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Matthew R. Becker

Publications and source records attributed to Matthew R. Becker.

At least 37 records · Page 2Linked to original sources

Astro2020: Empirically Constraining Galaxy Evolution

Over the past decade, empirical constraints on the galaxy-dark matter halo connection have significantly advanced our understanding of galaxy evolution. Past techniques have focused on connections between halo properties and galaxy stellar mass and/or star formation rates. Empirical techniques in the next decade will link halo assembly histories with galaxies' circumgalactic media, supermassive black holes, morphologies, kinematics, sizes, colors, metallicities, and transient rates. Uncovering these links will resolve many critical uncertainties in galaxy formation and will enable much higher-fidelity mock catalogs essential for interpreting observations. Achieving these results will require broader and deeper spectroscopic coverage of galaxies and their circumgalactic media; survey teams will also need to meet several criteria (cross-comparisons, public access, and covariance matrices) to facilitate combining data across different surveys. Acting on these recommendations will continue enabling dramatic progress in both empirical modeling and galaxy evolution for the next decade.

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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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Cosmic Shear as a Probe of Galaxy Formation Physics

We evaluate the potential for current and future cosmic shear measurements from large galaxy surveys to constrain the impact of baryonic physics on the matter power spectrum. We do so using a model-independent parameterization that describes deviations of the matter power spectrum from the dark-matter-only case as a set of principal components that are localized in wavenumber and redshift. We perform forecasts for a variety of current and future datasets, and find that at least ~90% of the constraining power of these datasets is contained in no more than nine principal components. The constraining power of different surveys can be quantified using a figure of merit defined relative to currently available surveys. With this metric, we find that the final Dark Energy Survey dataset (DES Y5) and the Hyper Suprime Cam Survey will be roughly an order of magnitude more powerful than existing data in constraining baryonic effects. Upcoming Stage IV surveys (LSST, Euclid, and WFIRST) will improve upon this by a further factor of a few. We show that this conclusion is robust to marginalization over several key systematics. The ultimate power of cosmic shear to constrain galaxy formation is dependent on understanding systematics in the shear measurements at small (sub-arcminute) scales. If these systematics can be sufficiently controlled, cosmic shear measurements from DES Y5 and other future surveys have the potential to provide a very clean probe of galaxy formation and to strongly constrain a wide range of predictions from modern hydrodynamical simulations.

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The Aemulus Project III: Emulation of the Galaxy Correlation Function

Using the N-body simulations of the AEMULUS Project, we construct an emulator for the non-linear clustering of galaxies in real and redshift space. We construct our model of galaxy bias using the halo occupation framework, accounting for possible velocity bias. The model includes 15 parameters, including both cosmological and galaxy bias parameters. We demonstrate that our emulator achieves ~ 1% precision at the scales of interest, 0.1<r<10 h^{-1} Mpc, and recovers the true cosmology when tested against independent simulations. Our primary parameters of interest are related to the growth rate of structure, f, and its degenerate combination fsigma_8. Using this emulator, we show that the constraining power on these parameters monotonically increases as smaller scales are included in the analysis, all the way down to 0.1 h^{-1} Mpc. For a BOSS-like survey, the constraints on fsigma_8 from r<30 h^{-1} Mpc scales alone are more than a factor of two tighter than those from the fiducial BOSS analysis of redshift-space clustering using perturbation theory at larger scales. The combination of real- and redshift-space clustering allows us to break the degeneracy between f and sigma_8, yielding a 9% constraint on f alone for a BOSS-like analysis. The current AEMULUS simulations limit this model to surveys of massive galaxies. Future simulations will allow this framework to be extended to all galaxy target types, including emission-line galaxies.

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The Aemulus Project II: Emulating the Halo Mass Function

Existing models for the dependence of the halo mass function on cosmological parameters will become a limiting source of systematic uncertainty for cluster cosmology in the near future. We present a halo mass function emulator and demonstrate improved accuracy relative to state-of-the-art analytic models. In this work, mass is defined using an overdensity criteria of 200 relative to the mean background density. Our emulator is constructed from the AEMULUS simulations, a suite of 40 N-body simulations with snapshots from z=3 to z=0. These simulations cover the flat wCDM parameter space allowed by recent Cosmic Microwave Background, Baryon Acoustic Oscillation and Type Ia Supernovae results, varying the parameters w, Omega_m, Omega_b, sigma_8, N_{eff}, n_s, and H_0. We validate our emulator using five realizations of seven different cosmologies, for a total of 35 test simulations. These test simulations were not used in constructing the emulator, and were run with fully independent initial conditions. We use our test simulations to characterize the modeling uncertainty of the emulator, and introduce a novel way of marginalizing over the associated systematic uncertainty. We confirm non-universality in our halo mass function emulator as a function of both cosmological parameters and redshift. Our emulator achieves better than 1% precision over much of the relevant parameter space, and we demonstrate that the systematic uncertainty in our emulator will remain a negligible source of error for cluster abundance studies through at least the LSST Year 1 data set.

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The Aemulus Project I: Numerical Simulations for Precision Cosmology

The rapidly growing statistical precision of galaxy surveys has lead to a need for ever-more precise predictions of the observables used to constrain cosmological and galaxy formation models. The primary avenue through which such predictions will be obtained is suites of numerical simulations. These simulations must span the relevant model parameter spaces, be large enough to obtain the precision demanded by upcoming data, and be thoroughly validated in order to ensure accuracy. In this paper we present one such suite of simulations, forming the basis for the AEMULUS Project, a collaboration devoted to precision emulation of galaxy survey observables. We have run a set of 75 (1.05 h^-1 Gpc)^3 simulations with mass resolution and force softening of 3.51\times 10^10 (Omega_m / 0.3) ~ h^-1 M_sun and 20 ~ h^-1 kpc respectively in 47 different wCDM cosmologies spanning the range of parameter space allowed by the combination of recent Cosmic Microwave Background, Baryon Acoustic Oscillation and Type Ia Supernovae results. We present convergence tests of several observables including spherical overdensity halo mass functions, galaxy projected correlation functions, galaxy clustering in redshift space, and matter and halo correlation functions and power spectra. We show that these statistics are converged to 1% (2%) for halos with more than 500 (200) particles respectively and scales of r>200 ~ h^-1 kpc in real space or k ~ 3 h Mpc^-1 in harmonic space for z\le 1. We find that the dominant source of uncertainty comes from varying the particle loading of the simulations. This leads to large systematic errors for statistics using halos with fewer than 200 particles and scales smaller than k ~ 4 h^-1 Mpc. We provide the halo catalogs and snapshots detailed in this work to the community at https://AemulusProject.github.io.

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The Concentration Dependence of the Galaxy-Halo Connection: Modeling Assembly Bias with Abundance Matching

Empirical methods for connecting galaxies to their dark matter halos have become essential for interpreting measurements of the spatial statistics of galaxies. In this work, we present a novel approach for parameterizing the degree of concentration dependence in the abundance matching method. This new parameterization provides a smooth interpolation between two commonly used matching proxies: the peak halo mass and the peak halo maximal circular velocity. This parameterization controls the amount of dependence of galaxy luminosity on halo concentration at a fixed halo mass. Effectively this interpolation scheme enables abundance matching models to have adjustable assembly bias in the resulting galaxy catalogs. With the new 400 Mpc/h DarkSky Simulation, whose larger volume provides lower sample variance, we further show that low-redshift two-point clustering and satellite fraction measurements from SDSS can already provide a joint constraint on this concentration dependence and the scatter within the abundance matching framework.

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Connecting Galaxies with Halos Across Cosmic Time: Stellar mass assembly distribution modeling of galaxy statistics

In this work, I explore an empirically motivated model for investigating the relationship between galaxy stellar masses, star formation rates and their halo masses and mass accretion histories. The core statistical quantity in this model is the stellar mass assembly distribution, $P(dM_{*}/dt|\mathbf{X},a)$, which specifies the probability density distribution of stellar mass assembly rates given a set of halo properties $\mathbf{X}$ and epoch $a$. Predictions from this model are obtained by integrating the stellar mass assembly distribution (SMAD) over halo merger trees, easily obtained from modern, high-resolution $N$-body simulations. Further properties of the galaxies hosted by the halos can be obtained by post-processing the stellar mass assembly histories with stellar population synthesis models. In my particular example implementation of this model, I use the \citet{behroozi13a} constraint on the median stellar mass assembly rates of halos as a function of their mass and redshift to construct an example parameterization of $P(dM_{*}/dt|\mathbf{X},a)$. This SMAD is then integrated over individual halo mass accretion histories from $N$-body merger trees starting at z = 4, using simple rules to account for merging halos. I find that this a simple model can reproduce qualitatively the bimodal features of the low-redshift galaxy population, including the qualitative split in the two-point clustering as a function of specific star formation rate. These results indicate that models which directly couple halo and galaxy growth through simple efficiency functions can naturally predict the star formation rate bimodality in higher-order statistics of the galaxy field, such as its two-point correlations or galactic conformity signals.

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Cosmic Discordance: Are Planck CMB and CFHTLenS weak lensing measurements out of tune?

We examine the level of agreement between low redshift weak lensing data and the CMB using measurements from the CFHTLenS and Planck+WMAP polarization. We perform an independent analysis of the CFHTLenS six bin tomography results of Heymans et al. (2013). We extend their systematics treatment and find the cosmological constraints to be relatively robust to the choice of non-linear modeling, extension to the intrinsic alignment model and inclusion of baryons. We find that the 90% confidence contours of CFHTLenS and Planck+WP do not overlap even in the full 6-dimensional parameter space of $Λ$CDM, so the two datasets are discrepant. Allowing a massive active neutrino or tensor modes does not significantly resolve the disagreement in the full n-dimensional parameter space. Our results differ from some in the literature because we use the full tomographic information in the weak lensing data and marginalize over systematics. We note that adding a sterile neutrino to $Λ$CDM does bring the 8-dimensional 64% contours to overlap, mainly due to the extra effective number of neutrino species, which we find to be 0.84 $\pm$ 0.35 (68%) greater than standard on combining the datasets. We discuss why this is not a completely satisfactory resolution, leaving open the possibility of other new physics or observational systematics as contributing factors. We provide updated cosmology fitting functions for the CFHTLenS constraints and discuss the differences from ones used in the literature.

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Fourier Band-Power E/B-mode Estimators for Cosmic Shear

We introduce new Fourier band-power estimators for cosmic shear data analysis and E/B-mode separation. We consider both the case where one performs E/B-mode separation and the case where one does not. The resulting estimators have several nice properties which make them ideal for cosmic shear data analysis. First, they can be written as linear combinations of the binned cosmic shear correlation functions. Second, they account for the survey window function in real-space. Third, they are unbiased by shape noise since they do not use correlation function data at zero separation. Fourth, the band-power window functions in Fourier space are compact and largely non-oscillatory. Fifth, they can be used to construct band-power estimators with very efficient data compression properties. In particular, we find that all of the information on the parameters $Ω_{m}$, $σ_{8}$ and $n_{s}$ in the shear correlation functions in the range of $\sim10-400$ arcminutes for single tomographic bin can be compressed into only three band-power estimates. Finally, we can achieve these rates of data compression while excluding small-scale information where the modeling of the shear correlation functions and power spectra is very difficult. Given these desirable properties, these estimators will be very useful for cosmic shear data analysis.

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Predicting Galaxy Star Formation Rates via the Co-evolution of Galaxies and Halos

In this paper, we test the age matching hypothesis that the star formation rate (SFR) of a galaxy of fixed stellar mass is determined by its dark matter halo formation history, and as such, that more quiescent galaxies reside in older halos. This simple model has been remarkably successful at predicting color-based galaxy statistics at low redshift as measured in the Sloan Digital Sky Survey (SDSS). To further test this method with observations, we present new SDSS measurements of the galaxy two-point correlation function and galaxy-galaxy lensing as a function of stellar mass and SFR, separated into quenched and star-forming galaxy samples. We find that our age matching model is in excellent agreement with these new measurements. We also employ a galaxy group finder and show that our model is able to predict: (1) the relative SFRs of central and satellite galaxies, (2) the SFR-dependence of the radial distribution of satellite galaxy populations within galaxy groups, rich groups, and clusters and their surrounding larger scale environments, and (3) the interesting feature that the satellite quenched fraction as a function of projected radial distance from the central galaxy exhibits an ~ r^-.15 slope, independent of environment. The accurate prediction for the spatial distribution of satellites is intriguing given the fact that we do not explicitly model satellite-specific processes after infall, and that in our model the virial radius does not mark a special transition region in the evolution of a satellite, contrary to most galaxy evolution models. The success of the model suggests that present-day galaxy SFR is strongly correlated with halo mass assembly history.

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The Dark Side of Galaxy Color: evidence from new SDSS measurements of galaxy clustering and lensing

The age matching model has recently been shown to predict correctly the luminosity L and g-r color of galaxies residing within dark matter halos. The central tenet of the model is intuitive: older halos tend to host galaxies with older stellar populations. In this paper, we demonstrate that age matching also correctly predicts the g-r color trends exhibited in a wide variety of statistics of the galaxy distribution for stellar mass M* threshold samples. In particular, we present new measurements of the galaxy two-point correlation function and the galaxy-galaxy lensing signal as a function of M* and g-r color from the Sloan Digital Sky Survey, and show that age matching exhibits remarkable agreement with these and other statistics of low-redshift galaxies. In so doing, we also demonstrate good agreement between the galaxy-galaxy lensing observed by SDSS and the signal predicted by abundance matching, a new success of this model. We describe how age matching is a specific example of a larger class of Conditional Abundance Matching models (CAM), a theoretical framework we introduce here for the first time. CAM provides a general formalism to study correlations at fixed mass between any galaxy property and any halo property. The striking success of our simple implementation of CAM provides compelling evidence that this technique has the potential to describe the same set of data as alternative models, but with a dramatic reduction in the required number of parameters. CAM achieves this reduction by exploiting the capability of contemporary N-body simulations to determine dark matter halo properties other than mass alone, which distinguishes our model from conventional approaches to the galaxy-halo connection.

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A High Throughput Workflow Environment for Cosmological Simulations

The next generation of wide-area sky surveys offer the power to place extremely precise constraints on cosmological parameters and to test the source of cosmic acceleration. These observational programs will employ multiple techniques based on a variety of statistical signatures of galaxies and large-scale structure. These techniques have sources of systematic error that need to be understood at the percent-level in order to fully leverage the power of next-generation catalogs. Simulations of large-scale structure provide the means to characterize these uncertainties. We are using XSEDE resources to produce multiple synthetic sky surveys of galaxies and large-scale structure in support of science analysis for the Dark Energy Survey. In order to scale up our production to the level of fifty 10^10-particle simulations, we are working to embed production control within the Apache Airavata workflow environment. We explain our methods and report how the workflow has reduced production time by 40% compared to manual management.

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CALCLENS: Weak Lensing Simulations for Large-area Sky Surveys and Second-order Effects in Cosmic Shear Power Spectra

I present a new algorithm, CALCLENS, for efficiently computing weak gravitational lensing shear signals from large N-body light cone simulations over a curved sky. This new algorithm properly accounts for the sky curvature and boundary conditions, is able to produce redshift-dependent shear signals including corrections to the Born approximation by using multiple-plane ray tracing, and properly computes the lensed images of source galaxies in the light cone. The key feature of this algorithm is a new, computationally efficient Poisson solver for the sphere that combines spherical harmonic transform and multgrid methods. As a result, large areas of sky (~10, 000 square degrees) can be ray traced efficiently at high-resolution using only a few hundred cores on widely available machines. Using this new algorithm and curved-sky calculations that only use a slower but more accurate spherical harmonic transform Poisson solver, I study the shear B-mode and rotation mode power spectra. Employing full-sky E/B-mode decompositions, I confirm that the shear B-mode and rotation mode power spectra are equal at high accuracy (~1%), as expected from perturbation theory up to second order. Coupled with realistic galaxy populations placed in large N-body light cone simulations, this new algorithm is ideally suited for the construction of synthetic weak lensing shear catalogs to be used to test for systematic effects in data analysis procedures for upcoming large-area sky surveys. The implementation presented in this work, written in C and employing widely available software libraries to maintain portability, is publicly available at http://code.google.com/p/calclens.

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Cosmic Shear E/B-mode Estimation with Binned Correlation Function Data

In this work I study the problem of E/B-mode separation with binned cosmic shear two-point correlation function data. Motivated by previous work on E/B-mode separation with shear two-point correlation functions and the practical considerations of data analysis, I consider E/B-mode estimators which are linear combinations of the binned shear correlation function data points. I demonstrate that these estimators mix E- and B-modes generally. I then show how to define estimators which minimize this E/B-mode mixing and give practical recipes for their construction and use. Using these optimal estimators, I demonstrate that the vector space composed of the binned shear correlation function data points can be decomposed into approximately ambiguous, E- and B-mode subspaces. With simple Fisher information estimates, I show that a non-trivial amount of information on typical cosmological parameters is contained in the ambiguous mode subspace computed in this formalism. Next, I give two examples which apply these practical estimators and recipes to generic problems in cosmic shear data analysis: data compression and spatially locating B-mode contamination. In particular, by using wavelet-like estimators with the shear correlation functions directly, one can pinpoint B-mode contamination to specific angular scales and extract information on its shape. Finally, I discuss how these estimators can be used as part of blinded or closed-box cosmic shear data analyses in order to assess and find B-mode contamination at high-precision while avoiding observer biases.

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Cosmological Constraints from the Large Scale Weak Lensing of SDSS MaxBCG Clusters

We derive constraints on the matter density \Om and the amplitude of matter clustering \sig8 from measurements of large scale weak lensing (projected separation R=5-30\hmpc) by clusters in the Sloan Digital Sky Survey MaxBCG catalog. The weak lensing signal is proportional to the product of \Om and the cluster-mass correlation function \xicm. With the relation between optical richness and cluster mass constrained by the observed cluster number counts, the predicted lensing signal increases with increasing \Om or \sig8, with mild additional dependence on the assumed scatter between richness and mass. The dependence of the signal on scale and richness partly breaks the degeneracies among these parameters. We incorporate external priors on the richness-mass scatter from comparisons to X-ray data and on the shape of the matter power spectrum from galaxy clustering, and we test our adopted model for \xicm against N-body simulations. Using a Bayesian approach with minimal restrictive priors, we find \sig8(\Om/0.325)^{0.501}=0.828 +/- 0.049, with marginalized constraints of \Om=0.325_{-0.067}^{+0.086} and \sig8=0.828_{-0.097}^{+0.111}, consistent with constraints from other MaxBCG studies that use weak lensing measurements on small scales (R<=2\hmpc). The (\Om,\sig8) constraint is consistent with and orthogonal to the one inferred from WMAP CMB data, reflecting agreement with the structure growth predicted by GR for an LCDM cosmological model. A joint constraint assuming LCDM yields \Om=0.298 +/- 0.020 and \sig8=0.831 +/- 0.020. Our cosmological parameter errors are dominated by the statistical uncertainties of the large scale weak lensing measurements, which should shrink sharply with current and future imaging surveys.

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On the Accuracy of Weak Lensing Cluster Mass Reconstructions

We study the bias and scatter in mass measurements of galaxy clusters resulting from fitting a spherically-symmetric Navarro, Frenk & White model to the reduced tangential shear profile measured in weak lensing observations. The reduced shear profiles are generated for ~10^4 cluster-sized halos formed in a LCDM cosmological N-body simulation of a 1 Gpc/h box. In agreement with previous studies, we find that the scatter in the weak lensing masses derived using this fitting method has irreducible contributions from the triaxial shapes of cluster-sized halos and uncorrelated large-scale matter projections along the line-of-sight. Additionally, we find that correlated large-scale structure within several virial radii of clusters contributes a smaller, but nevertheless significant, amount to the scatter. The intrinsic scatter due to these physical sources is ~20% for massive clusters, and can be as high as ~30% for group-sized systems. For current, ground-based observations, however, the total scatter should be dominated by shape noise from the background galaxies used to measure the shear. Importantly, we find that weak lensing mass measurements can have a small, ~5%-10%, but non-negligible amount of bias. Given that weak lensing measurements of cluster masses are a powerful way to calibrate cluster mass-observable relations for precision cosmological constraints, we strongly emphasize that a robust calibration of the bias requires detailed simulations which include more observational effects than we consider here. Such a calibration exercise needs to be carried out for each specific weak lensing mass estimation method, as the details of the method determine in part the expected scatter and bias. We present an iterative method for estimating mass M500c that can eliminate the bias for analyses of ground-based data.

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Cosmological Constraints from Galaxy Clustering and the Mass-to-Number Ratio of Galaxy Clusters

We place constraints on the average density (Omega_m) and clustering amplitude (sigma_8) of matter using a combination of two measurements from the Sloan Digital Sky Survey: the galaxy two-point correlation function, w_p, and the mass-to-galaxy-number ratio within galaxy clusters, M/N, analogous to cluster M/L ratios. Our w_p measurements are obtained from DR7 while the sample of clusters is the maxBCG sample, with cluster masses derived from weak gravitational lensing. We construct non-linear galaxy bias models using the Halo Occupation Distribution (HOD) to fit both w_p and M/N for different cosmological parameters. HOD models that match the same two-point clustering predict different numbers of galaxies in massive halos when Omega_m or sigma_8 is varied, thereby breaking the degeneracy between cosmology and bias. We demonstrate that this technique yields constraints that are consistent and competitive with current results from cluster abundance studies, even though this technique does not use abundance information. Using w_p and M/N alone, we find Omega_m^0.5*sigma_8=0.465+/-0.026, with individual constraints of Omega_m=0.29+/-0.03 and sigma_8=0.85+/-0.06. Combined with current CMB data, these constraints are Omega_m=0.290+/-0.016 and sigma_8=0.826+/-0.020. All errors are 1-sigma. The systematic uncertainties that the M/N technique are most sensitive to are the amplitude of the bias function of dark matter halos and the possibility of redshift evolution between the SDSS Main sample and the maxBCG sample. Our derived constraints are insensitive to the current level of uncertainties in the halo mass function and in the mass-richness relation of clusters and its scatter, making the M/N technique complementary to cluster abundances as a method for constraining cosmology with future galaxy surveys.

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