Redshift Space Research Articles

Precision analysis of the redshift-space galaxy bispectrum

We study the information content of the angle-averaged (monopole) redshift space galaxy bispectrum. The main novelty of our approach is the use of a systematic tree-level perturbation theory model that includes galaxy bias, IR resummation, and also accounts for nonlinear redshift space distortions, binning, and projection effects. We analyze data from the PT challenge simulations, whose cumulative volume of 566 $h^{-3}$Gpc$^3$ allows for a precise comparison to theoretical predictions. Fitting the power spectrum and bispectrum of our simulated data, and varying all necessary cosmological and nuisance parameters in a consistent Markov chain Monte Carlo analysis, we find that our tree-level bispectrum model is valid up to $k_{\max}=0.08~h{\rm Mpc}^{-1}$ (at $z=0.61$). We also find that inclusion of the bispectrum monopole improves constraints on cosmological parameters by $(5-15)\%$ relative to the power spectrum. The improvement is more significant for the quadratic bias parameters of our simulated galaxies, which we also show to deviate from biases of the host dark matter halos at the $\sim 3\sigma$ level. Finally, we adjust the covariance and scale cuts to match the volume of the BOSS survey, and estimate that within the minimal $\Lambda$CDM model the bispectrum data can tighten the constraint on the mass fluctuation amplitude $\sigma_8$ by roughly $10\%$.

Mapping the Three-dimensional Lyα Forest Large-scale Structure in Real and Redshift Space*

Abstract This work presents a new physically motivated supervised machine-learning method, hydro-bam, to reproduce the three-dimensional Lyα forest field in real and redshift space, which learns from a reference hydrodynamic simulation and thereby saves about seven orders of magnitude in computing time. We show that our method is accurate up to k ∼ 1 h Mpc−1 in the one- (probability distribution function), two- (power spectra), and three-point (bispectra) statistics of the reconstructed fields. When compared to the reference simulation including redshift-space distortions, our method achieves deviations of ≲2% up to k = 0.6 h Mpc−1 in the monopole and ≲5% up to k = 0.9 h Mpc−1 in the quadrupole. The bispectrum is well reproduced for triangle configurations with sides up to k = 0.8 h Mpc−1. In contrast, the commonly adopted Fluctuating Gunn–Peterson approximation shows significant deviations, already when peculiar motions are not included (real space) at configurations with sides of k = 0.2–0.4 h Mpc−1 in the bispectrum and is also significantly less accurate in the power spectrum (within 5% up to k = 0.7 h Mpc−1). We conclude that an accurate analysis of the Lyα forest requires considering the complex baryonic thermodynamical large-scale structure relations. Our hierarchical domain-specific machine-learning method can efficiently exploit this and is ready to generate accurate Lyα forest mock catalogs covering the large volumes required by surveys such as DESI and WEAVE.

Constructing the Emission-line Galaxy–Host Halo Connection through Auto and Cross Correlations

Abstract We investigate the [O ii] emission-line galaxy (ELG)-host halo connection via auto and cross correlations, and propose a concise and effective method to populate ELGs in dark matter halos without assuming a parameterized halo occupation distribution (HOD) model. Using the observational data from VIMOS Public Extragalactic Redshift Survey, we measure the auto and cross correlation functions between ELGs selected by [O ii] luminosity and normal galaxies selected by stellar mass. Combining the stellar–halo mass relation derived for the normal galaxies and the fraction of ELGs observed in the normal galaxy population, we demonstrate that we can establish an accurate ELG–halo connection. With the ELG–halo connection, we can accurately reproduce the auto and cross correlation functions of ELGs and normal galaxies both in real space and in redshift space, once the satellite fraction is properly reduced. Our method provides a novel strategy to generate ELG mock catalogs for ongoing and upcoming galaxy redshift surveys. We also provide a simple description for the HOD of ELGs.

Cosmology behind the mask: Constraining the parameters of ΛCDM with the unmasked galaxy density field from VIPERS

Abstract Galaxy redshift surveys are designed to map cosmic structures in three dimensions for large-scale structure studies. Nevertheless, limitations due to sampling and the survey window are unavoidable and degrade the cosmological constraints. We present an analysis of the VIMOS Public Extragalactic Redshift Survey (VIPERS) over the redshift range 0.6 < z < 1 that is optimised to extract the cosmological parameters while fully accounting for the complex survey geometry. We employ the Gibbs sampling algorithm to iteratively draw samples of the galaxy density field in redshift space, the galaxy bias, the matter density, baryon fraction and growth-rate parameter fσ8 based on a multivariate Gaussian likelihood and prior on the density field. Despite the high number of degrees of freedom, the samples converge to the joint posterior distribution and give self-consistent constraints on the model parameters. We validate the approach using VIPERS mock galaxy catalogues. Although the uncertainty is underestimated by the Gaussian likelihood on the scales that we consider by 50%, the dispersion of the results from the mock catalogues gives a robust error estimate. We find that the precision of the results matches those of the traditional analyses applied to the VIPERS data that use more constrained models. By relaxing the model assumptions, we confirm that the data deliver consistent constraints on the ΛCDM model. This work provides a case-study for the application of maximum-likelihood analyses for the next generation of galaxy redshift surveys.

Standardizing Platinum Dainotti-correlated gamma-ray bursts, and using them with standardized Amati-correlated gamma-ray bursts to constrain cosmological model parameters.

We show that the Platinum gamma-ray burst (GRB) data compilation, probing the redshift range 0.553 ≤ z ≤ 5.0, obeys a cosmological-model-independent three-parameter Fundamental Plane (Dainotti) correlation and so is standardizable. While they probe the largely unexplored z ∼ 2.3-5 part of cosmological redshift space, the GRB cosmological parameter constraints are consistent with, but less precise than, those from a combination of baryon acoustic oscillation (BAO) and Hubble parameter [H(z)] data. In order to increase the precision of GRB-only cosmological constraints, we exclude common GRBs from the larger Amati-correlated A118 data set composed of 118 GRBs and jointly analyse the remaining 101 Amati-correlated GRBs with the 50 Platinum GRBs. This joint 151 GRB data set probes the largely unexplored z ∼ 2.3-8.2 region; the resulting GRB-only cosmological constraints are more restrictive, and consistent with, but less precise than, those from H(z) +BAO data.

Cosmological constraints without nonlinear redshift-space distortions

Non-linear redshift-space distortions ("fingers of God") are challenging to model analytically, a fact that limits the applicability of perturbation theory in redshift space as compared to real space. We show how this problem can be mitigated using a new observable, $Q_0$, which can be easily estimated from the redshift space clustering data and is approximately equal to the real space power spectrum. The new statistic does not suffer from fingers of God and can be accurately described with perturbation theory down to $k_{\rm max}\simeq 0.4~h~\text{Mpc}^{-1}$. It can be straightforwardly included in the likelihood at negligible additional computational cost, and yields noticeable improvements on cosmological parameters compared to standard power spectrum multipole analyses. Using both simulations and observational data from the Baryon Oscillation Spectroscopic Survey, we show that improvements vary from $10\%$ to $100\%$ depending on the cosmological parameter considered, the galaxy sample and the survey volume.

Modeling the Spectral Diversity of Quasars in the Sixteenth Data Release from the Sloan Digital Sky Survey

Abstract We present a new approach to capturing the broad diversity of emission-line and continuum properties in quasar spectra. We identify populations of spectrally similar quasars through pixel-level clustering on 12,968 high signal-to-noise ratio (S/N) spectra from the Sloan Digital Sky Survey (SDSS) in the redshift range of 1.57 < z < 2.4. Our clustering analysis finds 396 quasar spectra that are not assigned to any population, 15 misclassified spectra, and 6 quasars with incorrect redshifts. We compress the quasar populations into a library of 684 high-S/N composite spectra, anchored in redshift space by the Mg ii emission line. Principal component analysis on the library results in an eigenspectrum basis spanning 1067–4007 Å. We model independent samples of SDSS quasar spectra with the eigenbasis, allowing for a free redshift parameter. Our models achieve a median reduced χ 2 on non–broad absorption line quasar spectra that is reduced by 8.5% relative to models using the eigenspectra from the SDSS spectroscopic pipeline. A significant contribution to the relative improvement is from the ability to reconstruct the range of emission-line variation. The redshift estimates from our model are consistent with the Mg ii emission-line redshift with an average offset that displays 51.4% less redshift-dependent variation relative to the SDSS eigenspectra. Our method for developing quasar spectra models can improve automated classification and predict the intrinsic spectrum in regions affected by intervening absorbers such as Lyα, C iv, and Mg ii, thus benefiting studies of large-scale structure.

Compact groups from semi-analytical models of galaxy formation – III. Purity and completeness of Hickson-like catalogues

ABSTRACT Many catalogues of isolated compact groups of galaxies (CGs) have been extracted using Hickson’s criteria to identify isolated, dense systems of galaxies, with at least three or four galaxies concordant in magnitude and redshift. But is not clear to what extent the catalogues of CGs are complete and reliable, relative to 3D truly isolated, dense groups. Using five different semi-analytical models of galaxy formation (SAMs), we identify isolated dense groups in 3D real space, containing at least three galaxies. We then build mock redshift space galaxy catalogues and run a Hickson-like CG finder. We find that the Hickson-like algorithm in redshift space is poor at recovering 3D CGs of at least three galaxies, with a purity of $\sim 10{{\ \rm per \, cent}}$ and a completeness of $\sim 22{{\ \rm per \, cent}}$. Among the $\sim 90{{\ \rm per \, cent}}$ of spurious systems, typically $60{{\ \rm per\ cent}}$ are dense structures that failed the 3D isolation criteria, while the remaining $40{{\ \rm per \, cent}}$ are chance alignments of galaxies along the line of sight, nearly all of which are within regular groups, with some variation with the SAM used for the analysis. In other words, while only 10 per cent of CGs are isolated dense groups, as intended, half are dense structures embedded within larger groups, and one-third are chance alignments within larger groups. The low completeness of the extracted CG sample is mainly due to the flux limits of the selection criteria. Our results suggest that a new observational algorithm to identify compact groups in redshift space is required to obtain dense isolated galaxy systems.

Imprints of interacting dark energy on cosmological perturbations

We investigate the characteristic modifications in the evolving cosmological perturbations when dark energy interacts with dust-like matter, causing the latter’s background energy density fall off with time faster than usual. Focusing in particular to the late-time cosmic evolution, we show that such an interaction (of a specific form, arising naturally in a scalar-tensor formulation, or a wide range of modified gravity equivalents thereof), can have a rather significant effect on the perturbative spectrum, than on the background configuration which is not expected to get distorted much from [Formula: see text]CDM. Specifically, the matter density contrast, which is by and large scale-invariant in the deep sub-horizon limit, not only gets dragged as the interaction affects the background Hubble expansion rate, but also receives a contribution from the perturbation in the (scalar field induced) dark energy, which oscillates about a nonzero mean value. As such, the standard parametrization ansatz for the matter density growth factor becomes inadequate. So we modify it suitably, and also find a numerical fit of the growth index in terms of the background parameters, in order to alleviate the problems that arise otherwise. Such a fit enables direct estimations of the background parameters, as well as the growth parameter and the reduced Hubble parameter, which we duly carry out using a redshift space distortion (RSD) subsample and its combination with the observational Hubble data. On the whole, the parametric estimates show consistency with the general observational constraints on the background level cosmology, as well as the constraints on scalar-tensor gravity from astrophysical observations, apart from having significance in the domain of cosmological perturbations.

The observed galaxy power spectrum in General Relativity

Measurements of the clustering of galaxies in Fourier space, and at low wavenumbers, offer a window into the early Universe via the possible presence of scale dependent bias generated by Primordial Non Gaussianites.On such large scales a Newtonian treatment of density perturbations might not be sufficient to describe the measurements, and a fully relativistic calculation should be employed. The interpretation of the data is thus further complicated by the fact that relativistic effects break statistical homogeneity and isotropy and are potentially divergent in the Infra-Red (IR).In this work we compute for the first time the ensemble average of the most used Fourier space estimator in spectroscopic surveys, including all general relativistic (GR) effects, and allowing for an arbitrary choice of angular and radial selection functions. We show that any observable is free of IR sensitivity once all the GR terms, individually divergent, are taken into account, and that this cancellation is a consequence of the presence of the Weinberg adiabatic mode as a solution to Einstein's equations. We then study the importance of GR effects, including lensing magnification, in the interpretation of the galaxy power spectrum multipoles, finding that they are in general a small, less than ten percent level, correction to the leading redshift space distortions term. This work represents the baseline for future investigations of the interplay between Primordial Non Gaussianities and GR effects on large scales and in Fourier space.

A fast estimator for quantifying the shape dependence of the 3D bispectrum

The dependence of the bispectrum on the size and shape of the triangle contains a wealth of cosmological information. Here we consider a triangle parameterization which allows us to separate the size and shape dependence. We have implemented an FFT based fast estimator for the three dimensional (3D) bin averaged bispectrum, and we demonstrate that it allows us to study the variation of the bispectrum across triangles of all possible shapes (and also sizes). The computational requirement is shown to scale as ∼ N g 3 log N g 3 where N g is the number of grid points along each side of the volume. We have validated the estimator using a non-Gaussian field for which the bispectrum can be analytically calculated. The estimated bispectrum values are found to be in good agreement (< 10 % deviation) with the analytical predictions across much of the triangle-shape parameter space. We also introduce linear redshift space distortion, a situation where also the bispectrum can be analytically calculated. Here the estimated bispectrum is found to be in close agreement with the analytical prediction for the monopole of the redshift space bispectrum.

Discovery and analysis of low-surface-brightness galaxies in the environment of NGC 1052

The environment of NGC 1052 has recently attracted much attention because of the presence of low-surface-brightness galaxies (LSBGs) with apparently “exotic” properties, making it a region of high interest for the detection of new objects. We used public deep photometric data from the Dark Energy Camera Legacy Survey to carry out a comprehensive search for LSBGs over a wide region of 6 × 6 degrees, equivalent to 2 × 2 Mpc at the distance of NGC 1052. We detected 42 LSBGs withreff&gt; 5 arcsec andμg(0) &gt; 24 mag arcsec−2, of which 20 are previously undetected objects. Among all the newly detected objects, RCP 32 stands out with extreme properties:reff= 23.0 arcsec and ⟨μg⟩eff= 28.6 mag arcsec−2. This makes RCP 32 one of the lowest surface brightness galaxies ever detected through integrated photometry, located at just 10 arcmin from the extensively studied NGC 1052-DF2. We explored the presence of globular clusters (GCs) in the LSBGs. We marginally detected a GC system in RCP 32, and argue that this LSBG is of great interest for follow-up observations given its extremely low baryon density. After analyzing the distribution of galaxies with available spectroscopy, we identified a large-scale structure of approximately 1 Mpc that is well isolated in redshift space and centered on NGC 1052. The spatial correlation analysis between the LSBGs and this large-scale structure suggests their association. However, when exploring the distribution of effective radius, we find an overpopulation of large LSBGs (reff&gt; 15 arcsec) located close to the line of sight of NGC 1052. We argue that this is suggestive of a substructure with similar radial velocity in sight projection, but at a closer distance, to which some of these apparently larger LSBGs could be associated. However. possible effects derived from tidal interactions are worthy of further study. Our work expands the catalog of LSBGs with new interesting objects and provides a detailed environmental context for the study of LSBGs in this region.

Estimation of Photometric Redshifts. I. Machine-learning Inference for Pan-STARRS1 Galaxies Using Neural Networks

Abstract We present a new machine-learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle the difficulty for inferring photometric redshifts. Moreover, to reduce bias induced by the new model's ability to deal with estimation difficulty, it exploits the power of ensemble learning. We extensively examine the mapping between input features and target redshift spaces to which the model is validly applicable to discover the strength and weaknesses of the trained model. Because our trained model is well calibrated, our model produces reliable confidence information about objects with non-catastrophic estimation. While our model is highly accurate for most test examples residing in the input space, where training samples are densely populated, its accuracy quickly diminishes for sparse samples and unobserved objects (i.e., unseen samples) in training. We report that out-of-distribution (OOD) samples for our model contain both physically OOD objects (i.e., stars and quasars) and galaxies with observed properties not represented by training data. The code for our model is available at https://github.com/GooLee0123/MBRNN for other uses of the model and retraining the model with different data.

ShapeFit: extracting the power spectrum shape information in galaxy surveys beyond BAO and RSD

In the standard (classic) approach, galaxy clustering measurements from spectroscopic surveys are compressed into baryon acoustic oscillations and redshift space distortions measurements, which in turn can be compared to cosmological models. Recent works have shown that avoiding this intermediate step and fitting directly the full power spectrum signal (full modelling) leads to much tighter constraints on cosmological parameters. Here we show where this extra information is coming from and extend the classic approach with one additional effective parameter, such that it captures, effectively, the same amount of information as the full modelling approach, but in a model-independent way. We validate this new method (ShapeFit) on mock catalogs, and compare its performance to the full modelling approach finding both to deliver equivalent results. The ShapeFit extension of the classic approach promotes the standard analyses at the level of full modelling ones in terms of information content, with the advantages of i) being more model independent; ii) offering an understanding of the origin of the extra cosmological information; iii) allowing a robust control on the impact of observational systematics.

The Four Cosmic Tidal Web Elements from the β-skeleton

Abstract Precise cosmic web classification of observed galaxies in massive spectroscopic surveys can be either highly uncertain or computationally expensive. As an alternative, we explore a fast Machine Learning-based approach to infer the underlying dark matter tidal cosmic web environment of a galaxy distribution from its β-skeleton graph. We develop and test our methodology using the cosmological magnetohydrodynamic simulation Illustris-TNG at z = 0. We explore three different tree-based machine-learning algorithms to find that a random forest classifier can best use graph-based features to classify a galaxy as belonging to a peak, filament, or sheet as defined by the T-Web classification algorithm. The best match between the galaxies and the dark matter T-Web corresponds to a density field smoothed over scales of 2 Mpc, a threshold over the eigenvalues of the dimensionless tidal tensor of λ th = 0.0, and galaxy number densities around 8 × 10−3 Mpc−3. This methodology results on a weighted F1 score of 0.728 and a global accuracy of 74%. More extensive tests that take into account light-cone effects and redshift space distortions are left for future work. We make one of our highest ranking random forest models available on a public repository for future reference and reuse.

Minimal theory of massive gravity in the light of CMB data and the S8 tension

We investigate the minimal theory of massive gravity (MTMG) in the light of different observational datasets that are in tension within the $\mathrm{\ensuremath{\Lambda}}$ cold dark matter cosmology. In particular, we analyze the MTMG model, for the first time, with the Planck--cosmic microwave background (CMB) data, and how these precise measurements affect the free parameters of the theory. The MTMG model can affect the CMB power spectrum at large angular scales and cause a suppression on the amplitude of the matter power spectrum. We find that on adding Planck-CMB data, the graviton has a small, positive, but nonzero mass at 68% confidence level, and from this perspective, we show that the tension between redshift space distortions measurements and Planck-CMB data in the parametric space ${S}_{8}\ensuremath{-}{\mathrm{\ensuremath{\Omega}}}_{m}$ can be resolved within the MTMG scenario. Through a robust and accurate analysis, we find that the ${H}_{0}$ tension between the CMB and the local distance ladder measurements still remains but can be reduced to $\ensuremath{\sim}3.5\ensuremath{\sigma}$ within the MTMG theory. The MTMG is very well consistent with the CMB observations, and undoubtedly, it can serve as a viable candidate among other modified gravity theories.

Towards testing the theory of gravity with DESI: summary statistics, model predictions and future simulation requirements

Shortly after its discovery, General Relativity (GR) was applied to predict the behavior of our Universe on the largest scales, and later became the foundation of modern cosmology. Its validity has been verified on a range of scales and environments from the Solar system to merging black holes. However, experimental confirmations of GR on cosmological scales have so far lacked the accuracy one would hope for — its applications on those scales being largely based on extrapolation and its validity there sometimes questioned in the shadow of the discovery of the unexpected cosmic acceleration. Future astronomical instruments surveying the distribution and evolution of galaxies over substantial portions of the observable Universe, such as the Dark Energy Spectroscopic Instrument (DESI), will be able to measure the fingerprints of gravity and their statistical power will allow strong constraints on alternatives to GR.In this paper, based on a set of N-body simulations and mock galaxy catalogs, we study the predictions of a number of traditional and novelsummary statistics beyond linear redshift distortions in two well-studied modified gravity models — chameleon f(R) gravity and a braneworld model — and the potential of testing these deviations from GR using DESI. Thesesummary statistics employ a wide array of statistical properties of the galaxy and the underlying dark matter field, including two-point and higher-order statistics, environmental dependence, redshift space distortions and weak lensing. We find that they hold promising power for testing GR to unprecedented precision. The major future challenge is to make realistic, simulation-based mock galaxy catalogs for both GR and alternative models to fully exploit the statistic power of the DESI survey (by matching the volumes and galaxy number densities of the mocks to those in the real survey) and to better understand the impact of key systematic effects. Using these, we identify future simulation and analysis needs for gravity tests using DESI.

A test of the standard cosmological model with geometry and growth

We perform a general test of the ΛCDM and wCDM cosmological models by comparing constraints on the geometry of the expansion history to those on the growth of structure. Specifically, we split the total matter energy density, Ω M , and (for wCDM) dark energy equation of state, w, into two parameters each: one that captures the geometry, and another that captures the growth. We constrain our split models using current cosmological data, including type Ia supernovae, baryon acoustic oscillations, redshift space distortions, gravitational lensing, and cosmic microwave background (CMB) anisotropies. We focus on two tasks: (i) constraining deviations from the standard model, captured by the parameters ΔΩ M ≡ Ω M grow-Ω M geom and Δw ≡ w grow-w geom, and (ii) investigating whether the S 8 tension between the CMB and weak lensing can be translated into a tension between geometry and growth, i.e. ΔΩ M ≠ 0, Δw ≠ 0. In both the split ΛCDM and wCDM cases, our results from combining all data are consistent with ΔΩ M = 0 and Δ w = 0.If we omit BAO/RSD data and constrain the split wCDM cosmology, we find the data prefers Δw < 0 at 3.6σ significance and ΔΩ M > 0 at 4.2σ evidence.We also find that for both CMB and weak lensing, ΔΩ M and S 8 are correlated, with CMB showing a slightly stronger correlation. The general broadening of the contours in our extended model does alleviate the S 8 tension, but the allowed nonzero values of ΔΩ M do not encompass the S 8 values that would point toward a mismatch between geometry and growth as the origin of the tension.

Measurement of redshift-space two- and three-point correlation of Lyα absorbers at 1.7 &amp;lt; z &amp;lt; 3.5: implications on evolution of the physical properties of IGM

ABSTRACT We present redshift-space two-point (ξ), three-point (ζ), and reduced three-point (Q) correlation of Lyα absorbers (Voigt profile components having H i column density, NH i &amp;gt; 1013.5 cm−2) over three redshift bins spanning 1.7 &amp;lt; z &amp;lt; 3.5 using high-resolution spectra of 292 quasars. We detect positive ξ up to 8 h−1 cMpc in all three redshift bins. The strongest detection of ζ = 1.81 ± 0.59 (with Q = 0.68 ± 0.23) is in $z$ = 1.7–2.3 bin at 1–2 h−1 cMpc. The measured ξ and ζ values show an increasing trend with NH i, while Q remains relatively independent of NH i. We find ξ and ζ to evolve strongly with redshift. Using simulations, we find that ξ and ζ seen in real space may be strongly amplified by peculiar velocities in redshift space. Simulations suggest that while feedback, thermal and pressure smoothing effects influence the clustering of Lyα absorbers at small scales, i.e. &amp;lt;0.5 h−1 cMpc, the H i photoionization rate (ΓH i) has a strong influence at all scales. The strong redshift evolution of ξ and ζ (for a fixed NH i cut-off) is driven by the redshift evolution of the relationship between NH i and baryon overdensity. Our simulation using best-fitting ΓH i($z$) measurements produces consistent clustering signals with observations at $z$ ∼ 2 but underpredicts the clustering at higher redshifts. One possible remedy is to have higher values of ΓH i at higher redshifts. Alternatively the discrepancy could be related to non-equilibrium and inhomogeneous conditions prevailing during He ii reionization not captured by our simulations.

Testing large-scale structure measurements against Fisher matrix predictions

We compare Baryonic Acoustic Oscillation (BAO) and Redshift Space Distortion (RSD) measurements from recent galaxy surveys with their Fisher matrix based predictions. Measurements of the position of the BAO signal lead to constraints on the comoving angular diameter distance DM and the Hubble distance DH that agree well with their Fisher matrix based expectations. However, RSD-based measurements of the growth rate fσ8 do not agree with the predictions made before the surveys were undertaken, even when repeating those predictions using the actual survey parameters. We show that this is due to a combination of effects including degeneracies with the geometric parameters DM and DH , and optimistic assumptions about the scale to which the linear signal can be extracted. We show that measurements using current data and large-scale modelling techniques extract an equivalent amount of signal to that in the linear regime for k ≲ 0.08 h Mpc-1, remarkably independent of the sample properties and redshifts covered.