Peculiar Velocity Data Research Articles

Constraining modified gravity scenarios with the 6dFGS and SDSS galaxy peculiar velocity data sets

ABSTRACT The detailed nature of dark energy remains a mystery, leaving the possibility that its effects might be explained by changes to the laws of gravity on large scales. The peculiar velocities of galaxies directly trace the strength of gravity on cosmic scales and provide a means to further constrain such models. We generate constraints on different scenarios of gravitational physics by measuring peculiar velocity (PV) and galaxy clustering two-point correlations, using redshifts and distances from the 6-degree Field Galaxy Survey and the Sloan Digital Sky Survey PV samples, and fitting them against models characteristic of different cosmologies. Our best-fitting results are all found to be in statistical agreement with general relativity, in which context we measure the low-redshift growth of structure to be $f\sigma _8 = 0.329^{+0.081}_{-0.083}$, consistent with the prediction of the standard Lambda cold dark matter model. We also fit the modified gravity scenarios of Dvali–Gabadadze–Porrati and a Hu–Sawicki model of $f(R)$ gravity, finding the $2\sigma$ limit of their characteristic parameters to be $r_{\rm c}H_0/c\gt 6.987$ and $-\log _{10}(|f_{R0}|)\gt 4.703$, respectively. These constraints are comparable to other literature values, though it should be noted that they are significantly affected by the prior adopted for their characteristic parameters. When applied to much larger upcoming PV surveys such as DESI, this method will place rapidly improving constraints on modified gravity models of cosmic expansion and growth.

An effective description of Laniakea: impact on cosmology and the local determination of the Hubble constant

We propose an effective model to describe the bias induced on cosmological observables by Laniakea, the gravitational supercluster hosting the Milky Way, which was defined using peculiar velocity data from Cosmicflows-4 (CF4). The structure is well described by an ellipsoidal shape exhibiting triaxial expansion, reasonably approximated by a constant expansion rate along the principal axes. Our best fits suggest that the ellipsoid, after subtracting the background expansion, contracts along the two smaller axes and expands along the longest one, predicting an average expansion of ∼ -1.1 km/s/Mpc. The different expansion rates within the region, relative to the mean cosmological expansion, induce line-of-sight-dependent corrections in the computation of luminosity distances. We apply these corrections to two low-redshift datasets: the Pantheon+ catalog of type Ia Supernovae (SN Ia), and 63 measurements of Surface Brightness Fluctuations (SBF) of early-type massive galaxies from the MASSIVE survey. We find corrections on the distances of order ∼ 2-3%, resulting in a shift in the inferred best-fit values of the Hubble constant H 0 of order ΔH 0 SN Ia ≈ 0.5 km/s/Mpc and ΔH 0 SBF ≈ 1.1 km/s/Mpc, seemingly worsening the Hubble tension.

Constraining scale dependent growth with redshift surveys

Ongoing and future redshift surveys have the capability tomeasure the growth rate of large scale structure at thepercent level over a broad range of redshifts, tightlyconstraining cosmological parameters. Beyond generalrelativity, however, the growth rate in the linear densityperturbation regime can be not only redshift dependent butscale dependent, revealing important clues to modified gravity.We demonstrate that a fully model independent approach of binningthe gravitational strength G eff (k,z) matchesscalar-tensor results for the growth rate fσ 8(k,z) to0.02%–0.27% rms accuracy. For data of the quality ofthe Dark Energy Spectroscopic Instrument (DESI) we find thebin values can be constrained to 1.4%–28%. We alsoexplore thegeneral scalar-tensor form, constraining the amplitude andpast and future scalaron mass/shape parameters.Perhaps most interesting is the strong complementarityof low redshift peculiar velocity data with DESI-likeredshift space distortion measurements, enablingimprovements up to a factor 6–7 on 2D joint confidencecontour areas.Finally, we quantify some issues with gravityparametrizations that do not include all the key physics.

Bayesian reconstruction of dark matter distribution from peculiar velocities: accounting for inhomogeneous Malmquist bias

ABSTRACT We present a Bayesian velocity field reconstruction algorithm that performs the reconstruction of the mass density field using only peculiar velocity data. Our method consistently accounts for the inhomogeneous Malmquist (IHM) bias using analytical integration along the line of sight. By testing our method on a simulation, we show that our method gives an unbiased reconstruction of the velocity field. We show that not accounting for the IHM bias can lead to significant biases in the Bayesian reconstructions. We applied our method to a peculiar velocity data set consisting of the SFI++ and 2MTF Tully–Fisher catalogues and the A2 supernovae compilation, thus obtaining a novel velocity reconstruction in the local Universe. Our velocity reconstructions have a cosmological power spectrum consistent with the theoretical expectation. Furthermore, we obtain a full description of the uncertainties on reconstruction through samples of the posterior distribution. We validate our velocity reconstruction of the local Universe by comparing it to an independent reconstruction using the 2M++ galaxy catalogue, obtaining good agreement between the two reconstructions. Using Bayesian model comparison, we find that our velocity model performs better than the adaptive kernel smoothed velocity with the same peculiar velocity data. However, our velocity model does not perform as well as the velocity reconstruction from the 2M++ galaxy catalogue, due to the sparse and noisy nature of the peculiar velocity tracer samples. The method presented here provides a way to include peculiar velocity data in initial condition reconstruction frameworks.

Using peculiar velocity surveys to constrain neutrino masses

ABSTRACT The presence of massive neutrinos in the early Universe is expected to have influenced the observed distribution of galaxies and their observed motions. In this work, we explore whether measurements of galaxy peculiar velocities could allow us to improve upon neutrino mass constraints from galaxy redshift surveys alone. Using Fisher matrix forecasts, we show that the galaxy peculiar motions do contain information on the sum of the masses of neutrinos ∑mν, and that this information can be used to improve upon constraints that may be obtained from low-redshift galaxy surveys (z < 0.5) combined with Planck measurements of the cosmic microwave background. Compared to the full constraining power offered by Planck and higher redshift DESI data, we find that the benefit of including peculiar velocities only marginally improves neutrino mass constraints. However, when one does not include information from Planck, our results show that the inclusion of peculiar velocity measurements can substantially improve upon the constraints from redshift surveys alone, and that in some cases the addition of further data from high-density peculiar velocity surveys is more successful at overcoming the sample variance than adding further data from redshifts only. We demonstrate that it may be possible to achieve upper bounds of ∑mν ≈ 0.14 eV (68 per cent confidence limit), from upcoming spectroscopic galaxy surveys alone, as long as the peculiar velocity data is available, an improvement of ∼14 per cent over redshift surveys alone, but not as strong as when CMB data are included.

Peculiar velocities in the local Universe: comparison of different models and the implications for H0 and dark matter

ABSTRACT When measuring the value of the Hubble parameter, H0, it is necessary to know the recession velocity free of the effects of peculiar velocities. In this work, we study different models of peculiar velocity in the local Universe. In particular, we compare models based on density reconstruction from galaxy redshift surveys and kernel smoothing of peculiar velocity data. The velocity field from the density reconstruction is obtained using the 2M++ galaxy redshift compilation, which is compared to two adaptive kernel-smoothed velocity fields: the first obtained from the 6dF Fundamental Plane sample and the other using a Tully–Fisher catalogue obtained by combining SFI++ and 2MTF. We highlight that smoothed velocity fields should be rescaled to obtain unbiased velocity estimates. Comparing the predictions of these models to the observations from a few test sets of peculiar velocity data, obtained from the Second Amendment Supernovae catalogue and the Tully–Fisher catalogues, we find that 2M++ reconstruction provides a better model of the peculiar velocity in the local Universe than the kernel-smoothed peculiar velocity models. We study the impact of peculiar velocities on the measurement of H0 from gravitational waves and megamasers. In doing so, we introduce a probabilistic framework to marginalize over the peculiar velocity corrections along the line of sight. For the megamasers, we find H0 = 70.1 ± 2.9 km s−1 Mpc−1 using the 2M++ velocity field. We also study the peculiar velocity of the galaxy NGC 1052-DF2, concluding that a short ∼13 Mpc distance is not a likely explanation of the anomalously low dark matter fraction of that galaxy.

Infall of galaxies onto groups

Context. The growth of the structure within the Universe manifests in the form of accretion flows of galaxies onto groups and clusters. Thus, the present-day properties of groups and their member galaxies are influenced by the characteristics of this continuous infall pattern. Several works both theoretical (in numerical simulations) and observational, have studied this process and provided useful steps for a better understanding of galaxy systems and their evolution. Aims. We aim to explore the streaming flow of galaxies onto groups using observational peculiar velocity data. The effects of distance uncertainties are also analyzed, as well as the relation between the infall pattern and the group and environment properties. Methods. This work deals with the analysis of peculiar velocity data and their projection in the direction of group centers, in order to determine the mean galaxy infall flow. We applied this analysis to the galaxies and groups extracted from the Cosmicflows–3 catalog. We also used mock catalogs derived from numerical simulations to explore the effects of distance uncertainties on the derivation of the galaxy velocity flow onto groups. Results. We determine the infalling velocity field onto galaxy groups with cz < 0.033 using peculiar velocity data. We measured the mean infall velocity onto group samples of different mass ranges, and also explored the impact of the environment where the group resides. Far beyond the group virial radius, the surrounding large-scale galaxy overdensity may impose additional infalling streaming amplitudes in the range of 200−400 km s−1. Also, we find that groups in samples with a well-controlled galaxy density environment show an infalling velocity amplitude that increases with group mass, consistent with the predictions of the linear model. These results from observational data are in excellent agreement with those derived from the mock catalogs.

The peculiar velocity field up to z ∼ 0.05 by forward-modelling Cosmicflows-3 data

Abstract A hierarchical Bayesian model is applied to the Cosmicflows-3 catalogue of galaxy distances in order to derive the peculiar velocity field and distribution of matter within z ∼ 0.054. The model assumes the ΛCDM model within the linear regime and includes the fit of the galaxy distances together with the underlying density field. By forward modelling the data, the method is able to mitigate biases inherent to peculiar velocity analyses, such as the Homogeneous Malmquist bias or the lognormal distribution of peculiar velocities. The statistical uncertainty on the recovered velocity field is about 150 km s−1 depending on the location, and we study systematics coming from the selection function and calibration of distance indicators. The resulting velocity field and related density fields recover the cosmography of the Local Universe which is presented in an unprecedented volume of our Universe 10 times larger than previously reached. This methodology opens the doors to reconstruction of initial conditions for larger and more accurate constrained cosmological simulations. This work is also preparatory to larger peculiar velocity data sets coming from Wallaby, TAIPAN, or LSST.

Uneven flows: On cosmic bulk flows, local observers, and gravity

Using N-body simulations we study the impact of various systematic effects on the bulk flow (BF) and the Cosmic Mach Number (CMN). We consider two types of systematics: those related to survey properties and those induced by observer's location in the Universe. In the former category we model sparse sampling, velocity errors, and survey incompleteness. In the latter, we consider Local Group (LG) analogue observers, placed in a specific location within the Cosmic Web, satisfying various observational criteria. We differentiate such LG observers from Copernican ones, who are at random locations. We report strong systematic effects on the measured BF and CMN induced by sparse sampling, velocity errors and radial incompleteness. For BF most of these effects exceed 10\% for scales $R\leq100h^{-1}$Mpc. For CMN some of these systematics can be catastrophically large ($>50\%$) also on bigger scales. Moreover, we find that the position of the observer in the Cosmic Web significantly affects the locally measured BF (CMN), with effects as large as $\sim20\%$ ($30\%)$ at $R\leq50h^{-1}$Mpc for a LG-like observer as compared to a random one. This effect is comparable to the sample variance. To highlight the importance of these systematics, we additionally study a model of modified gravity (MG) with $\sim15\%$ enhanced growth rate. We found that the systematic effects can mimic the modified gravity signal. The worst-case scenario is realized for a case of a LG-like observer, when the effects induced by local structures are degenerate with the enhanced growth rate fostered by MG. Our results indicate that dedicated constrained simulations and realistic mock galaxy catalogs will be absolutely necessary to fully benefit from the statistical power of the forthcoming peculiar velocity data from surveys such as TAIPAN, WALLABY, Cosmic Flows-4 and SKA.

Large-scale bulk flows from the Cosmicflows-2 catalogue

The Cosmicflows-2 catalogue is a compendium of peculiar velocity measurements. While it has many objects in common with the COMPOSITE catalogue, a previously analysed collection of peculiar velocity data found to give an unexpectedly large bulk flow on large scales, the data in Cosmicflows-2 have been reanalysed to ensure consistency between distances measured using different methods. In particular, a focus on accurate distances led the authors of the Cosmicflows-2 to not correct for homogeneous or inhomogeneous Malmquist bias, both or which are corrected for in the COMPOSITE compilation. We find remarkable agreement between the COMPOSITE and the Cosmicflows-2 if the small EFAR sample of clusters located in two dense superclusters is removed from both surveys, giving results that are inconsistent with the $\Lambda$ cold dark matter standard model with Planck central parameters at the 98\% level. On smaller scales we find overall agreement between data sets and consistency with the standard model.

Dynamics of pairwise motions in the Cosmic Web

AbstractWe present results of analysis of the dark matter (DM) pairwise velocity statistics in different Cosmic Web environments. We use the DM velocity and density field from the Millennium 2 simulation together with the NEXUS+ algorithm to segment the simulation volume into voxels uniquely identifying one of the four possible environments: nodes, filaments, walls or cosmic voids. We show that the PDFs of the mean infall velocities v12 as well as its spatial dependence together with the perpendicular and parallel velocity dispersions bear a significant signal of the large-scale structure environment in which DM particle pairs are embedded. The pairwise flows are notably colder and have smaller mean magnitude in wall and voids, when compared to much denser environments of filaments and nodes. We discuss on our results, indicating that they are consistent with a simple theoretical predictions for pairwise motions as induced by gravitational instability mechanism. Our results indicate that the Cosmic Web elements are coherent dynamical entities rather than just temporal geometrical associations. In addition it should be possible to observationally test various Cosmic Web finding algorithms by segmenting available peculiar velocity data and studying resulting pairwise velocity statistics.

Reconstructing cosmological initial conditions from galaxy peculiar velocities – III. Constrained simulations

In previous works we proposed the Reverse Zeldovich Approximation (RZA) method, which can be used to estimate the cosmological initial conditions underlying the galaxy distribution in the Local Universe using peculiar velocity data. In this paper, we apply the technique to run constrained cosmological simulations from the RZA-reconstructed initial conditions, designed to reproduce the large-scale structure of the Local Universe. We test the method with mock peculiar velocity catalogues extracted from a reference simulation. We first reconstruct the initial conditions of this reference simulation using the mock data, and then run the reconstructed initial conditions forward in time until z=0. We compare the resulting constrained simulations with the original simulation at z=0 to test the accuracy of this method. We also compare them with constrained simulations run from the mock data without the addition of RZA, i.e. using only the currently established constrained realizations (CR) method. Our re-simulations are able to correctly recover the evolution of the large-scale structure underlying the data. The results show that the addition of RZA to the CR method significantly improves both the reconstruction of the initial conditions and the accuracy of the obtained constrained resimulations. Haloes from the original simulation are recovered in the re-simulations with an average accuracy of about 2 Mpc/h on their position and a factor of 2 in mass, down to haloes with a mass of approx 10^14 M_odot/h. In comparison, without RZA the re-simulations recover only the most massive haloes with masses of about 5x10^14 M_odot/h and higher, and with a systematic shift on their position of about approx 10 Mpc/h due to the cosmic displacement field. We show that with the additional Lagrangian reconstruction step introduced by the RZA, this shift can be removed.

Reconstructing cosmological initial conditions from galaxy peculiar velocities – II. The effect of observational errors

The Reverse Zeldovich Approximation (RZA) is a reconstruction method which allows to estimate the cosmic displacement field from galaxy peculiar velocity data and to constrain initial conditions for cosmological simulations of the Local Universe. In this paper, we investigate the effect of different observational errors on the reconstruction quality of this method. For this, we build a set of mock catalogues from a cosmological simulation, varying different error sources like the galaxy distance measurement error (0 - 20%), the sparseness of the data points, and the maximum catalogue radius (3000 - 6000 km/s). We perform the RZA reconstruction of the initial conditions on these mock catalogues and compare with the actual initial conditions of the simulation. We also investigate the impact of the fact that only the radial part of the peculiar velocity is observationally accessible. We find that the sparseness of a dataset has the highest detrimental effect on RZA reconstruction quality. Observational distance errors also have a significant influence, but it is possible to compensate this relatively well with Wiener Filter reconstruction. We also investigate the effect of different object selection criteria and find that distance catalogues distributed randomly and homogeneously across the sky (such as spiral galaxies selected for the Tully-Fisher method) allow for a higher reconstruction quality than if when data is preferentially drawn from massive objects or dense environments (such as elliptical galaxies). We find that the error of estimating the initial conditions with RZA is always dominated by the inherent non-linearity of data observed at z=0 rather than by the combined effect of the observational errors. Even an extremely sparse dataset with high observational errors still leads to a good reconstruction of the initial conditions on a scale of about 5 Mpc/h.

Reconstructing cosmological initial conditions from galaxy peculiar velocities – I. Reverse Zeldovich Approximation

We propose a new method to recover the cosmological initial conditions of the presently observed galaxy distribution, which can serve to run constrained simulations of the Local Universe. Our method, the Reverse Zeldovich Approximation (RZA), can be applied to radial galaxy peculiar velocity data and extends the previously used Constrained Realizations (CR) method by adding a Lagrangian reconstruction step. The RZA method consists of applying the Zeldovich approximation in reverse to galaxy peculiar velocities to estimate the cosmic displacement field and the initial linear matter distribution from which the present-day Local Universe evolved.We test our method with a mock survey taken from a cosmological simulation. We show that the halo peculiar velocities at z = 0 are close to the linear prediction of the Zeldovich approximation, if a grouping is applied to the data to remove virial motions. We find that the addition of RZA to the CR method significantly improves the reconstruction of the initial conditions. The RZA is able to recover the correct initial positions of the velocity tracers with a median error of only 1.36 Mpc/h in our test simulation. For realistic sparse and noisy data, this median increases to 5 Mpc/h. This is a significant improvement over the previous approach of neglecting the displacement field, which introduces errors on a scale of 10 Mpc/h or even higher. Applying the RZA method to the upcoming high-quality observational peculiar velocity catalogues will generate much more precise constrained simulations of the Local Universe.

The non-linear matter and velocity power spectra in f(R) gravity

We study the matter and velocity divergence power spectra in a f(R) gravity theory and their time evolution measured from several large-volume N-body simulations with varying box sizes and resolution. We find that accurate prediction of the matter power spectrum in f(R) gravity places stronger requirements on the simulation than is the case with LCDM, because of the nonlinear nature of the fifth force. Linear perturbation theory is shown to be a poor approximation for the f(R) models, except when the chameleon effect is very weak. We show that the relative differences from the fiducial LCDM model are much more pronounced in the nonlinear tail of the velocity divergence power spectrum than in the matter power spectrum, which suggests that future surveys which target the collection of peculiar velocity data will open new opportunities to constrain modified gravity theories. A close investigation of the time evolution of the power spectra shows that there is a pattern in the evolution history, which can be explained by the properties of the chameleon-type fifth force in f(R) gravity. Varying the model parameter |f_R0|, which quantifies the strength of the departure from standard gravity, mainly varies the epoch marking the onset of the fifth force, as a result of which the different f(R) models are in different stages of the same evolutionary path at any given time

Power spectrum estimation from peculiar velocity catalogues

The peculiar velocities of galaxies are an inherently valuable cosmological probe, providing an unbiased estimate of the distribution of matter on scales much larger than the depth of the survey. Much research interest has been motivated by the high dipole moment of our local peculiar velocity field, which suggests a large-scale excess in the matter power spectrum and can appear to be in some tension with the Λ cold dark matter (ΛCDM) model. We use a composite catalogue of 4537 peculiar velocity measurements with a characteristic depth of 33 h−1 Mpc to estimate the matter power spectrum. We compare the constraints with this method, directly studying the full peculiar velocity catalogue, to results by Macaulay et al., studying minimum variance moments of the velocity field, as calculated by Feldman, Watkins & Hudson. We find good agreement with the ΛCDM model on scales of k > 0.01 h Mpc−1. We find an excess of power on scales of k < 0.01 h Mpc−1 with a 1σ uncertainty which includes the ΛCDM model. We find that the uncertainty in excess at these scales is larger than an alternative result studying only moments of the velocity field, which is due to the minimum variance weights used to calculate the moments. At small scales, we are able to clearly discriminate between linear and non-linear clustering in simulated peculiar velocity catalogues and find some evidence (although less clear) for linear clustering in the real peculiar velocity data.

Testing the minimum variance method for estimating large-scale velocity moments

The estimation and analysis of large-scale bulk flow moments of peculiar velocity surveys is complicated by non-spherical survey geometry, the non-uniform sampling of the matter velocity field by the survey objects and the typically large measurement errors of the measured line-of-sight velocities. Previously, we have developed an optimal `minimum variance' (MV) weighting scheme for using peculiar velocity data to estimate bulk flow moments for idealized, dense and isotropic surveys with Gaussian radial distributions, that avoids many of these complications. These moments are designed to be easy to interpret and are comparable between surveys. In this paper, we test the robustness of our MV estimators using numerical simulations. Using MV weights, we estimate the bulk flow moments for various mock catalogues extracted from the LasDamas and the Horizon Run numerical simulations and compare these estimates to the moments calculated directly from the simulation boxes. We show that the MV estimators are unbiased and negligibly affected by non-linear flows.

THE GROWTH RATE OF COSMIC STRUCTURE FROM PECULIAR VELOCITIES AT LOW AND HIGH REDSHIFTS

Peculiar velocities are an important probe of the growth rate of mass density fluctuations in the Universe. Most previous studies have focussed exclusively on measuring peculiar velocities at intermediate ($0.2 < z < 1$) redshifts using statistical redshift-space distortions. Here we emphasize the power of peculiar velocities obtained directly from distance measurements at low redshift ($z \lesssim 0.05$), and show that these data break the usual degeneracies in the \Omega_{m,0} -- $\sigma_{8,0}$ parameter space. Using only peculiar velocity data, we find $\Omega_{m,0} = 0.259\pm0.045$ and $\sigma_{8,0} = 0.748\pm0.035$. Fixing the amplitude of fluctuations at very high redshift using observations of the Cosmic Microwave Background (CMB), the same data can be used to constrain the growth index $\gamma$, with the strongest constraints coming from peculiar velocity measurements in the nearby Universe. We find $\gamma = 0.619\pm 0.054$, consistent with LCDM. Current peculiar velocity data already strongly constrain modified gravity models, and will be a powerful test as data accumulate.

The three faces of Ωm: testing gravity with low- and high-redshift SNe Ia surveys

Abstract Peculiar velocities of galaxies hosting Type Ia supernovae (SNe Ia) generate a significant systematic effect in deriving the dark energy equation of state w, at level of a few per cent. Here, we illustrate how the peculiar velocity effect in SNe Ia data can be turned from a ‘systematic’ into a probe of cosmological parameters. We assume a flat Λcold dark matter model (w = −1) and use low- and high-redshift SNe Ia data to derive simultaneously three distinct estimates of the matter density Ωm which appear in the problem: from the geometry, from the dynamics and from the shape of the matter power spectrum. We find that each of the three Ωm's agrees with the canonical value Ωm = 0.25 to within 1σ, for reasonably assumed fluctuation amplitude and Hubble parameter. This is consistent with the standard cosmological scenario for both the geometry and the growth of structure. For fixed Ωm = 0.25 for all three Ωm's, we constrain γ= 0.72 ± 0.21 in the growth factor of Ωm(z)γ, so we cannot currently distinguish between standard Einstein gravity and predictions from some modified gravity models. Future surveys of thousands of SNe Ia, or inclusion of peculiar velocity data, could significantly improve the above tests.

Peculiar velocities into the next generation: cosmological parameters from large surveys without bias from non-linear structure

We investigate methods to best estimate the normalization of the mass density fluctuation power spectrum (σ8) using peculiar velocity data from a survey like the six-degree Field Galaxy Velocity Survey (6dFGSv). We focus on two potential problems: (i) biases from non-linear growth of structure and (ii) the large number of velocities in the survey. Simulations of ΛCDM-like models are used to test the methods. We calculate the likelihood from a full covariance matrix of velocities averaged in grid cells. This simultaneously reduces the number of data points and smoothes out non-linearities which tend to dominate on small scales. We show how the averaging can be taken into account in the predictions in a practical way, and show the effect of the choice of cell size. We find that a cell size can be chosen that significantly reduces the non-linearities without significantly increasing the error bars on cosmological parameters. We compare our results with those from a principal components analysis following Watkins et al. and Feldman et al. to select a set of optimal moments constructed from linear combinations of the peculiar velocities that are least sensitive to the non-linear scales. We conclude that averaging in grid cells performs equally well. We find that for a survey such as 6dFGSv we can estimate σ8 with less than 3 per cent bias from non-linearities. The expected error on σ8 after marginalizing over Ωm is approximately 16 per cent.