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The apparent anisotropies of the galaxy clustering in observable redshift space provide a unique opportunity to simultaneously probe cosmic expansion and gravity on cosmological scales via the Alcock--Paczynski effect and redshift-space distortions. While the improved theoretical models have been proposed and developed to describe the apparent anisotropic clustering at weakly non-linear scales, the applicability of these models is still limited in the presence of the non--perturbative smearing effect caused by the randomness of the relative velocities. Although the cosmological constraint from the anisotropic clustering will be certainly improved with a more elaborate theoretical model, we here consider an alternative way by using the statistical power of both the power spectrum and bispectrum at large scales. Based on the Fisher matrix analysis, we estimate the benefit of combining the power spectra and bispectra, finding that the constraints on the cosmic expansion and growth of structure will be improved by a factor of two. This compensates for the loss of constraining power using the power spectrum alone due to the randomness of the relative velocities., Comment: 11 pages, 8 figures, preprint number YITP-15-7

The anisotropic galaxy clustering on large scales provides us with a unique opportunity to probe into the gravity theory through the redshift-space distortions (RSDs) and the Alcock-Paczynski effect. Using the multipole power spectra up to hexadecapole (ell=4), of the Luminous Red Galaxy (LRG) sample in the data release 7 (DR7) of the Sloan Digital Sky Survey II (SDSS-II), we obtain simultaneous constraints on the linear growth rate f, angular diameter distance D_A, and Hubble parameter H at redshift z = 0.3. For this purpose, we first extensively examine the validity of a theoretical model for the non-linear RSDs using mock subhalo catalogues from N-body simulations, which are constructed to match with the observed multipole power spectra. We show that the input cosmological parameters of the simulations can be recovered well within the error bars by comparing the multipole power spectra of our theoretical model and those of the mock subhalo catalogues. We also carefully examine systematic uncertainties in our analysis by testing the dependence on prior assumption of the theoretical model and the range of wavenumbers to be used in the fitting. These investigations validate that the theoretical model can be safely applied to the real data. Thus, our results from the SDSS DR7 LRG sample are robust including systematics of theoretical modeling; f(z = 0.3) sigma_8(z = 0.3) =0.49+-0.08(stat.)+-0.04(sys.), D_A (z = 0.3) =968+-42(stat.)+-17(sys.)[Mpc], H (z = 0.3) =81.7+-5.0(stat.)+-3.7(sys.)[km/s/Mpc]. We believe that our method to constrain the cosmological parameters using subhaloes catalogues will be useful for more refined samples like CMASS and LOWZ catalogues in the Baryon Oscillation Spectroscopic Survey in SDSS-III., Comment: accepted for publication in MNRAS

We model the apparent clustering anisotropy of Luminous Red Galaxies (LRGs) in the Sloan Digital Sky Survey using subhalos identified in cosmological $N$-body simulations. We first conduct a Markov-chain Monte Carlo analysis on the parameters characterizing subhalos hosting LRGs assuming a specific $\Lambda$CDM cosmology on which we run the simulations. We show that simple models with central and satellite subhalos can explain the observed multipole moments of the power spectrum up to hexadecapole on large scales ($k\lesssim0.3~h\mathrm{Mpc}^{-1}$). A satellite fraction of $20$ to $30$ per cent is favored weakly depending on the detail of the model. The fraction is shown to be robust when we adopt a more refined model based on the halo occupation number from the literature. We then vary cosmological parameters controlling the anisotropy in redshift-space effectively by deforming the simulation box (the Alcock-Paczynski effect) and changing the amplitude of the velocities (the redshift-space distortions). We demonstrate that we can constrain the geometry of the universe, the structure growth rate, and the parameters characterizing LRGs simultaneously. This is a step toward cosmological analysis with realistic bias description beyond empirical bias functions with nuisance parameters., Comment: 18 pages, 21 figures. HOD analysis added. Accepted for publication in MNRAS

Redshift-space distortions (RSD) offer an attractive method to measure the growth of cosmic structure on large scales, and combining with the measurement of the cosmic expansion history, it can be used as cosmological tests of gravity. With the advent of future galaxy redshift surveys aiming at precisely measuring the RSD, an accurate modeling of RSD going beyond linear theory is a critical issue in order to detect or disprove small deviations from general relativity (GR). While several improved models of RSD have been recently proposed based on the perturbation theory (PT), the framework of these models heavily relies on GR. Here, we put forward a new PT prescription for RSD in general modified gravity models. As a specific application, we present theoretical predictions of the redshift-space power spectra in f(R) gravity model, and compare them with N-body simulations. Using the PT template that takes into account the effects of both modifications of gravity and RSD properly, we successfully recover the fiducial model parameter in N-body simulations in an unbiased way. On the other hand, we found it difficult to detect the scale dependence of the growth rate in a model-independent way based on GR templates., Comment: 17 pages, 9 figures, version accepted for publication in PRD

The rate of increase of global-mean surface air temperature (SAT(sub g)) has apparently slowed during the last decade. We investigated the extent to which state-of-the-art general circulation models (GCMs) can capture this hiatus period by using multimodel ensembles of historical climate simulations. While the SAT(sub g) linear trend for the last decade is not captured by their ensemble means regardless of differences in model generation and external forcing, it is barely represented by an 11-member ensemble of a GCM, suggesting an internal origin of the hiatus associated with active heat uptake by the oceans. Besides, we found opposite changes in ocean heat uptake efficiency (k), weakening in models and strengthening in nature, which explain why the models tend to overestimate the SAT(sub g) trend. The weakening of k commonly found in GCMs seems to be an inevitable response of the climate system to global warming, suggesting the recovery from hiatus in coming decades.