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Eduardo Rozo

Publications and source records attributed to Eduardo Rozo.

At least 73 records · Page 4Linked to original sources

The Halo Boundary of Galaxy Clusters in the SDSS

Mass around dark matter halos can be divided into "infalling" material and "collapsed" material that has passed through at least one pericenter. Analytical models and simulations predict a rapid drop in the halo density profile associated with the transition between these two regimes. Using data from SDSS, we explore the evidence for such a feature in the density profiles of galaxy clusters and investigate the connection between this feature and a possible phase space boundary. We first estimate the steepening of the outer galaxy density profile around clusters: the profiles show an abrupt steepening, providing evidence for truncation of the halo profile. Next, we measure the galaxy density profile around clusters using two sets of galaxies selected based on color. We find evidence of an abrupt change in the galaxy colors that coincides with the location of the steepening of the density profile. Since galaxies are likely to be quenched of star formation and turn red inside of clusters, this change in the galaxy color distribution can be interpreted as the transition from an infalling regime to a collapsed regime. We also measure this transition using a model comparison approach which has been used recently in studies of the "splashback" phenomenon, but find that this approach is not a robust way to quantify the significance of detecting a splashback-like feature. Finally, we perform measurements using an independent cluster catalog to test for potential systematic errors associated with cluster selection. We identify several avenues for future work: improved understanding of the small-scale galaxy profile, lensing measurements, identification of proxies for the halo accretion rate, and other tests. With upcoming data from the DES, KiDS and HSC surveys, we can expect significant improvements in the study of halo boundaries.

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SPIDERS: the spectroscopic follow-up of X-ray selected clusters of galaxies in SDSS-IV

SPIDERS (The SPectroscopic IDentification of eROSITA Sources) is a program dedicated to the homogeneous and complete spectroscopic follow-up of X-ray AGN and galaxy clusters over a large area ($\sim$7500 deg$^2$) of the extragalactic sky. SPIDERS is part of the SDSS-IV project, together with the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) and the Time-Domain Spectroscopic Survey (TDSS). This paper describes the largest project within SPIDERS before the launch of eROSITA: an optical spectroscopic survey of X-ray selected, massive ($\sim 10^{14}$ to $10^{15}~M_{\odot}$) galaxy clusters discovered in ROSAT and XMM-Newton imaging. The immediate aim is to determine precise ($Δ_z \sim 0.001$) redshifts for 4,000-5,000 of these systems out to $z \sim 0.6$. The scientific goal of the program is precision cosmology, using clusters as probes of large-scale structure in the expanding Universe. We present the cluster samples, target selection algorithms and observation strategies. We demonstrate the efficiency of selecting targets using a combination of SDSS imaging data, a robust red-sequence finder and a dedicated prioritization scheme. We describe a set of algorithms and work-flow developed to collate spectra and assign cluster membership, and to deliver catalogues of spectroscopically confirmed clusters. We discuss the relevance of line-of-sight velocity dispersion estimators for the richer systems. We illustrate our techniques by constructing a catalogue of 230 spectroscopically validated clusters ($0.031 < z < 0.658$), found in pilot observations. We discuss two potential science applications of the SPIDERS sample: the study of the X-ray luminosity-velocity dispersion ($L_X-σ$) relation and the building of stacked phase-space diagrams.

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Intrinsic alignments in redMaPPer clusters -- I. Central galaxy alignments and angular segregation of satellites

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94817 members within 0.1<z<0.35, based on the redMaPPer cluster catalog constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes and the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centering probability, and redder color. Satellites with redder color, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation toward their central galaxy major axes. Finally, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.

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Tidal stripping as a test of satellite quenching in redMaPPer clusters

When dark matter halos are accreted by massive host clusters, strong gravitational tidal forces begin stripping mass from the accreted subhalos. This stripping eventually removes all mass beyond a subhalo's tidal radius, but the unbound mass remains in the vicinity of the satellite for at least a dynamical time t_dyn. The N-body subhalo study of Chamberlain et al. verified this picture and pointed out a useful observational consequence: measurements of subhalo correlations beyond the tidal radius are sensitive to the infall time, t_infall, of the subhalo onto its host. We perform this cross-correlation measurement using ~ 160,000 red satellite galaxies in SDSS redMaPPer clusters and find evidence that subhalo correlations do persist well beyond the tidal radius, suggesting that many of the observed satellites fell into their current host less than a dynamical time ago, t_infall < t_dyn. Combined with estimated dynamical times t_dyn ~ 3-5 Gyr and SED fitting results for the time at which satellites stopped forming stars, t_quench ~ 6 Gyr, we infer that for a significant fraction of the satellites, star formation quenched before those satellites entered their current hosts. The result holds for red satellites over a large range of cluster-centric distances 0.1 - 0.6 Mpc/h. We discuss the implications of this result for models of galaxy formation.

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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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Constraining the Mass-Richness Relationship of redMaPPer Clusters with Angular Clustering

The potential of using cluster clustering for calibrating the mass-observable relation of galaxy clusters has been recognized theoretically for over a decade. Here, we demonstrate the feasibility of this technique to achieve high precision mass calibration using redMaPPer clusters in the Sloan Digital Sky Survey North Galactic Cap. By including cross-correlations between several richness bins in our analysis we significantly improve the statistical precision of our mass constraints. The amplitude of the mass-richness relation is constrained to 7% statistical precision. However, the error budget is systematics dominated, reaching an 18% total error that is dominated by theoretical uncertainty in the bias-mass relation for dark matter halos. We perform a detailed treatment of the effects of assembly bias on our analysis, finding that the contribution of such effects to our parameter uncertainties is somewhat greater than that of measurement noise. We confirm the results from Miyatake et al. (2015) that the clustering amplitude of redMaPPer clusters depends on galaxy concentration, and provide additional evidence in support of this effect being due to some form of assembly bias. The results presented here demonstrate the power of cluster clustering for mass calibration and cosmology provided the current theoretical systematics can be ameliorated.

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Measuring subhalo mass in redMaPPer clusters with CFHT Stripe 82 Survey

We use the shear catalog from the CFHT Stripe-82 Survey to measure the subhalo masses of satellite galaxies in redMaPPer clusters. Assuming a Chabrier Initial Mass Function (IMF) and a truncated NFW model for the subhalo mass distribution, we find that the sub-halo mass to galaxy stellar mass ratio increases as a function of projected halo-centric radius $r_p$, from $M_{\rm sub}/M_{\rm star}=4.43^{+ 6.63}_{- 2.23}$ at $r_p \in [0.1,0.3]$ $h^{-1}Mpc$ to $M_{\rm sub}/M_{\rm star}=75.40^{+ 19.73}_{- 19.09}$ at $r_p \in [0.6,0.9]$ $h^{-1}Mpc$. We also investigate the dependence of subhalo masses on stellar mass by splitting satellite galaxies into two stellar mass bins: $10<\log(M_{\rm star}/M_{\rm sun})<10.5$ and $11<\log(M_{\rm star}/M_{\rm sun})<12$. The best-fit subhalo mass of the more massive satellite galaxy bin is larger than that of the less massive satellites: $\log(M_{\rm sub}/M_{\rm sun})=11.14 ^{+ 0.66 }_{- 0.73}$ ($M_{\rm sub}/M_{\rm star}=19.5^{+19.8}_{-17.9}$) versus $\log(M_{\rm sub}/M_{\rm sun})=12.38 ^{+ 0.16 }_{- 0.16}$ ($M_{\rm sub}/M_{\rm star}=21.1^{+7.4}_{-7.7}$).

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Evidence of Halo Assembly Bias in Massive Clusters

We present significant evidence of halo assembly bias for SDSS redMaPPer galaxy clusters in the redshift range $[0.1, 0.33]$. By dividing the 8,648 clusters into two subsamples based on the average member galaxy separation from the cluster center, we first show that the two subsamples have very similar halo mass of $M_{\rm 200m}\simeq 1.9\times 10^{14}~h^{-1}M_\odot$ based on the weak lensing signals at small radii $R<\sim 10~h^{-1}{\rm Mpc}$. However, their halo bias inferred from both the large-scale weak lensing and the projected auto-correlation functions differs by a factor of $\sim$1.5, which is a signature of assembly bias. The same bias hypothesis for the two subsamples is excluded at 2.5$σ$ in the weak lensing and 4.4$σ$ in the auto-correlation data, respectively. This result could bring a significant impact on both galaxy evolution and precision cosmology.

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Detection of the Splashback Radius and Halo Assembly bias of Massive Galaxy Clusters

We show that the projected number density profiles of SDSS photometric galaxies around galaxy clusters displays strong evidence for the splashback radius, a sharp halo edge corresponding to the location of the first orbital apocenter of satellite galaxies after their infall. We split the clusters into two subsamples with different mean projected radial distances of their members, $\langle R_{\rm mem}\rangle$, at fixed richness and redshift, and show that the sample with smaller $\langle R_{\rm mem}\rangle$ has a smaller ratio of the splashback radius to the traditional halo boundary $R_{\rm 200m}$, than the subsample with larger $\langle R_{\rm mem}\rangle$, indicative of different mass accretion rates for the two subsamples. The same cluster samples were recently used by Miyatake et al. to show that their large-scale clustering differs despite their similar weak lensing masses, demonstrating strong evidence for halo assembly bias. We expand on this result by presenting a 6.6-$σ$ detection of halo assembly bias using the cluster-photometric galaxy cross-correlations. Our measured splashback radii are smaller, while the strength of the assembly bias signal is stronger, than expectations from N-body simulations based on the $Λ$-dominated, cold dark matter structure formation model. Dynamical friction or cluster-finding systematics such as miscentering or projection effects are not likely to be the sole source of these discrepancies.

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Galaxy Cluster Mass Estimation from Stacked Spectroscopic Analysis

We use simulated galaxy surveys to study: i) how galaxy membership in redMaPPer clusters maps to the underlying halo population, and ii) the accuracy of a mean dynamical cluster mass, $M_σ(λ)$, derived from stacked pairwise spectroscopy of clusters with richness $λ$. Using $\sim\! 130,000$ galaxy pairs patterned after the SDSS redMaPPer cluster sample study of Rozo et al. (2015 RMIV), we show that the pairwise velocity PDF of central--satellite pairs with $m_i < 19$ in the simulation matches the form seen in RMIV. Through joint membership matching, we deconstruct the main Gaussian velocity component into its halo contributions, finding that the top-ranked halo contributes $\sim 60\%$ of the stacked signal. The halo mass scale inferred by applying the virial scaling of Evrard et al. (2008) to the velocity normalization matches, to within a few percent, the log-mean halo mass derived through galaxy membership matching. We apply this approach, along with mis-centering and galaxy velocity bias corrections, to estimate the log-mean matched halo mass at $z=0.2$ of SDSS redMaPPer clusters. Employing the velocity bias constraints of Guo et al. (2015), we find $\langle \ln(M_{200c})|λ\rangle = \ln(M_{30}) + α_m \ln(λ/30)$ with $M_{30} = 1.56 \pm 0.35 \times 10^{14} M_\odot$ and $α_m = 1.31 \pm 0.06_{stat} \pm 0.13_{sys}$. Systematic uncertainty in the velocity bias of satellite galaxies overwhelmingly dominates the error budget.

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Luminous Red Galaxies in Clusters: Central Occupation, Spatial Distributions, and Mis-centering

Luminous Red Galaxies (LRG) from the Sloan Digital Sky Survey are considered among the best understood samples of galaxies, and they are employed in a broad range of cosmological studies. Because they form a relatively homogeneous population, with high stellar masses and red colors, they are expected to occupy halos in a relatively simple way. In this paper, we study how LRGs occupy massive halos via direct counts in clusters and we reveal several unexpected trends suggesting that the connection between LRGs and dark matter halos may not be straightforward. Using the redMaPPer cluster catalog, we derive the central occupation of LRGs as a function richness, Ncen(λ). Assuming no correlation between cluster mass and central galaxy luminosity at fixed richness, we show that clusters contain a significantly lower fraction of central LRGs than predicted from the two-point correlation function. At halo masses of 10^14.5 Msun, we find Ncen=0.73, compared to Ncen of 0.89 from correlation studies. Our central occupation function for LRGs converges to 0.95 at large halo masses. A strong anti-correlation between central luminosity and cluster mass at fixed richness is required to reconcile our results with those based on clustering studies. We also derive P_BNC, the probability that the brightest cluster member is not the central galaxy. We find P_BNC ~ 20-30% which is a factor of ~2 lower than the value found by Skibba et al. 2011. Finally, we study the radial offsets of bright non-central LRGs from cluster centers and show that bright non-central LRGs follow a different radial distribution compared to red cluster members, which follow a Navarro-Frank-White profile. This work demonstrates that even the most massive clusters do not always have an LRG at the center, and that the brightest galaxy in a cluster is not always the central galaxy.

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Environment-based selection effects of Planck clusters

We investigate whether the large scale structure environment of galaxy clusters imprints a selection bias on Sunyaev Zel'dovich (SZ) catalogs. Such a selection effect might be caused by line of sight (LoS) structures that add to the SZ signal or contain point sources that disturb the signal extraction in the SZ survey. We use the Planck PSZ1 union catalog (Planck Collab- oration et al. 2013a) in the SDSS region as our sample of SZ selected clusters. We calculate the angular two-point correlation function (2pcf) for physically correlated, foreground and background structure in the RedMaPPer SDSS DR8 catalog with respect to each cluster. We compare our results with an optically selected comparison cluster sample and with theoretical predictions. In contrast to the hypothesis of no environment-based selection, we find a mean 2pcf for background structures of -0.049 on scales of $\lesssim 40'$, significantly non-zero at $\sim 4 σ$, which means that Planck clusters are more likely to be detected in regions of low background density. We hypothesize this effect arises either from background estimation in the SZ survey or from radio sources in the background. We estimate the defect in SZ signal caused by this effect to be negligibly small, of the order of $\sim 10^{-4}$ of the signal of a typical Planck detection. Analogously, there are no implications on X-ray mass measurements. However, the environ- mental dependence has important consequences for weak lensing follow up of Planck galaxy clusters: we predict that projection effects account for half of the mass contained within a 15' radius of Planck galaxy clusters. We did not detect a background underdensity of CMASS LRGs, which also leaves a spatially varying redshift dependence of the Planck SZ selection function as a possible cause for our findings.

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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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redMaPPer IV: Photometric Membership Identification of Cluster Galaxies with 1% Precision

In order to study the galaxy population of galaxy clusters with photometric data one must be able to accurately discriminate between cluster members and non-members. The redMaPPer cluster finding algorithm treats this problem probabilistically. Here, we utilize SDSS and GAMA spectroscopic membership rates to validate the redMaPPer membership probability estimates for clusters with $z\in[0.1,0.3]$. We find small - but correctable - biases, sourced by three different systematics. The first two were expected a priori, namely blue cluster galaxies and correlated structure along the line of sight. The third systematic is new: the redMaPPer template fitting exhibits a non-trivial dependence on photometric noise, which biases the original redMaPPer probabilities when utilizing noisy data. After correcting for these effects, we find exquisite agreement ($\approx 1\%$) between the photometric probability estimates and the spectroscopic membership rates, demonstrating that we can robustly recover cluster membership estimates from photometric data alone. As a byproduct of our analysis we find that on average unavoidable projection effects from correlated structure contribute $\approx 6\%$ of the richness of a redMaPPer galaxy cluster. This work also marks the second public release of the SDSS redMaPPer cluster catalog.

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The X-CLASS - redMaPPer galaxy cluster comparison: I. Identification procedures

We performed a detailed and, for a large part interactive, analysis of the matching output between the X-CLASS and redMaPPer cluster catalogues. The overlap between the two catalogues has been accurately determined and possible cluster positional errors were manually recovered. The final samples comprise 270 and 355 redMaPPer and X-CLASS clusters respectively. X-ray cluster matching rates were analysed as a function of optical richness. In a second step, the redMaPPer clusters were correlated with the entire X-ray catalogue, containing point and uncharacterised sources (down to a few 10^{-15} erg s^{-1} cm^{-2} in the [0.5-2] keV band). A stacking analysis was performed for the remaining undetected optical clusters. Main results show that neither of the wavebands misses any massive cluster (as coded by X-ray luminosity or optical richness). After correcting for obvious pipeline short-comings (about 10% of the cases both in optical and X-ray), ~50% of the redMaPPer (down to a richness of 20) are found to coincide with an X-CLASS cluster; when considering X-ray sources of any type, this fraction increases to ~ 80%; for the remaining objects, the stacking analysis finds a weak signal within 0.5 Mpc around the cluster optical centers. The fraction of clusters totally dominated by AGN-type emission appears to be of the order of a few percent. Conversely ~ 40% of the X-CLASS clusters are identified with a redMaPPer (down to a richness of 20) - part of the non-matches being due to the fact that the X-CLASS sample extends further out than redMaPPer (z<1 vs z<0.6); extending the correlation down to a richness of 5, raises the matching rate to ~ 65%.

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Orientation Bias of Optically Selected Galaxy Clusters and Its Impact on Stacked Weak Lensing Analyses

Weak-lensing measurements of the averaged shear profiles of galaxy clusters binned by some proxy for cluster mass are commonly converted to cluster mass estimates under the assumption that these cluster stacks have spherical symmetry. In this paper we test whether this assumption holds for optically selected clusters binned by estimated optical richness. Using mock catalogues created from N-body simulations populated realistically with galaxies, we ran a suite of optical cluster finders and estimated their optical richness. We binned galaxy clusters by true cluster mass and estimated optical richness and measure the ellipticity of these stacks. We find that the processes of optical cluster selection and richness estimation are biased, leading to stacked structures that are elongated along the line-of-sight. We show that weak-lensing alone cannot measure the size of this orientation bias. Weak lensing masses of stacked optically selected clusters are overestimated by up to 3-6 per cent when clusters can be uniquely associated with haloes. This effect is large enough to lead to significant biases in the cosmological parameters derived from large surveys like the Dark Energy Survey, if not calibrated via simulations or fitted simultaneously. This bias probably also contributes to the observed discrepancy between the observed and predicted Sunyaev-Zel'dovich signal of optically-selected clusters.

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redMaPPer III: A Detailed Comparison of the Planck 2013 and SDSS DR8 RedMaPPer Cluster Catalogs

We compare the Planck Sunyaev-Zeldovich (SZ) cluster sample (PSZ1) to the Sloan Digital Sky Survey (SDSS) redMaPPer catalog, finding that all Planck clusters within the redMaPPer mask and within the redshift range probed by redMaPPer are contained in the redMaPPer cluster catalog. These common clusters define a tight scaling relation in the richness-SZ mass ($λ$--$M_{SZ}$) plane, with an intrinsic scatter in richness of $σ_{λ|M_{SZ}} = 0.266 \pm 0.017$. The corresponding intrinsic scatter in true cluster halo mass at fixed richness is $\approx 21\%$. The regularity of this scaling relation is used to identify failures in both the redMaPPer and Planck cluster catalogs. Of the 245 galaxy clusters in common, we identify three failures in redMaPPer and 36 failures in the PSZ1. Of these, at least 12 are due to clusters whose optical counterpart was correctly identified in the PSZ1, but where the quoted redshift for the optical counterpart in the external data base used in the PSZ1 was incorrect. The failure rates for redMaPPer and the PSZ1 are $1.2\%$ and $14.7\%$ respectively, or 9.8% in the PSZ1 after subtracting the external data base errors. We have further identified 5 PSZ1 sources that suffer from projection effects (multiple rich systems along the line-of-sight of the SZ detection) and 17 new high redshift ($z\gtrsim 0.6$) cluster candidates of varying degrees of confidence. Should all of the high-redshift cluster candidates identified here be confirmed, we will have tripled the number of high redshift Planck clusters in the SDSS region. Our results highlight the power of multi-wavelength observations to identify and characterize systematic errors in galaxy cluster data sets, and clearly establish photometric data both as a robust cluster finding method, and as an important part of defining clean galaxy cluster samples.

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A Maximum Likelihood Approach to Estimating Correlation Functions

We define a Maximum Likelihood (ML for short) estimator for the correlation function, ξ, that uses the same pair counting observables (D, R, DD, DR, RR) as the standard Landy and Szalay (1993, LS for short) estimator. The ML estimator outperforms the LS estimator in that it results in smaller measurement errors at any fixed random point density. Put another way, the ML estimator can reach the same precision as the LS estimator with a significantly smaller random point catalog. Moreover, these gains are achieved without significantly increasing the computational requirements for estimating ξ. We quantify the relative improvement of the ML estimator over the LS estimator, and discuss the regimes under which these improvements are most significant. We present a short guide on how to implement the ML estimator, and emphasize that the code alterations required to switch from a LS to a ML estimator are minimal.

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