arXiv subjects

Marc Manera

Publications and source records attributed to Marc Manera.

At least 91 records · Page 5Linked to original sources

arXiv2023

PROVABGS: The Probabilistic Stellar Mass Function of the BGS One-Percent Survey

We present the probabilistic stellar mass function (pSMF) of galaxies in the DESI Bright Galaxy Survey (BGS), observed during the One-Percent Survey. The One-Percent Survey was one of DESI's survey validation programs conducted from April to May 2021, before the start of the main survey. It used the same target selection and similar observing strategy as the main survey and successfully observed the spectra and redshifts of 143,017 galaxies in the $r < 19.5$ magnitude-limited BGS Bright sample and 95,499 galaxies in the fainter surface brightness and color selected BGS Faint sample over $z < 0.6$. We derive pSMFs from posteriors of stellar mass, $M_*$, inferred from DESI photometry and spectroscopy using the Hahn et al. (2022a; arXiv:2202.01809) PRObabilistic Value-Added BGS (PROVABGS) Bayesian SED modeling framework. We use a hierarchical population inference framework that statistically and rigorously propagates the $M_*$ uncertainties. Furthermore, we include correction weights that account for the selection effects and incompleteness of the BGS observations. We present the redshift evolution of the pSMF in BGS as well as the pSMFs of star-forming and quiescent galaxies classified using average specific star formation rates from PROVABGS. Overall, the pSMFs show good agreement with previous stellar mass function measurements in the literature. Our pSMFs showcase the potential and statistical power of BGS, which in its main survey will observe >100$\times$ more galaxies. Moreover, we present the statistical framework for subsequent population statistics measurements using BGS, which will characterize the global galaxy population and scaling relations at low redshifts with unprecedented precision.

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arXiv2023

The DESI One-Percent Survey: Exploring the Halo Occupation Distribution of Luminous Red Galaxies and Quasi-Stellar Objects with AbacusSummit

We present the first comprehensive Halo Occupation Distribution (HOD) analysis of the DESI One-Percent survey Luminous Red Galaxy (LRG) and Quasi-Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32 Mpc/h in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of fsat = 11+-1%, a mean halo mass of log10 Mh = 13.40+0.02-0.02, and a linear bias of blin = 1.93+0.06-0.04. For LRGs in 0.6 < z < 0.8, we find fsat = 14+-1%, log10 Mh = 13.24+0.02-0.02, and blin = 2.08+0.03-0.03. For QSOs, we infer fsat = 3+8-2%, log10 Mh = 12.65+0.09-0.04, and blin = 2.63+0.37-0.26 in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high-fidelity galaxy mocks. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealing significant and interesting trends in mean halo mass, linear bias, and satellite fraction.

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arXiv2023

Synthetic light cone catalogues of modern redshift and weak lensing surveys with AbacusSummit

The joint analysis of different cosmological probes, such as galaxy clustering and weak lensing, can potentially yield invaluable insights into the nature of the primordial Universe, dark energy and dark matter. However, the development of high-fidelity theoretical models that cover a wide range of scales and redshifts is a necessary stepping-stone. Here, we present public high-resolution weak lensing maps on the light cone, generated using the $N$-body simulation suite AbacusSummit in the Born approximation, and accompanying weak lensing mock catalogues, tuned via fits to the Early Data Release small-scale clustering measurements of the Dark Energy Spectroscopic Instrument (DESI). Available in this release are maps of the cosmic shear, deflection angle and convergence fields at source redshifts ranging from $z = 0.15$ to 2.45 with $Δz = 0.05$ as well as CMB convergence maps ($z \approx 1090$) for each of the 25 ${\tt base}$-resolution simulations ($L_{\rm box} = 2000\,h^{-1}{\rm Mpc}$, $N_{\rm part} = 6912^3$) as well as for the two ${\tt huge}$ simulations ($L_{\rm box} = 7500\,h^{-1}{\rm Mpc}$, $N_{\rm part} = 8640^3$) at the fiducial AbacusSummit cosmology ($Planck$ 2018). The pixel resolution of each map is 0.21 arcmin, corresponding to a HEALPiX $N_{\rm side}$ of 16384. The sky coverage of the ${\tt base}$ simulations is an octant until $z \approx 0.8$ (decreasing to about 1800 deg$^2$ at $z \approx 2.4$), whereas the ${\tt huge}$ simulations offer full-sky coverage until $z \approx 2.2$. Mock lensing source catalogues are sampled matching the ensemble properties of the Kilo-Degree Survey, Dark Energy Survey, and Hyper-Suprime Cam weak lensing datasets. The produced mock catalogues are validated against theoretical predictions for various clustering and lensing statistics such as galaxy clustering multipoles, galaxy-shear and shear-shear, showing excellent agreement.

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arXiv2023

Planting a Lyman alpha forest on AbacusSummit

The full-shape correlations of the Lyman alpha (Ly$α$) forest contain a wealth of cosmological information through the Alcock-Paczyński effect. However, these measurements are challenging to model without robustly testing and verifying the theoretical framework used for analyzing them. Here, we leverage the accuracy and volume of the $N$-body simulation suite \textsc{AbacusSummit} to generate high-resolution Ly$α$ skewers and quasi-stellar object (QSO) catalogs. One of the main goals of our mocks is to aid in the full-shape Ly$α$ analysis planned by the Dark Energy Spectroscopic Instrument (DESI) team. We provide optical depth skewers for six of the fiducial cosmology base-resolution simulations ($L_{\rm box} = 2\,h^{-1}{\rm Gpc}$, $N = 6912^3$) at $z = 2.5$. We adopt a simple recipe based on the Fluctuating Gunn-Peterson Approximation (FGPA) for constructing these skewers from the matter density in an $N$-body simulation and calibrate it against the 1D and 3D Ly$α$ power spectra extracted from the hydrodynamical simulation IllustrisTNG (TNG; $L_{\rm box} = 205\,h^{-1}{\rm Mpc}$, $N = 2500^3$). As an important application, we study the non-linear broadening of the baryon acoustic oscillation (BAO) peak and show the cross-correlation between DESI-like QSOs and our Ly$α$ forest skewers. We find differences on small scales between the Kaiser approximation prediction and our mock measurements of the Ly$α$$\times$QSO cross-correlation, which would be important to account for in upcoming analyses. The \textsc{AbacusSummit} Ly$α$ forest mocks open up the possibility for improved modelling of cross correlations between Ly$α$ and cosmic microwave background (CMB) lensing and Ly$α$ and QSOs, and for forecasts of the 3-point Ly$α$ correlation function. Our catalogues and skewers are publicly available on Globus.

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arXiv2022

Target Selection and Validation of DESI Luminous Red Galaxies

The Dark Energy Spectroscopic Instrument (DESI) is carrying out a 5-year survey that aims to measure the redshifts of tens of millions of galaxies and quasars, including 8 million luminous red galaxies (LRGs) in the redshift range of $0.4<z<{\sim}\,1.0$. Here we present the selection of the DESI LRG sample and assess its spectroscopic performance using data from Survey Validation (SV) and the first 2 months of the Main Survey. The DESI LRG sample, selected using $g$, $r$, $z$, and $W1$ photometry from the DESI Legacy Imaging Surveys, is highly robust against imaging systematics. The sample has a target density of 605 deg$^{-2}$ and a comoving number density of $5\times10^{-4}\ h^3\mathrm{Mpc}^{-3}$ in $0.4<z<0.8$; this is a significantly higher density than previous LRG surveys (such as SDSS, BOSS and eBOSS) while also extending to $z \sim 1$. After applying a bright star veto mask developed for the sample, $98.9\%$ of the observed LRG targets yield confident redshifts (with a catastrophic failure rate of $0.2\%$ in the confident redshifts), and only $0.5\%$ of the LRG targets are stellar contamination. The LRG redshift efficiency varies with source brightness and effective exposure time, and we present a simple model that accurately characterizes this dependence. In the appendices, we describe the extended LRG samples observed during SV.

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arXiv2021

Primordial non-Gaussianity without tails -- how to measure fNL with the bulk of the density PDF

We investigate the possibility to detect primordial non-Gaussianity by analysing the bulk of the probability distribution function (PDF) of late-time cosmic density fluctuations. For this purpose we devise a new method to predict the impact of general non-Gaussian initial conditions on the late-time density PDF. At redshift $z=1$ and for a smoothing scale of 30Mpc/$h$ our predictions agree with the high-resolution Quijote N-body simulations to $\sim 0.2\%$ precision. This is within cosmic variance of a $\sim 100(\mathrm{Gpc}/h)^3$ survey volume. When restricting to this 30Mpc/$h$ smoothing scale and to mildly non-linear densities ($δ[30\mathrm{Mpc}/h] \in [-0.3, 0.4]$) and also marginalizing over potential ignorance of the amplitude of the non-linear power spectrum an analysis of the PDF for such a survey volume can still measure the amplitude of different primordial bispectrum shapes to an accuracy of \smash{$Δf_{\mathrm{NL}}^{\mathrm{loc}}=\pm 7.4\ ,\ Δf_{\mathrm{NL}}^{\mathrm{equi}}=\pm 22.0\ ,\ Δf_{\mathrm{NL}}^{\mathrm{ortho}}=\pm 46.0$} . When pushing to smaller scales and assuming a joint analysis of the PDF with smoothing radii of 30Mpc/$h$ and 15Mpc/$h$ ($δ[15\mathrm{Mpc}/h] \in [-0.4, 0.5]$) this improves to \smash{$Δf_{\mathrm{NL}}^{\mathrm{loc}}=\pm 3.3\ ,\ Δf_{\mathrm{NL}}^{\mathrm{equi}}=\pm 11.0\ ,\ Δf_{\mathrm{NL}}^{\mathrm{ortho}}=\pm 17.0\ $} - even when marginalizing over the non-linear variances at both scales as two free parameters. Especially, such an analysis could simultaneously measure $f_{\mathrm{NL}}$ and the amplitude and slope of the non-linear power spectrum. However, at 15Mpc/$h$ our predictions are only accurate to $\lesssim 0.8\%$ for the considered density range. We discuss how this has to be improved in order to push to these small scales and make full use of upcoming surveys with a PDF-based analysis.

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arXiv2020

Obtaining non-linear galaxy bias constraints from galaxy-lensing phase differences

We demonstrate the utility and constraining power of a new statistic for investigating galaxy bias: the galaxy-lensing phase difference. The statistic consists in taking the differences of the phases of the harmonic wave-modes between the weak lensing convergence field and the galaxy count field. We use dark matter simulations populated with galaxies up to redshift $z=1$ to test the performance of this estimator. We find that phase differences are sensitive to the absolute value of the second order bias ($c_2=b_2/b_1$), and demonstrate why this is the case. For a $\sim$1500 sq. deg. galaxy survey we recover $c_2$ with an error of approximately $0.1$ for a wide range of $c_2$ values; current constraints from redshift surveys have errors of 0.1-0.6 depending on redshift. This new statistic is therefore expected to provide constraints for $c_2$ which are complementary and competitive with constraining power by the conventional estimators from the power spectrum and bispectrum. For the Dark Energy Survey (DES), we predict leading measurements of second-order bias.

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arXiv2020

GEOMAX: beyond linear compression for 3pt galaxy clustering statistics

We present the GEOMAX algorithm and its Python implementation for a two-step compression of bispectrum measurements. The first step groups bispectra by the geometric properties of their arguments; the second step then maximises the Fisher information with respect to a chosen set of model parameters in each group. The algorithm only requires the derivatives of the data vector with respect to the parameters and a small number of mock data, producing an effective, non-linear compression. By applying GEOMAX to bispectrum monopole measurements from BOSS DR12 CMASS redshift-space galaxy clustering data, we reduce the $68\%$ credible intervals for the inferred parameters $\left(b_1,b_2,f,σ_8\right)$ by $\left(50.4\%,56.1\%,33.2\%,38.3\%\right)$ with respect to standard MCMC on the full data vector. We run the analysis and comparison between compression methods over one hundred galaxy mocks to test the statistical significance of the improvements. On average GEOMAX performs $\sim15\%$ better than geometrical or maximal linear compression alone and is consistent with being lossless. Given its flexibility, the GEOMAX approach has the potential to optimally exploit three-point statistics of various cosmological probes like weak lensing or line-intensity maps from current and future cosmological data-sets such as DESI, Euclid, PFS and SKA.

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arXiv2019

Advancing the matter bispectrum estimation of large-scale structure: fast prescriptions for galaxy mock catalogues

We investigate various phenomenological schemes for the rapid generation of 3D mock galaxy catalogues with a given power spectrum and bispectrum. We apply the fast bispectrum estimator \MODALLSS{} to these mock galaxy catalogues and compare to $N$-body simulation data analysed with the halo-finder \texttt{ROCKSTAR} (our benchmark data). We propose an assembly bias model for populating parent halos with subhalos by using a joint lognormal-Gaussian probability distribution for the subhalo occupation number and the halo concentration. This prescription enabled us to recover the benchmark power spectrum from $N$-body simulations to within 1\% and the bispectrum to within 4\% across the entire range of scales of the simulation. A small further boost adding an extra galaxy to all parent halos above the mass threshold $M>2\times10^{14}\,h^{-1} M_\odot$ obtained a better than 1\% fit to both power spectrum and bispectrum in the range $K/3<1.1\,h\,\text{Mpc}^{-1}$, where $K=k_1+k_2+k_3$. This statistical model should be applicable to fast dark matter codes, allowing rapid generation of mock catalogues which simultaneously reproduce the halo power spectrum and bispectrum obtained from $N$-body simulations. We also investigate alternative schemes using the Halo Occupation Distribution (HOD) which depend only on halo mass, but these yield results deficient in both the power spectrum (2\%) and the bispectrum (>4\%) at $k,K/3 \approx 0.2\,h\,\text{Mpc}^{-1}$, with poor scaling for the latter. Efforts to match the power spectrum by modifying the standard four-parameter HOD model result in overboosting the bispectrum (with a 10\% excess). We also characterise the effect of changing the halo profile on the power spectrum and bispectrum.

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arXiv2019

Cosmological Measurements from Angular Power Spectra Analysis of BOSS DR12 Tomography

We constrain cosmological parameters by analysing the angular power spectra of the Baryon Oscillation Spectroscopic Survey DR12 galaxies, a spectroscopic follow-up of around 1.3 million SDSS galaxies over 9,376 deg$^2$ with an effective volume of $\sim 6.5$ (Gpc $h^{-1}$)$^3$ in the redshift range $0.15 \leq z < 0.80$. We split this sample into 13 tomographic bins ($Δz = 0.05$); angular power spectra were calculated using a Pseudo-$C_{\ell}$ estimator, and covariance matrices were estimated using log-normal simulated maps. Cosmological constraints obtained from these data were combined with constraints from Planck CMB experiment as well as the JLA supernovae compilation. Considering a $w$CDM cosmological model measured on scales up to $k_{max} = 0.07h$ Mpc$^{-1}$, we constrain a constant dark energy equation-of-state with a $\sim 4\%$ error at the 1-$σ$ level: $w_0 = -0.993^{+0.046}_{-0.043}$, together with $Ω_m = 0.330\pm 0.012$, $Ω_b = 0.0505 \pm 0.002$, $S_8 \equiv σ_8 \sqrt{Ω_m/0.3} = 0.863 \pm 0.016$, and $h = 0.661 \pm 0.012$. For the same combination of datasets, but now considering a $Λ$CDM model with massive neutrinos and the same scale cut, we find: $Ω_m = 0.328 \pm 0.009$, $Ω_b = 0.05017^{+0.0009}_{-0.0008}$, $S_8 = 0.862 \pm 0.017$, and $h = 0.663^{+0.006}_{-0.007}$ and a 95\% credible interval (CI) upper limit of $\sum m_ν < 0.14$ eV for a normal hierarchy. These results are competitive if not better than standard analyses with the same dataset, and demonstrate this should be a method of choice for future surveys, opening the door for their full exploitation in cross-correlations probes.

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arXiv2019

Upper Bound of Neutrino Masses from Combined Cosmological Observations and Particle Physics Experiments

We investigate the impact of prior models on the upper bound of the sum of neutrino masses, $\sum m_ν$. We use data from Large Scale Structure of galaxies, Cosmic Microwave Background, Type Ia SuperNovae, and Big Bang Nucleosynthesis. We probe physically motivated neutrino mass models (respecting oscillation experiment constraints) and compare them to constraints using standard cosmological approximations. The former give a consistent upper bound of $\sum m_ν \lesssim 0.26$ eV ($95\%$ CI) and yields a strong competitive upper bound for the lightest neutrino mass species, $m_0^ν < 0.086$ eV ($95\%$ CI). By contrast one of the approximations, which is somewhat inconsistent with oscillation experiments, yields an upper bound of $\sum m_ν \lesssim 0.15$ eV ($95\%$ CI), which differs substantially from the former upper bound. We, therefore, argue that cosmological neutrino mass and hierarchy determination should be pursued using physically motivated models since approximations might lead to incorrect and nonphysical upper bounds.

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arXiv2019

The Dark Energy Spectroscopic Instrument (DESI)

We present the status of the Dark Energy Spectroscopic Instrument (DESI) and its plans and opportunities for the coming decade. DESI construction and its initial five years of operations are an approved experiment of the US Department of Energy and is summarized here as context for the Astro2020 panel. Beyond 2025, DESI will require new funding to continue operations. We expect that DESI will remain one of the world's best facilities for wide-field spectroscopy throughout the decade. More about the DESI instrument and survey can be found at https://www.desi.lbl.gov.

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arXiv2019

Enhancing BOSS bispectrum cosmological constraints with maximal compression

We apply two compression methods to the galaxy power spectrum monopole/quadrupole and bispectrum monopole measurements from the BOSS DR12 CMASS sample. Both methods reduce the dimension of the original data-vector to the number of cosmological parameters considered, using the Karhunen-Loève algorithm with an analytic covariance model. In the first case, we infer the posterior through MCMC sampling from the likelihood of the compressed data-vector (MC-KL). The second, faster option, works by first Gaussianising and then orthogonalising the parameter space before the compression; in this option (G-PCA) we only need to run a low-resolution preliminary MCMC sample for the Gaussianization to compute our posterior. Both compression methods accurately reproduce the posterior distributions obtained by standard MCMC sampling on the CMASS dataset for a $k$-space range of $0.03-0.12\,h/\mathrm{Mpc}$. The compression enables us to increase the number of bispectrum measurements by a factor of $\sim 23$ over the standard binning (from 116 to 2734 triangles used), which is otherwise limited by the number of mock catalogues available. This reduces the $68\%$ credible intervals for the parameters $\left(b_1,b_2,f,σ_8\right)$ by $\left(-24.8\%,-52.8\%,-26.4\%,-21\%\right)$, respectively. The best-fit values we obtain are $(b_1=2.31\pm0.17,b_2=0.77\pm0.19,$ $f(z_{\mathrm{CMASS}})=0.67\pm0.06,σ_8(z_{\mathrm{CMASS}})=0.51\pm0.03)$. Using these methods for future redshift surveys like DESI, Euclid and PFS will drastically reduce the number of simulations needed to compute accurate covariance matrices and will facilitate tighter constraints on cosmological parameters.

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arXiv2019

Geometrical compression: a new method to enhance the BOSS galaxy bispectrum monopole constraints

We present a novel method to compress galaxy clustering three-point statistics and apply it to redshift space galaxy bispectrum monopole measurements from BOSS DR12 CMASS data considering a $k$-space range of $0.03-0.12\,h/\mathrm{Mpc}$. The method consists in binning together bispectra evaluated at sets of wave-numbers forming closed triangles with similar geometrical properties: the area, the cosine of the largest angle and the ratio between the cosines of the remaining two angles. This enables us to increase the number of bispectrum measurements for example by a factor of $23$ over the standard binning (from 116 to 2734 triangles used), which is otherwise limited by the number of mock catalogues available to estimate the covariance matrix needed to derive parameter constraints. The $68\%$ credible intervals for the inferred parameters $\left(b_1,b_2,f,σ_8\right)$ are thus reduced by $\left(-39\%,-49\%,-29\%,-22\%\right)$, respectively. We find very good agreement with the posteriors recently obtained by alternative maximal compression methods. This new method does not require the a-priori computation of the data-vector covariance matrix and has the potential to be directly applicable to other three-point statistics (e.g. glaxy clustering, weak gravitational lensing, 21 cm emission line) measured from future surveys such as DESI, Euclid, PFS and SKA.

astro-ph.CO↗

arXiv2018

Maximal compression of the redshift space galaxy power spectrum and bispectrum

We explore two methods of compressing the redshift space galaxy power spectrum and bispectrum with respect to a chosen set of cosmological parameters. Both methods involve reducing the dimension of the original data-vector ( e.g. 1000 elements ) to the number of cosmological parameters considered ( e.g. seven ) using the Karhunen-Loève algorithm. In the first case, we run MCMC sampling on the compressed data-vector in order to recover the one-dimensional (1D) and two-dimensional (2D) posterior distributions. The second option, approximately 2000 times faster, works by orthogonalising the parameter space through diagonalisation of the Fisher information matrix before the compression, obtaining the posterior distributions without the need of MCMC sampling. Using these methods for future spectroscopic redshift surveys like DESI, EUCLID and PFS would drastically reduce the number of simulations needed to compute accurate covariance matrices with minimal loss of constraining power. We consider a redshift bin of a DESI-like experiment. Using the power spectrum combined with the bispectrum as a data-vector, both compression methods on average recover the 68% credible regions to within 0.7% and 2% of those resulting from standard MCMC sampling respectively. These confidence intervals are also smaller than the ones obtained using only the power spectrum by (81%, 80%, 82%) respectively for the bias parameter b_1, the growth rate f and the scalar amplitude parameter A_s.

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arXiv2017

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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arXiv2017

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: single-probe measurements and the strong power of normalized growth rate on constraining dark energy

We present measurements of the anisotropic galaxy clustering from the Data Release 9 (DR9) CMASS sample of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). We analyze the broad-range shape of the monopole and quadrupole correlation functions to obtain constraints, at the effective redshift $z=0.57$ of the sample, on the Hubble expansion rate $H(z)$, the angular-diameter distance $D_A(z)$, the normalized growth rate $f(z)σ_8(z)$, the physical matter density $Ω_m h^2$, and the biased amplitude of matter fluctuation bσ_8(z). We obtain {$H(0.57)$, $D_A(0.57)$, $f(0.57)σ_8(0.57)$, $Ω_m h^2$, $bσ_8(0.57)$} = {$87.6_{-6.8}^{+6.7}$, $1396\pm73$, $0.126_{-0.010}^{+0.008}$, $1.19\pm0.14$, $0.428\pm0.066$} and their covariance matrix as well. The parameters which are not well constrained by our of galaxy clustering analysis are marginalized over with wide flat priors. Since no priors from other data sets (i.e., CMB) are adopted and no dark energy models are assumed, our results from BOSS CMASS galaxy clustering alone may be combined with other data sets, i.e. CMB, SNe, lensing or other galaxy clustering data to constrain the parameters of a given cosmological model. We show that the major power on constraining dark energy from the anisotropic galaxy clustering signal, as compared to the angular-averaged one (monopole), arises from including the normalized growth rate $f(z)σ_8(z)$. In the case of the wCDM cosmological model our single-probe CMASS constraints, combined with CMB (WMAP9+SPT), yield a value for the dark energy equation of state parameter of $w=-0.90\pm0.11$. Therefore, it is important to include $f(z)σ_8(z)$ while investigating the nature of dark energy with current and upcoming large-scale galaxy surveys.

astro-ph.CO↗

arXiv2017

COLA with scale-dependent growth: applications to screened modified gravity models

We present a general parallelized and easy-to-use code to perform numerical simulations of structure formation using the COLA (COmoving Lagrangian Acceleration) method for cosmological models that exhibit scale-dependent growth at the level of first and second order Lagrangian perturbation theory. For modified gravity theories we also include screening using a fast approximate method that covers all the main examples of screening mechanisms in the literature. We test the code by comparing it to full simulations of two popular modified gravity models, namely $f(R)$ gravity and nDGP, and find good agreement in the modified gravity boost-factors relative to $Λ$CDM even when using a fairly small number of COLA time steps.

astro-ph.CO↗