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The observable universe contains density perturbations on scales larger than any finite volume survey. Perturbations on scales larger than a survey can measure degrade its power to constrain cosmological parameters. The dependence of survey observables such as the weak lensing power spectrum on these long-wavelength modes results in super-sample covariance. Accurately forecasting parameter constraints for future surveys requires accurately accounting for the super-sample effects. If super-sample covariance is in fact a major component of the survey error budget, it may be necessary to investigate mitigation strategies that constrain the specific realization of the long-wavelength modes. We present a Fisher matrix based formalism for approximating the magnitude of super-sample covariance and the effectiveness of mitigation strategies for realistic survey geometries. We implement our formalism in the public code SuperSCRAM: Super-Sample Covariance Reduction and Mitigation. We illustrate SuperSCRAM with an example application, where the modes contributing to super-sample covariance in the WFIRST weak lensing survey are constrained by the low-redshift galaxy number counts in the wider LSST footprint. We find that super-sample covariance increases the volume of the error ellipsoid in 7D cosmological parameter space by a factor of 4.5 relative to Gaussian statistical errors only, but our simple mitigation strategy more than halves the contamination, to a factor of 2.0., Comment: 32 pages, 7 figures, 1 table, comments/suggestions welcome!

We present measurements of the Baryon Acoustic Oscillation (BAO) scale in redshift-space using the clustering of quasars. We consider a sample of 147,000 quasars from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) distributed over 2044 square degrees with redshifts $0.8 < z < 2.2$ and measure their spherically-averaged clustering in both configuration and Fourier space. Our observational dataset and the 1400 simulated realizations of the dataset allow us to detect a preference for BAO that is greater than 2.8$\sigma$. We determine the spherically averaged BAO distance to $z = 1.52$ to 3.8 per cent precision: $D_V(z=1.52)=3843\pm147 \left(r_{\rm d}/r_{\rm d, fid}\right)\ $Mpc. This is the first time the location of the BAO feature has been measured between redshifts 1 and 2. Our result is fully consistent with the prediction obtained by extrapolating the Planck flat $\Lambda$CDM best-fit cosmology. All of our results are consistent with basic large-scale structure (LSS) theory, confirming quasars to be a reliable tracer of LSS, and provide a starting point for numerous cosmological tests to be performed with eBOSS quasar samples. We combine our result with previous, independent, BAO distance measurements to construct an updated BAO distance-ladder. Using these BAO data alone and marginalizing over the length of the standard ruler, we find $\Omega_{\Lambda} > 0$ at 6.6$\sigma$ significance when testing a $\Lambda$CDM model with free curvature., Comment: Accepted by MNRAS; BAO distance likelihood available in source files 'QSOv1.9fEZmock_BAOchi2.dat'; full set of data to be public eventually from SDSS website

Cosmological perturbation theory is a powerful tool to predict the statistics of large-scale structure in the weakly non-linear regime, but even at 1-loop order it results in computationally expensive mode-coupling integrals. Here we present a fast algorithm for computing 1-loop power spectra of quantities that depend on the observer's orientation, thereby generalizing the FAST-PT framework (McEwen et al., 2016) that was originally developed for scalars such as the matter density. This algorithm works for an arbitrary input power spectrum and substantially reduces the time required for numerical evaluation. We apply the algorithm to four examples: intrinsic alignments of galaxies in the tidal torque model; the Ostriker-Vishniac effect; the secondary CMB polarization due to baryon flows; and the 1-loop matter power spectrum in redshift space. Code implementing this algorithm and these applications is publicly available at https://github.com/JoeMcEwen/FAST-PT ., Comment: 32 pages, 5 figures, 4 tables. Minor changes. Published in JCAP. Code available at https://github.com/JoeMcEwen/FAST-PT

We search for a galaxy clustering bias due to a modulation of galaxy number with the baryon-dark matter relative velocity resulting from recombination-era physics. We find no detected signal and place the constraint $b_v < 0.01$ on the relative velocity bias for the CMASS galaxies. This bias is an important potential systematic of Baryon Acoustic Oscillation (BAO) method measurements of the cosmic distance scale using the 2-point clustering. Our limit on the relative velocity bias indicates a systematic shift of no more than $0.3\%$ rms in the distance scale inferred from the BAO feature in the BOSS 2-point clustering, well below the $1\%$ statistical error of this measurement. This constraint is the most stringent currently available and has important implications for the ability of upcoming large-scale structure surveys such as DESI to self-protect against the relative velocity as a possible systematic., Comment: 7 pages, 2 figures, submitted MNRAS

We present a novel algorithm, FAST-PT, for performing convolution or mode-coupling integrals that appear in nonlinear cosmological perturbation theory. The algorithm uses several properties of gravitational structure formation -- the locality of the dark matter equations and the scale invariance of the problem -- as well as Fast Fourier Transforms to describe the input power spectrum as a superposition of power laws. This yields extremely fast performance, enabling mode-coupling integral computations fast enough to embed in Monte Carlo Markov Chain parameter estimation. We describe the algorithm and demonstrate its application to calculating nonlinear corrections to the matter power spectrum, including one-loop standard perturbation theory and the renormalization group approach. We also describe our public code (in Python) to implement this algorithm, including the applications described here., Comment: 24 pages, 5 figures, 2 tables. fig.1 corrected. changes made. matched with the journal version. Code available at https://github.com/JoeMcEwen/FAST-PT

The combination of galaxy-galaxy lensing (GGL) and galaxy clustering is a promising route to measuring the amplitude of matter clustering and testing modified gravity theories of cosmic acceleration. Halo occupation distribution (HOD) modeling can extend the approach down to nonlinear scales, but galaxy assembly bias could introduce systematic errors by causing the HOD to vary with large scale environment at fixed halo mass. We investigate this problem using the mock galaxy catalogs created by Hearin & Watson (2013, HW13), which exhibit significant assembly bias because galaxy luminosity is tied to halo peak circular velocity and galaxy colour is tied to halo formation time. The preferential placement of galaxies (especially red galaxies) in older halos affects the cutoff of the mean occupation function $\langle N_\text{cen}(M_\text{min}) \rangle$ for central galaxies, with halos in overdense regions more likely to host galaxies. The effect of assembly bias on the satellite galaxy HOD is minimal. We introduce an extended, environment dependent HOD (EDHOD) prescription to describe these results and fit galaxy correlation measurements. Crucially, we find that the galaxy-matter cross-correlation coefficient, $r_{gm} \equiv \xi_{gm} \cdot [ \xi_{mm} \xi_{gg} ]^{-1/2}$, is insensitive to assembly bias on scales $r \gtrsim 1 \; h^{-1}\text{Mpc}$, even though $\xi_{gm} $ and $\xi_{gg} $ are both affected individually. We can therefore recover the correct $\xi_{mm} $ from the HW13 galaxy-galaxy and galaxy-matter correlations using either a standard HOD or EDHOD fitting method. For $M_r \leq -19$ or $M_r \leq -20$ samples the recovery of $\xi_{mm}$ is accurate to 2% or better. For a sample of red $M_r \leq -20$ galaxies we achieve 2% recovery at $r \gtrsim 2\;h^{-1}\text{Mpc}$ with EDHOD modeling but lower accuracy at smaller scales or with a standard HOD fit., Comment: Figure 17 conveys the key result; experts can start at the conclusions

At the epoch of decoupling, cosmic baryons had supersonic velocities relative to the dark matter that were coherent on large scales. These velocities subsequently slow the growth of small-scale structure and, via feedback processes, can influence the formation of larger galaxies. We examine the effect of streaming velocities on the galaxy correlation function, including all leading-order contributions for the first time. We find that the impact on the BAO peak is dramatically enhanced (by a factor of ~5) over the results of previous investigations, with the primary new effect due to advection: if a galaxy retains memory of the primordial streaming velocity, it does so at its Lagrangian, rather than Eulerian, position. Since correlations in the streaming velocity change rapidly at the BAO scale, this advection term can cause a significant shift in the observed BAO position. If streaming velocities impact tracer density at the 1% level, compared to the linear bias, the recovered BAO scale is shifted by approximately 0.5%. This new effect, which is required to preserve Galilean invariance, greatly increases the importance of including streaming velocities in the analysis of upcoming BAO measurements and opens a new window to the astrophysics of galaxy formation., Comment: 10 pages, 2 figures. PRL version with supplemental materials in appendix. Comments welcome