Projected two- and three-point statistics: forecasts and mitigation of non-linear RSDs

Oliver Leicht,James Fergusson,Tobias Baldauf,Paul Shellard

doi:10.1093/mnras/stab616

Oliver Leicht, James Fergusson + Show 2 more

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https://doi.org/10.1093/mnras/stab616

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Abstract

ABSTRACT The combination of two- and three-point clustering statistics of galaxies and the underlying matter distribution has the potential to break degeneracies between cosmological parameters and nuisance parameters and can lead to significantly tighter constraints on parameters describing the composition of the Universe and the dynamics of inflation. Here, we investigate the relation between biases in the estimated parameters and inaccurate modelling of non-linear redshift-space distortions for the power spectrum and bispectrum of projected galaxy density fields and lensing convergence. Non-linear redshift-space distortions are one of the leading systematic uncertainties in galaxy clustering. Projections along the line of sight suppress radial modes and are thus allowing a trade-off between biases due to non-linear redshift-space distortions and statistical uncertainties. We investigate this bias-error trade-off for a CMASS-like survey with a varying number of redshift bins. Improved modelling of the non-linear redshift-space distortions allows the recovery of more radial information when controlling for biases. Not modelling non-linear redshift-space distortions inflates error bars for almost all parameters by $20{{\ \rm per\ cent}}$. The information loss for the amplitude of local non-Gaussianities is smaller, since it is best constrained from large scales. In addition, we show empirically that one can recover more than 99 per cent of the 3D power spectrum information if the depth of the tomographic bins is reduced to 10 h−1 Mpc.

Highlights

Our understanding of the Universe has been shaped by observations of the cosmic microwave background (CMB) and large-scale structure of the Universe (LSS) over the last 30 yr (Riess et al 2016; Alam et al 2017; Planck Collaboration VI 2018)
Following Scoccimarro et al (2001), Schmidt (2016), and Desjacques et al (2018), we model the shot-noise as Poissonian, which leads to the following non-zero spectra
Throughout this section, we use the finding that the crosscovariances between power spectra and bispectra are negligible at large scales (Song, Taruya & Oka 2015; Chan & Blot 2017; Yankelevich & Porciani 2019)

Summary

Introduction

Our understanding of the Universe has been shaped by observations of the cosmic microwave background (CMB) and large-scale structure of the Universe (LSS) over the last 30 yr (Riess et al 2016; Alam et al 2017; Planck Collaboration VI 2018). 2014), Euclid (Amendola et al 2018), and DESI (DESI Collaboration 2016) will contribute complementary information about the late-time evolution of the Universe. Those surveys will achieve exquisitely small statistical errors due to the vast volumes they cover and high number density of tracers they resolve. Given their 3D origin, upcoming LSS data sets are predicted to eventually contain more information about cosmological parameters than the CMB. The early Universe’s density distribution was very close to a Gaussian random field (Planck Collaboration IX 2019) that is fully described by the two-point correlation function or its Fourier transform, the power spectrum.

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