints on generalized extended inflationary theories, in which the Brans-Dicke field {Phi} couples to the inflaton sector in the form of two arbitrary power-law functions of {Phi}. We find that the most stringent constraints arise from the need to suppress large bubbles and from considerations of the density perturbations generated during extended inflation. We find that there are sizable portions of the parameter spaces in which all the constraints are satisfied.

title: Dark Energy Constraints from Baryon Acoustic Oscillations
abstract: Baryon acoustic oscillations (BAOs) in the galaxy power spectrum allow us to extract the scale of the comoving sound horizon at recombination, a cosmological standard ruler accurately determined by the cosmic microwave background anisotropy data. We examine various issues important in the use of BAOs to probe dark energy. We find that if we assume a flat universe and priors on ?m, ?mh2, and ?bh2 as expected from the Planck mission, the constraints on dark energy parameters (w0, w') scale much less steeply with survey area than (area)-1/2 for a given redshift range. The constraints on the dark energy density ?X(z), however, do scale roughly with (area)-1/2 due to the strong correlation between H(z) and ?m (which reduces the effect of priors on ?m). Dark energy constraints from BAOs are very sensitive to the assumed linear scale of matter clustering and the redshift accuracy of the survey. For a BAO survey with 0.5 ? z ? 2, ? (R) = 0.4 [corresponding to kmax (z = 0) = 0.086 h Mpc-1], and ?z/ (1 + z) = 0.001, we find = (0.115,0.183) and (0.069, 0.104) for survey areas of 1000 and 10,000 deg2, respectively. We find that it is critical to minimize the bias in the scale estimates in order to derive reliable dark energy constraints. For a 1000 (10,000) deg2 BAO survey, a 1 ? bias in ln H (z) leads to a 2 ? (3 ?) bias in w'. The bias in w' due to the same scale bias from ln DA (z) is slightly smaller and opposite in sign. The results from this paper will be useful in assessing different proposed BAO surveys and guiding the design of optimal dark energy detection strategies.

title: MathGR: a tensor and GR computation package to keep it simple
abstract: We introduce the MathGR package, written in Mathematica. The package can manipulate tensor and GR calculations with either abstract or explicit indices, simplify tensors with permutational symmetries, decompose tensors from abstract indices to partially or completely explicit indices and convert partial derivatives into total derivatives. Frequently used GR tensors and a model of FRW universe with ADM type perturbations are predefined. The package is built around the philosophy to "keep it simple", and makes use of latest tensor technologies of Mathematica.

title: SYSTEMATIC ERRORS IN THE DETERMINATION OF HUBBLE CONSTANT DUE TO THE ASPHERICITY AND NONISOTHERMALITY OF CLUSTERS OF GALAXIES
abstract: We present statistical studies on the systematic errors in the determination of the Hubble constant H0 from joint analyses of X-ray and the Sunyaev-Zel'dovich (SZ) effect of clusters of galaxies. We focus on the effects of their triaxiality and nonisothermality. From the triaxial model of dark matter halos obtained from numerical simulations, we derive the distribution of the intracluster gas under the assumption of the hydrodynamic equilibrium. Both the isothermal and the polytropic gases are investigated. We run Monte Carlo simulations to generate samples of clusters according to the distributions of their masses, axial ratios, concentration parameters, and line-of-sight directions. The estimation of H0 is done by fitting X-ray and SZ profiles of a triaxial cluster with the isothermal and spherical β model. We find that for a sample of clusters with M = 1014 h-1 M☉ and z = 0.1, the estimated H0 is positively biased with H(estimated) ≈ 1.05H0(true) and H(estimated) ≈ 1.05H0(true) for the isothermal case. For the polytropic case with γ = 1.15, the bias is large with H(estimated) ≈ 1.35H0(true) and H(estimated) ≈ 3H0(true). For a mass-limited sample of clusters with Mlim = 1013 h-1 M☉, the results are similar. On the other hand, such a large overestimation has not been seen in real observations. It is noticed that the β-value for observed clusters is within the range of 0.5-0.8. Considering only the subsample in Monte Carlo simulations with β in the range of 0.5-0.8, we have H(estimated) = 1.002H0(true) and H(estimated) = 0.994H0(true) for the isothermal and polytropic cases, respectively. We further find that the value of β is more sensitive to the intrinsic asphericity of clusters than the axial ratio of two-dimensional X-ray images η is. Limiting to clusters with β ≥ 0.5 essentially excludes highly aspherical clusters from the sample. From this subsample of clusters, we can get a fair estimate on H0.

title: Revisiting generalized Chaplygin gas as a unified dark matter and dark energy model
abstract: In this paper, we revisit the generalized Chaplygin gas (GCG) model as a unified dark matter and dark energy model. The energy density of GCG model is given as ρGCG/ρGCG0=[Bs+(1−Bs)a−3(1+α)]1/(1+α), where α and Bs are two model parameters which will be constrained by type Ia supernova as standard candles, baryon acoustic oscillation as standard rulers and the seventh year full WMAP data points. In this paper, we will not separate GCG into dark matter and dark energy parts any more as adopted in the literature. By using the Markov Chain Monte Carlo method, we find the results $\alpha=0.00126_{-0.00126- 0.00126}^{+ 0.000970+ 0.00268}$ and $B_{s}= 0.775_{-0.0161- 0.0338}^{+ 0.0161+ 0.0307}$.

title: GEM technical design report

title: Observational constraints to Ricci dark energy model by using: SN, BAO, OHD, fgas data sets
abstract: We perform a global constraint on the Ricci dark energy model with both the flat case and the non-flat case, using the Markov Chain Monte Carlo (MCMC) method and the combined observational data from the cluster X-ray gas mass fraction, Supernovae of type Ia (397), baryon acoustic oscillations, current Cosmic Microwave Background, and the observational Hubble function. In the flat model, we obtain the best fit values of the parameters in 1σ,2σ regions: Ωm0 = 0.2927+0.0420+0.0542−0.0323−0.0388, α = 0.3823+0.0331+0.0415−0.0418−0.0541, Age/Gyr = 13.48+0.13+0.17−0.16−0.21, H0 = 69.09+2.56+3.09−2.37−3.39. In the non-flat model, the best fit parameters are found in 1σ,2σ regions:Ωm0 = 0.3003+0.0367+0.0429−0.0371−0.0423, α = 0.3845+0.0386+0.0521−0.0474−0.0523, Ωk = 0.0240+0.0109+0.0133−0.0130−0.0153, Age/Gyr = 12.54+0.51+0.65−0.37−0.49, H0 = 72.89+3.31+3.88−3.05−3.72. Compared to the constraint results in the ΛCDM model by using the same datasets, it is shown that the current combined datasets prefer the ΛCDM model to the Ricci dark energy model.