Large Scale Structure Observations

Galaxy Surveys are enjoying a renaissance thanks to the advent of multi-object spectrographs on ground-based telescopes. The last 15 years have seen the fruits of this experimental advance, including the 2-degree Field Galaxy Redshift Survey (2dFGRS; Colless et al. 2003) and the Sloan Digital Sky Survey (SDSS; York et al. 2000). Most recently, the Baryon Oscillation Spectroscopic Survey (BOSS; Dawson et al. 2013), part of the SDSS-III project (Eisenstein et al. 2011), has provided the largest volume of the low-redshift Universe ever surveyed with a galaxy density useful for high-precision cosmology. This set of lecture notes looks at some of the physical processes that underpin these measurements, the evolution of measurements themselves, and looks ahead to the next 15 years and the advent of surveys such as the enhanced Baryon Oscillation Spectroscopic Survey (eBOSS), the Dark Energy Spectroscopic Instrument (DESI) and the ESA Euclid satellite mission.Comment: Lectures given at Post-Planck Cosmology, Ecole de Physique des Houches, Les Houches, July 8-Aug 2, 2013, eds. B. Wandelt, C. Deffayet, P. Peter, to be published by Oxford University Press, and New Horizons for Observational Cosmology, International School of Physics Enrico Fermi, Varenna, July 1-6, 2013, eds. A. Melchiorri, A. Cooray, E. Komatsu, to be published by the Italian Society of Physic

Unbiased clustering estimation in the presence of missing observations

In order to be efficient, spectroscopic galaxy redshift surveys do not obtain redshifts for all galaxies in the population targeted. The missing galaxies are often clustered, commonly leading to a lower proportion of successful observations in dense regions. One example is the close-pair issue for SDSS spectroscopic galaxy surveys, which have a deficit of pairs of observed galaxies with angular separation closer than the hardware limit on placing neighbouring fibers. Spatially clustered missing observations will exist in the next generations of surveys. Various schemes have previously been suggested to mitigate these effects, but none works for all situations. We argue that the solution is to link the missing galaxies to those observed with statistically equivalent clustering properties, and that the best way to do this is to rerun the targeting algorithm, varying the angular position of the observations. Provided that every pair has a non-zero probability of being observed in one realisation of the algorithm, then a pair-upweighting scheme linking targets to successful observations, can correct these issues. We present such a scheme, and demonstrate its validity using realisations of an idealised simple survey strategy.Comment: 14 pages, 8 figures, published in MNRA

Galaxy 2-Point Covariance Matrix Estimation for Next Generation Surveys

We perform a detailed analysis of the covariance matrix of the spherically averaged galaxy power spectrum and present a new, practical method for estimating this within an arbitrary survey without the need for running mock galaxy simulations that cover the full survey volume. The method uses theoretical arguments to modify the covariance matrix measured from a set of small-volume cubic galaxy simulations, which are computationally cheap to produce compared to larger simulations and match the measured small-scale galaxy clustering more accurately than is possible using theoretical modelling. We include prescriptions to analytically account for the window function of the survey, which convolves the measured covariance matrix in a non-trivial way. We also present a new method to include the effects of supersample covariance and modes outside the small simulation volume which requires no additional simulations and still allows us to scale the covariance matrix. As validation, we compare the covariance matrix estimated using our new method to that from a brute force calculation using 500 simulations originally created for analysis of the Sloan Digital Sky Survey Main Galaxy Sample (SDSS-MGS). We find excellent agreement on all scales of interest for large scale structure analysis, including those dominated by the effects of the survey window, and on scales where theoretical models of the clustering normally break-down, but the new method produces a covariance matrix with significantly better signal-to-noise. Although only formally correct in real-space, we also discuss how our method can be extended to incorporate the effects of Redshift Space Distortions.Comment: 18 pages, 9 figures. Accepted for publication in MNRAS. Added new references to introduction and slightly updated text accordingl

An accurate linear model for redshift space distortions in the void-galaxy correlation function

Redshift space distortions within voids provide a unique method to test for environmental dependence of the growth rate of structures in low density regions, where effects of modified gravity theories might be important. We derive a linear theory model for the redshift space void-galaxy correlation that is valid at all pair separations, including deep within the void, and use this to obtain expressions for the monopole $\xi^s_0$ and quadrupole $\xi^s_2$ contributions. Our derivation highlights terms that have previously been neglected but are important within the void interior. As a result our model differs from previous works and predicts new physical effects, including a change in the sign of the quadrupole term within the void radius. We show how the model can be generalised to include a velocity dispersion. We compare our model predictions to measurements of the correlation function using mock void and galaxy catalogues modelled after the BOSS CMASS galaxy sample using the Big MultiDark $N$-body simulation, and show that the linear model with dispersion provides an excellent fit to the data at all scales, $0\leq s\leq120\;h^{-1}$Mpc. While the RSD model matches simulations, the linear bias approximation does not hold within voids, and care is needed in fitting for the growth rate. We show that fits to the redshift space correlation recover the growth rate $f(z=0.52)$ to a precision of $2.7\%$ using the simulation volume of $(2.5\;h^{-1}\mathrm{Gpc})^3$.Comment: 16 pages, 12 figures. v3: updated to match version published in MNRAS. Several minor changes to text for better explanations, with reference to subsequent results (arXiv:1805.09349). No changes to theory, results or conclusion

Using correlations between CMB lensing and large-scale structure to measure primordial non-Gaussianity

We apply a new method to measure primordial non-Gaussianity, using the cross-correlation between galaxy surveys and the CMB lensing signal to measure galaxy bias on very large scales, where local-type primordial non-Gaussianity predicts a $k^2$ divergence. We use the CMB lensing map recently published by the Planck collaboration, and measure its external correlations with a suite of six galaxy catalogues spanning a broad redshift range. We then consistently combine correlation functions to extend the recent analysis by Giannantonio et al. (2013), where the density-density and the density-CMB temperature correlations were used. Due to the intrinsic noise of the Planck lensing map, which affects the largest scales most severely, we find that the constraints on the galaxy bias are similar to the constraints from density-CMB temperature correlations. Including lensing constraints only improves the previous statistical measurement errors marginally, and we obtain $f_{\mathrm{NL}} = 12 \pm 21$ (1$\sigma$) from the combined data set. However, the lensing measurements serve as an excellent test of systematic errors: we now have three methods to measure the large-scale, scale-dependent bias from a galaxy survey: auto-correlation, and cross-correlation with both CMB temperature and lensing. As the publicly available Planck lensing maps have had their largest-scale modes at multipoles $l<10$ removed, which are the most sensitive to the scale-dependent bias, we consider mock CMB lensing data covering all multipoles. We find that, while the effect of $f_{\mathrm{NL}}$ indeed increases significantly on the largest scales, so do the contributions of both cosmic variance and the intrinsic lensing noise, so that the improvement is small.Comment: 5 pages, 3 figures. Additional references added. Submitted to MNRA

Galaxy peculiar velocities and evolution-bias

Galaxy bias can be split into two components: a formation-bias based on the locations of galaxy creation, and an evolution-bias that details their subsequent evolution. In this letter we consider evolution-bias in the peaks model. In this model, galaxy formation takes place at local maxima in the density field, and we analyse the subsequent peculiar motion of these galaxies in a linear model of structure formation. The peak restriction yields differences in the velocity distribution and correlation between the galaxy and the dark matter fields, which causes the evolution-bias component of the total bias to evolve in a scale-dependent way. This mechanism naturally gives rise to a change in shape between galaxy and matter correlation functions that depends on the mean age of the galaxy population. This model predicts that older galaxies would be more strongly biased on large scales compared to younger galaxies. Our arguments are supported by a Monte-Carlo simulation of galaxy pairs propagated using the Zel'dovich-approximation for describing linear peculiar galaxy motion.Comment: 5 pages, 4 figures, MNRAS accepte

L-PICOLA: A parallel code for fast dark matter simulation

Robust measurements based on current large-scale structure surveys require precise knowledge of statistical and systematic errors. This can be obtained from large numbers of realistic mock galaxy catalogues that mimic the observed distribution of galaxies within the survey volume. To this end we present a fast, distributed-memory, planar-parallel code, L-PICOLA, which can be used to generate and evolve a set of initial conditions into a dark matter field much faster than a full non-linear N-Body simulation. Additionally, L-PICOLA has the ability to include primordial non-Gaussianity in the simulation and simulate the past lightcone at run-time, with optional replication of the simulation volume. Through comparisons to fully non-linear N-Body simulations we find that our code can reproduce the $z=0$ power spectrum and reduced bispectrum of dark matter to within 2% and 5% respectively on all scales of interest to measurements of Baryon Acoustic Oscillations and Redshift Space Distortions, but 3 orders of magnitude faster. The accuracy, speed and scalability of this code, alongside the additional features we have implemented, make it extremely useful for both current and next generation large-scale structure surveys. L-PICOLA is publicly available at https://cullanhowlett.github.io/l-picolaComment: 22 Pages, 20 Figures. Accepted for publication in Astronomy and Computin

Improving the modelling of redshift-space distortions - II. A pairwise velocity model covering large and small scales

We develop a model for the redshift-space correlation function, valid for both dark matter particles and halos on scales $>5\,h^{-1}$Mpc. In its simplest formulation, the model requires the knowledge of the first three moments of the line-of-sight pairwise velocity distribution plus two well-defined dimensionless parameters. The model is obtained by extending the Gaussian-Gaussianity prescription for the velocity distribution, developed in a previous paper, to a more general concept allowing for local skewness, which is required to match simulations. We compare the model with the well known Gaussian streaming model and the more recent Edgeworth streaming model. Using N-body simulations as a reference, we show that our model gives a precise description of the redshift-space clustering over a wider range of scales. We do not discuss the theoretical prescription for the evaluation of the velocity moments, leaving this topic to further investigation.Comment: 18 pages, 10 figures, published in MNRA

The effect of redshift-space distortions on projected 2-pt clustering measurements

Although redshift-space distortions only affect inferred distances and not angles, they still distort the projected angular clustering of galaxy samples selected using redshift dependent quantities. From an Eulerian view-point, this effect is caused by the apparent movement of galaxies into or out of the sample. From a Lagrangian view-point, we find that projecting the redshift-space overdensity field over a finite radial distance does not remove all the anisotropic distortions. We investigate this effect, showing that it strongly boosts the amplitude of clustering for narrow samples and can also reduce the significance of baryonic features in the correlation function. We argue that the effect can be mitigated by binning in apparent galaxy pair-centre rather than galaxy position, and applying an upper limit to the radial galaxy separation. We demonstrate this approach, contrasting against standard top-hat binning in galaxy distance, using sub-samples taken from the Hubble Volume simulations. Using a simple model for the radial distribution expected for galaxies from a survey such as the Dark Energy Survey (DES), we show that this binning scheme will simplify analyses that will measure baryon acoustic oscillations within such galaxy samples. Comparing results from different binning schemes has the potential to provide measurements of the amplitude of the redshift-space distortions. Our analysis is relevant for other photometric redshift surveys, including those made by the Panoramic Survey Telescope & Rapid Response System (Pan-Starrs) and the Large Synoptic Survey Telescope (LSST).Comment: 13 pages, 15 figures, accepted by MNRAS, corrected typos, revised argument in section 3, figure added in section 3, results unchange