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Enrique Gaztañaga

Publications and source records attributed to Enrique Gaztañaga.

102 records · Page 6Linked to original sources

Close galaxy pairs with accurate photometric redshifts

Context. Studies of galaxy pairs can provide valuable information to jointly understand the formation and evolution of galaxies and galaxy groups. Consequently, taking into account the new high precision photo-z surveys, it is important to have reliable and tested methods that allow us to properly identify these systems and estimate their total masses and other properties. Aims. In view of the forthcoming Physics of the Accelerating Universe Survey (PAUS) we propose and evaluate the performance of an identification algorithm of projected close isolated galaxy pairs. We expect that the photometric selected systems can adequately reproduce the observational properties and the inferred lensing mass - luminosity relation of a pair of truly bound galaxies that are hosted by the same dark matter halo. Methods. We develop an identification algorithm that considers the projected distance between the galaxies, the projected velocity difference and an isolation criteria in order to restrict the sample to isolated systems. We apply our identification algorithm using a mock galaxy catalog that mimics the features of PAUS. To evaluate the feasibility of our pair finder, we compare the identified photometric samples with a test sample that considers that both members are included in the same halo. Also, taking advantage of the lensing properties provided by the mock catalog, we apply a weak lensing analysis to determine the mass of the selected systems. Results. Photometric selected samples tend to show high purity values, but tend to misidentify truly bounded pairs as the photometric redshift errors increase. Nevertheless, overall properties such as the luminosity and mass distributions are successfully reproduced. We also accurately reproduce the lensing mass - luminosity relation as expected for galaxy pairs located in the same halo.

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Redshift inference from the combination of galaxy colors and clustering in a hierarchical Bayesian model $-$ Application to realistic $N$-body simulations

Photometric galaxy surveys constitute a powerful cosmological probe but rely on the accurate characterization of their redshift distributions using only broadband imaging, and can be very sensitive to incomplete or biased priors used for redshift calibration. Sánchez & Bernstein (2019) presented a hierarchical Bayesian model which estimates those from the robust combination of prior information, photometry of single galaxies and the information contained in the galaxy clustering against a well-characterized tracer population. In this work, we extend the method so that it can be applied to real data, developing some necessary new extensions to it, especially in the treatment of galaxy clustering information, and we test it on realistic simulations. After marginalizing over the mapping between the clustering estimator and the actual density distribution of the sample galaxies, and using prior information from a small patch of the survey, we find the incorporation of clustering information with photo-$z$'s to tighten the redshift posteriors, and to overcome biases in the prior that mimic those happening in spectroscopic samples. The method presented here uses all the information at hand to reduce prior biases and incompleteness. Even in cases where we artificially bias the spectroscopic sample to induce a shift in mean redshift of $Δ\bar z \approx 0.05,$ the final biases in the posterior are $Δ\bar z \lesssim0.003.$ This robustness to flaws in the redshift prior or training samples would constitute a milestone for the control of redshift systematic uncertainties in future weak lensing analyses.

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nIFTy Cosmology: the clustering consistency of galaxy formation models

We present a clustering comparison of 12 galaxy formation models (including Semi-Analytic Models (SAMs) and Halo Occupation Distribution (HOD) models) all run on halo catalogues and merger trees extracted from a single ΛCDM N-body simulation. We compare the results of the measurements of the mean halo occupation numbers, the radial distribution of galaxies in haloes and the 2-Point Correlation Functions (2PCF). We also study the implications of the different treatments of orphan (galaxies not assigned to any dark matter subhalo) and non-orphan galaxies in these measurements. Our main result is that the galaxy formation models generally agree in their clustering predictions but they disagree significantly between HOD and SAMs for the orphan satellites. Although there is a very good agreement between the models on the 2PCF of central galaxies, the scatter between the models when orphan satellites are included can be larger than a factor of 2 for scales smaller than 1 Mpc/h. We also show that galaxy formation models that do not include orphan satellite galaxies have a significantly lower 2PCF on small scales, consistent with previous studies. Finally, we show that the 2PCF of orphan satellites is remarkably different between SAMs and HOD models. Orphan satellites in SAMs present a higher clustering than in HOD models because they tend to occupy more massive haloes. We conclude that orphan satellites have an important role on galaxy clustering and they are the main cause of the differences in the clustering between HOD models and SAMs.

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What determines large scale galaxy clustering: halo mass or local density?

Using dark matter simulations we show how halo bias is determined by local density and not by halo mass. This is not totally surprising, as according to the peak-background split model, local density is the property that constraints bias at large scales. Massive haloes have a high clustering because they reside in high density regions. Small haloes can be found in a wide range of environments which determine their clustering amplitudes differently. This contradicts the assumption of standard Halo Occupation Distribution (HOD) models that the bias and occupation of haloes is determined solely by their mass. We show that the bias of central galaxies from semi-analytic models of galaxy formation as a function of luminosity and colour is not correctly predicted by the standard HOD model. Using local density instead of halo mass the HOD model correctly predicts galaxy bias. These results indicate the need to include information about local density and not only mass in order to correctly apply HOD analysis in these galaxy samples. This new model can be readily applied to observations and has the advantage that the galaxy density can be directly observed, in contrast with the dark matter halo mass.

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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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Non-local bias contribution to third-order galaxy correlations

We study halo clustering bias with second- and third-order statistics of halo and matter density fields in the MICE Grand Challenge simulation. We verify that two-point correlations deliver reliable estimates of the linear bias parameters at large scales, while estimations from the variance can be significantly affected by non-linear and possibly non-local contributions to the bias function. Combining three-point auto- and cross-correlations we find, for the first time in configuration space, evidence for the presence of such non-local contributions. These contributions are consistent with predicted second-order non-local effects on the bias functions originating from the dark matter tidal field. Samples of massive haloes show indications of bias (local or non-local) beyond second order. Ignoring non-local bias causes $20-30$\% and $5-10$\% overestimation of the linear bias from three-point auto- and cross-correlations respectively. We study two third-order bias estimators which are not affected by second-order non-local contributions. One is a combination of three-point auto- and cross- correlation. The other is a combination of third-order one- and two-point cumulants. Both methods deliver accurate bias estimations of the linear bias. Furthermore their estimations of second-order bias agree mutually. Ignoring non-local bias causes higher values of the second-order bias from three-point correlations. Our results demonstrate that third-order statistics can be employed for breaking the growth-bias degeneracy.

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Precise photometric redshifts with a narrow-band filter set: The PAU Survey at the William Herschel Telescope

The Physics of the Accelerating Universe (PAU) survey at the William Herschel Telescope (WHT) will use a new optical camera (PAUCam) with a large set of narrow-band filters to perform a photometric galaxy survey with a quasi-spectroscopic redshift precision of σ(z)/(1 + z) ~ 0.0035 and map the large-scale structure of the universe in three dimensions up to i_AB < 22.5-23.0. In this paper we present a detailed photo-z performance study using photometric simulations for 40 equally-spaced 12.5-nm-wide (FWHM) filters with a ~25% overlap and spanning the wavelength range from 450 nm to 850 nm, together with a ugrizY broad-band filter system. We then present the migration matrix r_ij, containing the probability that a galaxy in a true redshift bin j is measured in a photo-z bin i, and study its effect on the determination of galaxy auto- and cross-correlations. Finally, we also study the impact on the photo-z performance of small variations of the filter set in terms of width, wavelength coverage, etc., and find a broad region where slightly modified filter sets provide similar results, with the original set being close to optimal.

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Magnification of Photometric LRGs by Foreground LRGs and Clusters in SDSS

The magnification effect of gravitational lensing is a powerful probe of the distribution of matter in the universe, yet it is frequently overlooked due to the fact that its signal to noise is smaller than that of lensing shear. Because its systematic errors are quite different from those of shear, magnification is nevertheless an important approach with which to study the distribution of large scale structure. We present lensing mass profiles of spectroscopic luminous red galaxies (LRGs) and galaxy clusters determined through measurements of the weak lensing magnification of photometric LRGs in their background. We measure the change in detected galaxy counts as well as the increased average galaxy flux behind the lenses. In addition, we examine the average change in source color due to extinction by dust in the lenses. By simultaneously fitting these three probes we constrain the mass profiles and dust-to-mass ratios of the lenses in six bins of lens richness. For each richness bin we fit an NFW halo mass, brightest cluster galaxy (BCG) mass, second halo term, and dust-to-mass ratio. The resulting mass-richness relation is consistent with previous analyses of the catalogs, and limits on the dust-to-mass ratio in the lenses are in agreement with expectations. We explore the effects of including the (low signal-to-noise) flux magnification and reddening measurements in the analysis compared to using only the counts magnification data; the additional probes significantly improve the agreement between our measured mass-richness relation and previous results.

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Photo-z Quality Cuts and their Effect on the Measured Galaxy Clustering

Photometric galaxy surveys are an essential tool to further our understanding of the large-scale structure of the universe, its matter and energy content and its evolution. These surveys necessitate the determination of the galaxy redshifts using photometric techniques (photo-z). Oftentimes, it is advantageous to remove from the galaxy sample those for which one suspects that the photo-z estimation might be unreliable. In this paper, we show that applying these photo-z quality cuts blindly can grossly bias the measured galaxy correlations within and across photometric redshift bins. We then extend the work of Ho et al. (2012) and Ross et al. (2011) to develop a simple and effective method to correct for this using the data themselves. Finally, we apply the method to the Mega-Z catalog, containing about a million luminous red galaxies in the redshift range 0.45 < z < 0.65. After splitting the sample into four Δz = 0.05 photo-z bins using the BPZ algorithm, we see how our corrections bring the measured galaxy auto- and cross-correlations into agreement with expectations. We then look for the BAO feature in the four bins, with and without applying the photo-z quality cuts, and find a broad agreement between the BAO scales extracted in both cases. Intriguingly, we observe a correlation between galaxy density and photo-z quality even before any photo-z quality cuts are applied. This may be due to uncorrected observational effects that result in correlated gradients across the sky of the galaxy density and the galaxy photo-z precision. Our correction procedure could also help to mitigate some of these systematic effects.

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Modeling the angular correlation function and its full covariance in Photometric Galaxy Surveys

Near future cosmology will see the advent of wide area photometric galaxy surveys, like the Dark Energy Survey (DES), that extent to high redshifts (z ~ 1 - 2) but with poor radial distance resolution. In such cases splitting the data into redshift bins and using the angular correlation function $w(θ)$, or the $C_{\ell}$ power spectrum, will become the standard approach to extract cosmological information or to study the nature of dark energy through the Baryon Acoustic Oscillations (BAO) probe. In this work we present a detailed model for $w(θ)$ at large scales as a function of redshift and bin width, including all relevant effects, namely nonlinear gravitational clustering, bias, redshift space distortions and photo-z uncertainties. We also present a model for the full covariance matrix characterizing the angular correlation measurements, that takes into account the same effects as for $w(θ)$ and also the possibility of a shot-noise component and partial sky coverage. Provided with a large volume N-body simulation from the MICE collaboration we built several ensembles of mock redshift bins with a sky coverage and depth typical of forthcoming photometric surveys. The model for the angular correlation and the one for the covariance matrix agree remarkably well with the mock measurements in all configurations. The prospects for a full shape analysis of $w(θ)$ at BAO scales in forthcoming photometric surveys such as DES are thus very encouraging.

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On the interpretation of clustering from the angular APM Galaxy Survey

We analyze the uncertainties in the amplitudes of the spatial correlation functions estimated from angular correlations in a sample from the APM Galaxy Survey, with $b_J=17-20$. We model the uncertainties in the selection function and in the evolution of clustering. In particular we estimate $σ_8^{APM}$, the rms galaxy number fluctuations in spheres of radius at $8 \Mpc$, from the measured angular variance in the APM. The uncertainty in $σ_8^{APM}$ has three main contributions: 8\% from sampling and selection function uncertainties, 7\% from the uncertainty in the evolution of clustering and 3\% from the uncertainty in the value of $Ω_0$. Including all these contributions, we find $σ_8^{APM}$ is in the range $0.78-1.08$. If the galaxy clustering in the APM evolves as expected from gravitational clustering of matter fluctuations, then $σ_8^{APM}=0.95 \pm 0.07$ ($1.00 \pm 0.08$) for $Ω_0 \simeq 1$ ($Ω_0 \simeq 0$), close to the values for nearby optical samples. On the other hand, if we assume that clustering evolution is fixed in comoving coordinates $σ_8^{APM}=0.83 \pm 0.05$ ($0.87 \pm 0.06$), closer to the results for nearby IRAS samples. The final uncertainty in the range of values for the hierarchical amplitudes $S_J\equiv \xibar_J/\xibar_2^{J-1}$ is typically twice the estimated sampling errors, with the highest values for the case of less clustering evolution. We compare our estimates with other results and discuss the implications for models of structure formation.

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Variance, Skewness & Kurtosis: results from the APM Cluster Redshift Survey and model predictions

We estimate the variance $\xibar_2$, the skewness $\xibar_3$ and the kurtosis $\xibar_4$ in the distribution of density fluctuations in a complete sample from the APM Cluster Redshift Survey with 339 clusters and a mean depth $ \sim 250\Mpc$. We are able to measure the statistics of fluctuations in spheres of radius $R \simeq 5-80 \Mpc$, with reasonable errorbars. The statistics in the cluster distribution follow the hierarchical pattern $\xibar_J=S_J~\xibar_2^{J-1}$ with $S_J$ roughly constant, $S_3 \simeq 2$ and $S_4 \sim 8$. We analyse the distribution of clusters taken from N-body simulations of different dark matter models. The results are compared with an alternative method of simulating clusters which uses the truncated Zel'dovich approximation. We argue that this alternative method is not reliable enough for making quantitative predictions of $\xibar$. The N-body simulation results follow similar hierarchical relations to the observations, with $S_J$ almost unaffected by redshift distortions from peculiar motions. The standard $Ω=1$ Cold Dark Matter (CDM) model is inconsistent with either the second, third or fourth order statistics at all scales. However both a hybrid Mixed Dark Matter model and a low density CDM variant agree with the $\xibar_J$ observations.

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