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Martin Crocce

Publications and source records attributed to Martin Crocce.

At least 37 records · Page 2Linked to original sources

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing

We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for $S_8 =σ_8(Ω_{\rm m}/0.3)^{0.5}= 0.65\pm 0.04$, driven by a low matter density parameter, $Ω_{\rm m}=0.179^{+0.031}_{-0.038}$, with $σ_8-Ω_{\rm m}$ posteriors in $2.4σ$ tension with the DES Y1 3x2pt results, and in $5.6σ$ with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with X-ray and microwave data, as well as independent constraints on the observable--mass relation from SZ selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold ($λ\ge 30$) significantly reduces the tension with other probes, and points to one or more richness-dependent effects not captured by our model.

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Comparing approximate methods for mock catalogues and covariance matrices I: correlation function

This paper is the first in a set that analyses the covariance matrices of clustering statistics obtained from several approximate methods for gravitational structure formation. We focus here on the covariance matrices of anisotropic two-point correlation function measurements. Our comparison includes seven approximate methods, which can be divided into three categories: predictive methods that follow the evolution of the linear density field deterministically (ICE-COLA, Peak Patch, and Pinocchio), methods that require a calibration with N-body simulations (Patchy and Halogen), and simpler recipes based on assumptions regarding the shape of the probability distribution function (PDF) of density fluctuations (log-normal and Gaussian density fields). We analyse the impact of using covariance estimates obtained from these approximate methods on cosmological analyses of galaxy clustering measurements, using as a reference the covariances inferred from a set of full N-body simulations. We find that all approximate methods can accurately recover the mean parameter values inferred using the N-body covariances. The obtained parameter uncertainties typically agree with the corresponding N-body results within 5% for our lower mass threshold, and 10% for our higher mass threshold. Furthermore, we find that the constraints for some methods can differ by up to 20% depending on whether the halo samples used to define the covariance matrices are defined by matching the mass, number density, or clustering amplitude of the parent N-body samples. The results of our configuration-space analysis indicate that most approximate methods provide similar results, with no single method clearly outperforming the others.

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The Physics of the Accelerating Universe Camera

The PAU (Physics of the Accelerating Universe) Survey goal is to obtain photometric redshifts (photo-z) and Spectral Energy Distribution (SED) of astronomical objects with a resolution roughly one order of magnitude better than current broad band photometric surveys. To accomplish this, a new large field of view camera (PAUCam) has been designed, built, commissioned and is now operated at the William Herschel Telescope (WHT). With the current WHT Prime Focus corrector, the camera covers ~1-degree diameter Field of View (FoV), of which, only the inner ~40 arcmin diameter are unvignetted. The focal plane consists of a mosaic of 18 2k$x4k Hamamatsu fully depleted CCDs, with high quantum efficiency up to 1 micrometers in wavelength. To maximize the detector coverage within the FoV, filters are placed in front of the CCDs inside the camera cryostat (made out of carbon fiber) using a challenging movable tray system. The camera uses a set of 40 narrow band filters ranging from ~4500 to ~8500 Angstroms complemented with six standard broad-band filters, ugrizY. The PAU Survey aims to cover roughly 100 square degrees over fields with existing deep photometry and galaxy shapes to obtain accurate photometric redshifts for galaxies down to i_AB~22.5, detecting also galaxies down to i_AB~24 with less precision in redshift. With this data set we will be able to measure intrinsic alignments, galaxy clustering and perform galaxy evolution studies in a new range of densities and redshifts. Here, we describe the PAU camera, its first commissioning results and performance.

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Comparing approximate methods for mock catalogues and covariance matrices II: Power spectrum multipoles

We study the accuracy of several approximate methods for gravitational dynamics in terms of halo power spectrum multipoles and their estimated covariance matrix. We propagate the differences in covariances into parameter constrains related to growth rate of structure, Alcock-Paczynski distortions and biasing. We consider seven methods in three broad categories: algorithms that solve for halo density evolution deterministically using Lagrangian trajectories (ICE-COLA, Pinocchio and PeakPatch), methods that rely on halo assignment schemes onto dark-matter overdensities calibrated with a target N-body run (Halogen, Patchy) and two standard assumptions about the full density PDF (Gaussian and Lognormal). We benchmark their performance against a set of three hundred N-body simulations, running similar sets of approximate simulations with matched initial conditions, for each method. We find that most methods reproduce the monopole to within $5\%$, while residuals for the quadrupole are sometimes larger and scale dependent. The variance of the multipoles is typically reproduced within $10\%$. Overall, we find that covariances built from approximate simulations yield errors on model parameters within $10\%$ of those from the N-body based covariance.

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The Buzzard Flock: Dark Energy Survey Synthetic Sky Catalogs

We present a suite of 18 synthetic sky catalogs designed to support science analysis of galaxies in the Dark Energy Survey Year 1 (DES Y1) data. For each catalog, we use a computationally efficient empirical approach, ADDGALS, to embed galaxies within light-cone outputs of three dark matter simulations that resolve halos with masses above ~5x10^12 h^-1 m_sun at z <= 0.32 and 10^13 h^-1 m_sun at z~2. The embedding method is tuned to match the observed evolution of galaxy counts at different luminosities as well as the spatial clustering of the galaxy population. Galaxies are lensed by matter along the line of sight --- including magnification, shear, and multiple images --- using CALCLENS, an algorithm that calculates shear with 0.42 arcmin resolution at galaxy positions in the full catalog. The catalogs presented here, each with the same LCDM cosmology (denoted Buzzard), contain on average 820 million galaxies over an area of 1120 square degrees with positions, magnitudes, shapes, photometric errors, and photometric redshift estimates. We show that the weak-lensing shear catalog, redMaGiC galaxy catalogs and redMaPPer cluster catalogs provide plausible realizations of the same catalogs in the DES Y1 data by comparing their magnitude, color and redshift distributions, angular clustering, and mass-observable relations, making them useful for testing analyses that use these samples. We make public the galaxy samples appropriate for the DES Y1 data, as well as the data vectors used for cosmology analyses on these simulations.

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Comparing approximate methods for mock catalogues and covariance matrices III: Bispectrum

We compare the measurements of the bispectrum and the estimate of its covariance obtained from a set of different methods for the efficient generation of approximate dark matter halo catalogs to the same quantities obtained from full N-body simulations. To this purpose we employ a large set of three-hundred realisations of the same cosmology for each method, run with matching initial conditions in order to reduce the contribution of cosmic variance to the comparison. In addition, we compare how the error on cosmological parameters such as linear and nonlinear bias parameters depends on the approximate method used for the determination of the bispectrum variance. As general result, most methods provide errors within 10% of the errors estimated from N-body simulations. Exceptions are those methods requiring calibration of the clustering amplitude but restrict this to two-point statistics. Finally we test how our results are affected by being limited to a few hundreds measurements from N-body simulation, and therefore to the bispectrum variance, by comparing with a larger set of several thousands realisations performed with one approximate method.

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Testing the consistency of three-point halo clustering in Fourier and configuration space

We compare reduced three-point correlations $Q$ of matter, haloes (as proxies for galaxies) and their cross correlations, measured in a total simulated volume of $\sim100 \ (h^{-1} \text{Gpc})^{3}$, to predictions from leading order perturbation theory on a large range of scales in configuration space. Predictions for haloes are based on the non-local bias model, employing linear ($b_1$) and non-linear ($c_2$, $g_2$) bias parameters, which have been constrained previously from the bispectrum in Fourier space. We also study predictions from two other bias models, one local ($g_2=0$) and one in which $c_2$ and $g_2$ are determined by $b_1$ via an approximately universal relation. Overall, measurements and predictions agree when $Q$ is derived for triangles with $(r_1r_2r_3)^{1/3} \gtrsim 60 h^{-1}\text{Mpc}$, where $r_{1-3}$ are the sizes of the triangle legs. Predictions for $Q_{matter}$, based on the linear power spectrum, show significant deviations from the measurements at the BAO scale (given our small measurement errors), which strongly decrease when adding a damping term or using the non-linear power spectrum, as expected. Predictions for $Q_{halo}$ agree best with measurements at large scales when considering non-local contributions. The universal bias model works well for haloes and might therefore be also useful for tightening constraints on $b_1$ from $Q$ in galaxy surveys. Such constraints are independent of the amplitude of matter density fluctuation ($σ_8$) and hence break the degeneracy between $b_1$ and $σ_8$, present in galaxy two-point correlations.

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Optimized Clustering Estimators for BAO Measurements Accounting for Significant Redshift Uncertainty

We determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the baryon acoustic oscillation (BAO) information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line-of-sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertainty $σ_z \geq 0.02(1+z)$ we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for $σ_z \geq 0.02(1+z)$. For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations (combining two separate sets) of galaxy simulations mimicking the Dark Energy Survey Year 1 sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.

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Accurate Estimators of Correlation Functions in Fourier Space

Efficient estimators of Fourier-space statistics for large number of objects rely on Fast Fourier Transforms (FFTs), which are affected by aliasing from unresolved small scale modes due to the finite FFT grid. Aliasing takes the form of a sum over images, each of them corresponding to the Fourier content displaced by increasing multiples of the sampling frequency of the grid. These spurious contributions limit the accuracy in the estimation of Fourier-space statistics, and are typically ameliorated by simultaneously increasing grid size and discarding high-frequency modes. This results in inefficient estimates for e.g. the power spectrum when desired systematic biases are well under per-cent level. We show that using interlaced grids removes odd images, which include the dominant contribution to aliasing. In addition, we discuss the choice of interpolation kernel used to define density perturbations on the FFT grid and demonstrate that using higher-order interpolation kernels than the standard Cloud in Cell algorithm results in significant reduction of the remaining images. We show that combining fourth-order interpolation with interlacing gives very accurate Fourier amplitudes and phases of density perturbations. This results in power spectrum and bispectrum estimates that have systematic biases below 0.01% all the way to the Nyquist frequency of the grid, thus maximizing the use of unbiased Fourier coefficients for a given grid size and greatly reducing systematics for applications to large cosmological datasets.

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ICE-COLA: fast simulations for weak lensing observables

Approximate methods to full N-body simulations provide a fast and accurate solution to the development of mock catalogues for the modeling of galaxy clustering observables. In this paper we extend ICE-COLA (Izard et al. 2016), based on an optimized implementation of the approximate COLA method, to produce weak lensing maps and halo catalogues in the light cone using an integrated and self consistent approach. We show that despite the approximate dynamics, the catalogues thus produced enable an accurate modeling of weak lensing observables one decade beyond the characteristic scale where the growth becomes non-linear. In particular, we compare ICE-COLA to the MICE-GC N-body simulation for some fiducial cases representative of upcoming surveys and find that, for sources at redshift $z=1$, their convergence power spectra agree to within one percent up to high multipoles (i.e., of order $1000$). The corresponding shear two point functions, $ξ_{+}$ and $ξ_{-}$, yield similar accuracy down to $2$ and $20$ arcmin respectively, while tangential shear around a $z=0.5$ lens sample is accurate down to $4$ arcmin. We show that such accuracy is stable against an increased angular resolution of the weak lensing maps. Hence, this opens the possibility of using approximate methods for the joint modeling of galaxy clustering and weak lensing observables and their covariance in ongoing and future galaxy surveys.

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The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Angular clustering tomography and its cosmological implications

We investigate the cosmological implications of studying galaxy clustering using a tomographic approach applied to the final BOSS DR12 galaxy sample, including both auto- and cross-correlation functions between redshift shells. We model the signal of the full shape of the angular correlation function, $ω(θ)$, in redshift bins using state-of-the-art modelling of non-linearities, bias and redshift-space distortions. We present results on the redshift evolution of the linear bias of BOSS galaxies, which cannot be obtained with traditional methods for galaxy-clustering analysis. We also obtain constraints on cosmological parameters, combining this tomographic analysis with measurements of the cosmic microwave background (CMB) and type Ia supernova (SNIa). We explore a number of cosmological models, including the standard $Λ$CDM model and its most interesting extensions, such as deviations from $w_\rm{DE} = -1$, non-minimal neutrino masses, spatial curvature and deviations from general relativity using the growth-index $γ$ parametrisation. These results are, in general, comparable to the most precise present-day constraints on cosmological parameters, and show very good agreement with the standard model. In particular, combining CMB, $ω(θ)$ and SNIa, we find a value of $w_\rm{DE}$ consistent with $-1$ to a precision better than 5\% when it is assumed to be constant in time, and better than 6\% when we also allow for a spatially-curved Universe.

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The DESI Experiment Part I: Science,Targeting, and Survey Design

DESI (Dark Energy Spectroscopic Instrument) is a Stage IV ground-based dark energy experiment that will study baryon acoustic oscillations (BAO) and the growth of structure through redshift-space distortions with a wide-area galaxy and quasar redshift survey. To trace the underlying dark matter distribution, spectroscopic targets will be selected in four classes from imaging data. We will measure luminous red galaxies up to $z=1.0$. To probe the Universe out to even higher redshift, DESI will target bright [O II] emission line galaxies up to $z=1.7$. Quasars will be targeted both as direct tracers of the underlying dark matter distribution and, at higher redshifts ($ 2.1 < z < 3.5$), for the Ly-$α$ forest absorption features in their spectra, which will be used to trace the distribution of neutral hydrogen. When moonlight prevents efficient observations of the faint targets of the baseline survey, DESI will conduct a magnitude-limited Bright Galaxy Survey comprising approximately 10 million galaxies with a median $z\approx 0.2$. In total, more than 30 million galaxy and quasar redshifts will be obtained to measure the BAO feature and determine the matter power spectrum, including redshift space distortions.

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The DESI Experiment Part II: Instrument Design

DESI (Dark Energy Spectropic Instrument) is a Stage IV ground-based dark energy experiment that will study baryon acoustic oscillations and the growth of structure through redshift-space distortions with a wide-area galaxy and quasar redshift survey. The DESI instrument is a robotically-actuated, fiber-fed spectrograph capable of taking up to 5,000 simultaneous spectra over a wavelength range from 360 nm to 980 nm. The fibers feed ten three-arm spectrographs with resolution $R= λ/Δλ$ between 2000 and 5500, depending on wavelength. The DESI instrument will be used to conduct a five-year survey designed to cover 14,000 deg$^2$. This powerful instrument will be installed at prime focus on the 4-m Mayall telescope in Kitt Peak, Arizona, along with a new optical corrector, which will provide a three-degree diameter field of view. The DESI collaboration will also deliver a spectroscopic pipeline and data management system to reduce and archive all data for eventual public use.

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The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological implications of the configuration-space clustering wedges

We explore the cosmological implications of anisotropic clustering measurements in configuration space of the final galaxy samples from Data Release 12 of the SDSS-III Baryon Oscillation Spectroscopic Survey. We implement a new detailed modelling of the effects of non-linearities, galaxy bias and redshift-space distortions that can be used to extract unbiased cosmological information from our measurements for scales $s \gtrsim 20\,h^{-1}{\rm Mpc}$. We combined the galaxy clustering information from BOSS with the latest cosmic microwave background (CMB) observations and Type Ia supernovae samples and found no significant evidence for a deviation from the $Λ$CDM cosmological model. In particular, these data sets can constrain the dark energy equation of state parameter to $w_{\rm DE}=-0.996\pm0.042$ when assumed time-independent, the curvature of the Universe to $Ω_{k}=-0.0007\pm 0.0030$ and the sum of the neutrino masses to $\sum m_ν < 0.25\,{\rm eV}$ at 95 per cent CL. We explore the constraints on the growth rate of cosmic structures assuming $f(z)=Ω_{\rm m}(z)^γ$ and obtain $γ= 0.609\pm 0.079$, in good agreement with the predictions of general relativity of $γ=0.55$. We compress the information of our clustering measurements into constraints on the parameter combinations $D_{\rm V}(z)/r_{\rm d}$, $F_{\rm AP}(z)$ and $fσ_8(z)$ at the effective redshifts of $z=0.38$, $0.51$ and $0.61$ with their respective covariance matrices and find good agreement with the predictions for these parameters obtained from the best-fitting $Λ$CDM model to the CMB data from the Planck satellite. This paper is part of a set that analyses the final galaxy clustering dataset from BOSS. The measurements and likelihoods presented here are combined with others in Alam et al. (2016) to produce the final cosmological constraints from BOSS.

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A new method to measure galaxy bias by combining the density and weak lensing fields

We present a new method to measure the redshift-dependent galaxy bias by combining information from the galaxy density field and the weak lensing field. This method is based on Amara et al. (2012), where they use the galaxy density field to construct a bias-weighted convergence field kg. The main difference between Amara et al. (2012) and our new implementation is that here we present another way to measure galaxy bias using tomography instead of bias parameterizations. The correlation between kg and the true lensing field k allows us to measure galaxy bias using different zero-lag correlations, such as / or / . Our method measures the linear bias factor on linear scales under the assumption of no stochasticity between galaxies and matter. We use the MICE simulation to measure the linear galaxy bias for a flux-limited sample (i < 22.5) in tomographic redshift bins using this method. This paper is the first that studies the accuracy and systematic uncertainties associated with the implementation of the method, and the regime where it is consistent with the linear galaxy bias defined by projected 2-point correlation functions (2PCF). We find that our method is consistent with linear bias at the percent level for scales larger than 30 arcmin, while nonlinearities appear at smaller scales. This measurement is a good complement to other measurements of bias, since it does not depend strongly on sigma8 as the 2PCF measurements. We apply this method to the Dark Energy Survey Science Verification data in a follow-up paper.

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Cosmology from large scale galaxy clustering and galaxy-galaxy lensing with Dark Energy Survey Science Verification data

We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 square degree contiguous patch of DES data from the Science Verification (SV) period of observations. Using large scale measurements, we constrain the matter density of the Universe as Omega_m = 0.31 +/- 0.09 and the clustering amplitude of the matter power spectrum as sigma_8 = 0.74 +/- 0.13 after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into S_8 = sigma_8(Omega_m/0.3)^{0.16} = 0.74 +/- 0.12 for our fiducial lens redshift bin at 0.35 <z< 0.5, while S_8 = 0.78 +/- 0.09 using two bins over the range 0.2 <z< 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck CMB data, Baryon Accoustic Oscillations and Supernova type Ia measurements.

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ICE-COLA: Towards fast and accurate synthetic galaxy catalogues optimizing a quasi $N$-body method

Next generation galaxy surveys demand the development of massive ensembles of galaxy mocks to model the observables and their covariances, what is computationally prohibitive using $N$-body simulations. COLA is a novel method designed to make this feasible by following an approximate dynamics but with up to 3 orders of magnitude speed-ups when compared to an exact $N$-body. In this paper we investigate the optimization of the code parameters in the compromise between computational cost and recovered accuracy in observables such as two-point clustering and halo abundance. We benchmark those observables with a state-of-the-art $N$-body run, the MICE Grand Challenge simulation (MICE-GC). We find that using 40 time steps linearly spaced since $z_i \sim 20$, and a force mesh resolution three times finer than that of the number of particles, yields a matter power spectrum within $1\%$ for $k \lesssim 1\,h {\rm Mpc}^{-1}$ and a halo mass function within $5\%$ of those in the $N$-body. In turn the halo bias is accurate within $2\%$ for $k \lesssim 0.7\,h {\rm Mpc}^{-1}$ whereas, in redshift space, the halo monopole and quadrupole are within $4\%$ for $k \lesssim 0.4\,h {\rm Mpc}^{-1}$. These results hold for a broad range in redshift ($0 < z < 1$) and for all halo mass bins investigated ($M > 10^{12.5} \, h^{-1} \, {\rm M_{\odot}}$). To bring accuracy in clustering to one percent level we study various methods that re-calibrate halo masses and/or velocities. We thus propose an optimized choice of COLA code parameters as a powerful tool to optimally exploit future galaxy surveys.

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nIFTy Cosmology: Galaxy/halo mock catalogue comparison project on clustering statistics

We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point and the three-point clustering statistics. The reference catalogues are drawn from the BigMultiDark N-body simulation. Both friend-of-friends (including distinct halos only) and spherical overdensity (including distinct halos and subhalos) catalogs have been used with the typical number density of a large-volume galaxy surveys. We demonstrate that a proper biasing model is essential for reproducing the power spectrum at quasilinear and even smaller scales. With respect to various clustering statistics a methodology based on perturbation theory and a realistic biasing model leads to very good agreement with N-body simulations. However, for the quadrupole of the correlation function or the power spectrum, only the method based on semi-N-body simulation could reach high accuracy (1% level) at small scales, i.e., r<25 Mpc/h or k>0.15 h/Mpc. Full N-body solutions will remain indispensable to produce reference catalogues. Nevertheless, we have demonstrated that the far more efficient approximate solvers can reach a few percent accuracy in terms of clustering statistics at the scales interesting for the large-scale structure analysis after calibration with a few reference N-body calculations. This makes them useful for massive production aimed at covariance studies, to scan large parameter spaces, and to estimate uncertainties in data analysis techniques, such as baryon acoustic oscillation reconstruction, redshift distortion measurements, etc.

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