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Hendrik Hildebrandt

Publications and source records attributed to Hendrik Hildebrandt.

At least 109 records · Page 6Linked to original sources

GAMA+KiDS: Empirical correlations between halo mass and other galaxy properties near the knee of the stellar-to-halo mass relation

We use KiDS weak lensing data to measure variations in mean halo mass as a function of several key galaxy properties (namely: stellar colour, specific star formation rate, Sersic index, and effective radius) for a volume-limited sample of GAMA galaxies in a narrow stellar mass range ($M_* \sim 2$--$5 \times 10^{10}$ Msol). This mass range is particularly interesting, inasmuch as it is where bimodalities in galaxy properties are most pronounced, and near to the break in both the galaxy stellar mass function and the stellar-to-halo mass relation (SHMR). In this narrow mass range, we find that both size and Sersic index are better predictors of halo mass than either colour or SSFR, with the data showing a slight preference for Sersic index. In other words, we find that mean halo mass is more tightly correlated with galaxy structure than either past star formation history or current star formation rate. Our results lead to an approximate lower bound on the dispersion in halo masses among $\log M_* \approx {10.5}$ galaxies: we find that the dispersion is $\gtrsim 0.3$ dex. This would imply either that offsets from the mean SHMR are closely coupled to size/structure, or that the dispersion in the SHMR is larger than past results have suggested. Our results thus provide new empirical constraints on the relationship between stellar and halo mass assembly at this particularly interesting mass range.

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KiDS+GAMA: The weak lensing calibrated stellar-to-halo mass relation of central and satellite galaxies

We simultaneously present constraints on the stellar-to-halo mass relation for central and satellite galaxies through a weak lensing analysis of spectroscopically classified galaxies. Using overlapping data from the fourth data release of the Kilo-Degree Survey (KiDS), and the Galaxy And Mass Assembly survey (GAMA), we find that satellite galaxies are hosted by halo masses that are $0.53 \pm 0.39$ dex (68\% confidence, $3σ$ detection) smaller than those of central galaxies of the same stellar mass (for a stellar mass of $\log(M_{\star}/M_{\odot}) = 10.6$). This is consistent with galaxy formation models, whereby infalling satellite galaxies are preferentially stripped of their dark matter. We find consistent results with similar uncertainties when comparing constraints from a standard azimuthally averaged galaxy-galaxy lensing analysis and a two-dimensional likelihood analysis of the full shear field. As the latter approach is somewhat biased due to the lens incompleteness and as it does not provide any improvement to the precision when applied to actual data, we conclude that stacked tangential shear measurements are best-suited for studies of the galaxy-halo connection.

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KiDS+VIKING-450: Improved cosmological parameter constraints from redshift calibration with self-organising maps

We present updated cosmological constraints for the KiDS+VIKING-450 cosmic shear data set (KV450), estimated using redshift distributions and photometric samples defined using self-organising maps (SOMs). Our fiducial analysis finds marginal posterior constraints of $S_8\equivσ_8\sqrt{Ω_{\rm m}/0.3}=0.716^{+0.043}_{-0.038}$; smaller than, but otherwise consistent with, previous work using this data set ($|ΔS_8| = 0.023$). We analyse additional samples and redshift distributions constructed in three ways: excluding certain spectroscopic surveys during redshift calibration, excluding lower-confidence spectroscopic redshifts in redshift calibration, and considering only photometric sources which are jointly calibrated by at least three spectroscopic surveys. In all cases, the method utilised here proves robust: we find a maximal deviation from our fiducial analysis of $|ΔS_8| \leq 0.011$ for all samples defined and analysed using our SOM. To demonstrate the reduction in systematic biases found within our analysis, we highlight our results when performing redshift calibration without the DEEP2 spectroscopic data set. In this case we find marginal posterior constraints of $S_8=0.707_{-0.042}^{+0.046}$; a difference with respect to the fiducial that is both significantly smaller than, and in the opposite direction to, the equivalent shift from previous work. These results suggest that our improved cosmological parameter estimates are insensitive to pathological misrepresentation of photometric sources by the spectroscopy used for direct redshift calibration, and therefore that this systematic effect cannot be responsible for the observed difference between $S_8$ estimates made with KV450 and Planck CMB probes.

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KiDS+VIKING+GAMA: Testing semi-analytic models of galaxy evolution with galaxy-galaxy-galaxy lensing

Several semi-analytic models (SAMs) try to explain how galaxies form, evolve and interact inside the dark matter large-scale structure. These SAMs can be tested by comparing their predictions for galaxy-galaxy-galaxy-lensing (G3L), which is weak gravitational lensing around galaxy pairs, with observations. We evaluate the SAMs by Henriques et al. (2015; H15) and by Lagos et al. (2012; L12), implemented in the Millennium Run, by comparing their predictions for G3L to observations at smaller scales than previous studies and also for pairs of lens galaxies from different populations. We compare the G3L signal predicted by the SAMs to measurements in the overlap of the Galaxy And Mass Assembly survey (GAMA), the Kilo-Degree Survey (KiDS), and the VISTA Kilo-degree Infrared Galaxy survey (VIKING), splitting lens galaxies into two colour and five stellar-mass samples. Using an improved G3L estimator, we measure the three-point correlation of the matter distribution for mixed lens pairs with galaxies from different samples, and unmixed lens pairs with galaxies from the same sample. Predictions by the H15 SAM agree with the observations for all colour-selected and all but one stellar-mass-selected sample with 95% confidence. Deviations occur for lenses with stellar masses below $9.5h^{-2}\mathrm{M}_\odot$ at scales below $0.2h^{-1}\mathrm{Mpc}$. Predictions by the L12 SAM for stellar-mass selected samples and red galaxies are significantly higher than observed, while the predicted signal for blue galaxy pairs is too low. The L12 SAM predicts more pairs of small stellar-mass and red galaxies than the H15 SAM and the observations, as well as fewer pairs of blue galaxies. Likely explanations are different treatments of environmental effects by the SAMs and different models of the initial mass function. We conclude that G3L provides a stringent test for models of galaxy formation and evolution.

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Photometric Redshift Calibration with Self Organising Maps

Accurate photometric redshift calibration is central to the robustness of all cosmology constraints from cosmic shear surveys. Analyses of the KiDS re-weighted training samples from all overlapping spectroscopic surveys to provide a direct redshift calibration. Using self-organising maps (SOMs) we demonstrate that this spectroscopic compilation is sufficiently complete for KiDS, representing $99\%$ of the effective 2D cosmic shear sample. We use the SOM to define a $100\%$ represented `gold' cosmic shear sample, per tomographic bin. Using mock simulations of KiDS and the spectroscopic training set, we estimate the uncertainty on the SOM redshift calibration, and find that photometric noise, sample variance, and spectroscopic selection effects (including redshift and magnitude incompleteness) induce a combined maximal scatter on the bias of the redshift distribution reconstruction ($Δ\langle z \rangle=\langle z \rangle_{\rm est}-\langle z \rangle_{\rm true}$) of $σ_{Δ\langle z \rangle} \leq 0.006$ in all tomographic bins. We show that the SOM calibration is unbiased in the cases of noiseless photometry and perfectly representative spectroscopic datasets, as expected from theory. The inclusion of both photometric noise and spectroscopic selection effects in our mock data introduces a maximal bias of $Δ\langle z \rangle =0.013\pm0.006$, or $Δ\langle z \rangle \leq 0.025$ at $97.5\%$ confidence, once quality flags have been applied to the SOM. The method presented here represents a significant improvement over the previously adopted direct redshift calibration implementation for KiDS, owing to its diagnostic and quality assurance capabilities. The implementation of this method in future cosmic shear studies will allow better diagnosis, examination, and mitigation of systematic biases in photometric redshift calibration.

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KiDS+VIKING-450 and DES-Y1 combined: Mitigating baryon feedback uncertainty with COSEBIs

We present cosmological constraints from a joint cosmic shear analysis of the Kilo-Degree Survey (KV450) and the Dark Energy Survey (DES-Y1), conducted using Complete Orthogonal Sets of E/B-Integrals (COSEBIs). With COSEBIs we isolate any B-modes which have a non-cosmic shear origin and demonstrate the robustness of our cosmological E-mode analysis as no significant B-modes are detected. We highlight how COSEBIs are fairly insensitive to the amplitude of the non-linear matter power spectrum at high $k$-scales, mitigating the uncertain impact of baryon feedback in our analysis. COSEBIs, therefore, allow us to utilise additional small-scale information, improving the DES-Y1 joint constraints on $S_8=σ_8(Ω_{\rm m}/0.3)^{0.5}$ and $Ω_{\rm m}$ by $20\%$. Adopting a flat $Λ$CDM model we find $S_8=0.755^{+0.019}_{-0.021}$, which is in $3.2σ$ tension with the Planck Legacy analysis of the cosmic microwave background.

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Cosmology from large-scale structure: Constraining $Λ$CDM with BOSS

We reanalyse the anisotropic galaxy clustering measurement from the Baryon Oscillation Spectroscopic Survey (BOSS), demonstrating that using the full shape information provides cosmological constraints that are comparable to other low-redshift probes. We find $Ω_\mathrm{m} = 0.317^{+0.015}_{-0.019}$, $σ_8 = 0.710\pm 0.049$, and $h = 0.704\pm 0.024$ for flat $Λ$CDM cosmologies using uninformative priors on $Ω_\mathrm{c}h^2$, $100θ_\mathrm{MC}$, $\ln 10^{10} A_{s}$, and $n_{s}$, and a prior on $Ω_\mathrm{b}h^2$ that is much wider than current constraints. We quantify the agreement between the Planck 2018 constraints from the cosmic microwave background and BOSS, finding the two data sets to be consistent within a flat $Λ$CDM cosmology using the Bayes factor as well as the prior-insensitive suspiciousness statistic. Combining two low-redshift probes, we jointly analyse the clustering of BOSS galaxies with weak lensing measurements from the Kilo-Degree Survey (KV450). The combination of BOSS and KV450 improves the measurement by up to 45%, constraining $σ_8 = 0.702\pm 0.029$ and $S_8 = σ_8\sqrt{Ω_\mathrm{m}/0.3} = 0.728\pm 0.026$. Over the full 5D parameter space, the odds in favour of single cosmology describing galaxy clustering, lensing, and the cosmic microwave background are $7\pm2$. The suspiciousness statistic signals a $2.1\pm0.3σ$ tension between the combined low-redshift probes and measurements from the cosmic microwave background.

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The effects of varying depth in cosmic shear surveys

We present a semi-analytic model for the shear two-point correlation function of a cosmic shear survey with non-uniform depth. Ground-based surveys are subject to depth variations that primarily arise through varying atmospheric conditions. For a survey like the Kilo-Degree Survey (KiDS), we find that the measured depth variation increases the amplitude of the observed shear correlation function at the level of a few percent out to degree-scales, relative to the assumed uniform-depth case. The impact on the inferred cosmological parameters is shown to be insignificant for a KiDS-like survey. For next-generation cosmic shear experiments, however, we conclude that variable depth should be accounted for.

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A gravitational lensing detection of filamentary structures connecting luminous red galaxies

We present a weak lensing detection of filamentary structures in the cosmic web, combining data from the Kilo-Degree Survey, the Red Cluster Sequence Lensing Survey and the Canada-France-Hawaii Telescope Lensing Survey. The line connecting luminous red galaxies with a separation of $3 - 5\, h^{-1}\text{Mpc}$ is chosen as a proxy for the location of filaments. We measure the average weak lensing shear around $\sim$11,000 candidate filaments selected in this way from the Sloan Digital Sky Survey. After nulling the shear induced by the dark matter haloes around each galaxy, we report a $3.4\,σ$ detection of an anisotropic shear signal from the matter that connects them. Adopting a filament density profile, motivated from $N$-body simulations, the average density at the centre of these filamentary structures is found to be $15 \pm 4$ times the critical density.

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KiDS+VIKING-450: A new combined optical & near-IR dataset for cosmology and astrophysics

We present the curation and verification of a new combined optical and near infrared dataset for cosmology and astrophysics, derived from the combination of $ugri$-band imaging from the Kilo Degree Survey (KiDS) and $ZY\!J\!H\!K_{\rm s}$-band imaging from the VISTA Kilo degree Infrared Galaxy (VIKING) survey. This dataset is unrivaled in cosmological imaging surveys due to its combination of area ($458$ deg$^2$ before masking), depth ($r\le25$), and wavelength coverage ($ugriZY\!J\!H\!K_{\rm s}$). The combination of survey depth, area, and (most importantly) wavelength coverage allows significant reductions in systematic uncertainties (i.e. reductions of between 10 and 60\% in bias, outlier rate, and scatter) in photometric-to-spectroscopic redshift comparisons, compared to the optical-only case at photo-$z$ above $0.7$. The complementarity between our optical and NIR surveys means that over $80\%$ of our sources, across all photo-$z$, have significant detections (i.e. not upper limits) in our $8$ reddest bands. We derive photometry, photo-$z$, and stellar masses for all sources in the survey, and verify these data products against existing spectroscopic galaxy samples. We demonstrate the fidelity of our higher-level data products by constructing the survey stellar mass functions in 8 volume-complete redshift bins. We find that these photometrically derived mass functions provide excellent agreement with previous mass evolution studies derived using spectroscopic surveys. The primary data products presented in this paper are publicly available at http://kids.strw.leidenuniv.nl/.

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Consistent cosmic shear in the face of systematics: a B-mode analysis of KiDS-450, DES-SV and CFHTLenS

We analyse three public cosmic shear surveys; the Kilo-Degree Survey (KiDS-450), the Dark Energy Survey (DES-SV) and the Canada France Hawaii Telescope Lensing Survey (CFHTLenS). Adopting the COSEBIs statistic to cleanly and completely separate the lensing E-modes from the non-lensing B-modes, we detect B-modes in KiDS-450 and CFHTLenS at the level of about 2.7 $σ$. For DES- SV we detect B-modes at the level of 2.8 $σ$ in a non-tomographic analysis, increasing to a 5.5 $σ$ B-mode detection in a tomographic analysis. In order to understand the origin of these detected B-modes we measure the B-mode signature of a range of different simulated systematics including PSF leakage, random but correlated PSF modelling errors, camera-based additive shear bias and photometric redshift selection bias. We show that any correlation between photometric-noise and the relative orientation of the galaxy to the point-spread-function leads to an ellipticity selection bias in tomographic analyses. This work therefore introduces a new systematic for future lensing surveys to consider. We find that the B-modes in DES-SV appear similar to a superposition of the B-mode signatures from all of the systematics simulated. The KiDS-450 and CFHTLenS B-mode measurements show features that are consistent with a repeating additive shear bias.

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Towards emulating cosmic shear data: Revisiting the calibration of the shear measurements for the Kilo-Degree Survey

Exploiting the full statistical power of future cosmic shear surveys will necessitate improvements to the accuracy with which the gravitational lensing signal is measured. We present a framework for calibrating shear with image simulations that demonstrates the importance of including realistic correlations between galaxy morphology, size and more importantly, photometric redshifts. This realism is essential so that selection and shape measurement biases can be calibrated accurately for a tomographic cosmic shear analysis. We emulate Kilo-Degree Survey (KiDS) observations of the COSMOS field using morphological information from {\it Hubble} Space Telescope imaging, faithfully reproducing the measured galaxy properties from KiDS observations of the same field. We calibrate our shear measurements from lensfit, and find through a range of sensitivity tests that lensfit is robust and unbiased within the allowed 2 per cent tolerance of our study. Our results show that the calibration has to be performed by selecting the tomographic samples in the simulations, consistent with the actual cosmic shear analysis, because the joint distributions of galaxy properties are found to vary with redshift. Ignoring this redshift variation could result in misestimating the shear bias by an amount that exceeds the allowed tolerance. To improve the calibration for future cosmic shear analyses, it will be essential to also correctly account for the measurement of photometric redshifts, which requires simulating multi-band observations.

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Weak-lensing shear measurement with machine learning: teaching artificial neural networks about feature noise

Cosmic shear is a primary cosmological probe for several present and upcoming surveys investigating dark matter and dark energy, such as Euclid or WFIRST. The probe requires an extremely accurate measurement of the shapes of millions of galaxies based on imaging data. Crucially, the shear measurement must address and compensate for a range of interwoven nuisance effects related to the instrument optics and detector, noise, unknown galaxy morphologies, colors, blending of sources, and selection effects. This paper explores the use of supervised machine learning (ML) as a tool to solve this inverse problem. We present a simple architecture that learns to regress shear point estimates and weights via shallow artificial neural networks. The networks are trained on simulations of the forward observing process, and take combinations of moments of the galaxy images as inputs. A challenging peculiarity of this ML application is the combination of the noisiness of the input features and the requirements on the accuracy of the inverse regression. To address this issue, the proposed training algorithm minimizes bias over multiple realizations of individual source galaxies, reducing the sensitivity to properties of the overall sample of source galaxies. Importantly, an observational selection function of these source galaxies can be straightforwardly taken into account via the weights. We first introduce key aspects of our approach using toy-model simulations, and then demonstrate its potential on images mimicking Euclid data. Finally, we analyze images from the GREAT3 challenge, obtaining competitively low shear biases despite the use of a simple training set. We conclude that the further development of ML approaches is of high interest to meet the stringent requirements on the shear measurement in current and future surveys. A demonstration implementation of our technique is publicly available.

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Studying galaxy troughs and ridges using Weak Gravitational Lensing with the Kilo-Degree Survey

We study projected underdensities in the cosmic galaxy density field known as 'troughs', and their overdense counterparts, which we call 'ridges'. We identify these regions using a bright sample of foreground galaxies from the photometric Kilo-Degree Survey (KiDS), specifically selected to mimic the spectroscopic Galaxy And Mass Assembly survey (GAMA). Using background galaxies from KiDS, we measure the weak gravitational lensing profiles of the troughs/ridges. We quantify the amplitude of their lensing strength $A$ as a function of galaxy density percentile rank $P$ and galaxy overdensity $δ$, and find that the skewness in the galaxy density distribution is reflected in the total mass distribution measured by weak lensing. We interpret our results using the mock galaxy catalogue from the Marenostrum Institut de Ciències de l'Espai (MICE) simulation, and find a good agreement with our observations. Using signal-to-noise weights derived from the Scinet LIghtCone Simulations (SLICS) mock catalogue we optimally stack the lensing signal of KiDS troughs with an angular radius $θ_A$ = {5,10,15,20} arcmin, resulting in {16.8,14.9,10.13,7.55} $σ$ detections. Finally, we select troughs using a volume-limited sample of galaxies, split into two redshift bins between 0.1 < z < 0.3. For troughs/ridges with transverse comoving radius $R_A$ = 1.9 Mpc/h, we find no significant difference in the comoving Excess Surface Density as a function of $P$ and $δ$ between the low- and high-redshift sample. Using the MICE and SLICS mocks we predict that trough and ridge evolution could be detected with gravitational lensing using deeper and wider lensing surveys, such as those from the Large Synoptic Survey Telescope and Euclid.

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The dependence of intrinsic alignment of galaxies on wavelength using KiDS and GAMA

The outer regions of galaxies are more susceptible to the tidal interactions that lead to intrinsic alignments of galaxies. The resulting alignment signal may therefore depend on the passband if the colours of galaxies vary spatially. To quantify this, we measured the shapes of galaxies with spectroscopic redshifts from the GAMA survey using deep gri imaging data from the KiloDegree Survey. The performance of the moment-based shape measurement algorithm DEIMOS was assessed using dedicated image simulations, which showed that the ellipticities could be determined with an accuracy better than 1% in all bands. Additional tests for potential systematic errors did not reveal any issues. We measure a significant difference of the alignment signal between the g,r and i-band observations. This difference exceeds the amplitude of the linear alignment model on scales below 2 Mpc/h. Separating the sample into central/satellite and red/blue galaxies, we find that that the difference is dominated by red satellite galaxies.

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AMICO galaxy clusters in KiDS-DR3: weak-lensing mass calibration

We present the mass calibration for galaxy clusters detected with the AMICO code in KiDS DR3 data. The cluster sample comprises $\sim$ 7000 objects and covers the redshift range 0.1 < $z$ < 0.6. We perform a weak lensing stacked analysis by binning the clusters according to redshift and two different mass proxies provided by AMICO, namely the amplitude $A$ (measure of galaxy abundance through an optimal filter) and the richness $λ^*$ (sum of membership probabilities in a consistent radial and magnitude range across redshift). For each bin, we model the data as a truncated NFW profile plus a 2-halo term, taking into account uncertainties related to concentration and miscentring. From the retrieved estimates of the mean halo masses, we construct the $A$-$M_{200}$ and the $λ^*$-$M_{200}$ relations. The relations extend over more than one order of magnitude in mass, down to $M_{200} \sim 2 (5) \times 10^{13} M_\odot/h$ at $z$ = 0.2 (0.5), with small evolution in redshift. The logarithmic slope is $\sim 2.0$ for the $A$-mass relation, and $\sim 1.7$ for the $λ^*$-mass relation, consistent with previous estimations on mock catalogues and coherent with the different nature of the two observables.

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KiDS-450: Enhancing cosmic shear with clipping transformations

We present the first "clipped" cosmic shear measurement using data from the Kilo-Degree Survey (KiDS-450). "Clipping" transformations suppress the signal from the highest density, non-linear regions of cosmological fields. We demonstrate that these transformations improve constraints on $S_8=σ_8(Ω_{\rm{m}}/0.3)^{0.5}$ when used in combination with conventional two-point statistics. For the KiDS-450 data, we find that the combined measurements improve the constraints on $S_8$ by 17%, compared to shear correlation functions alone. We determine the expectation value of the clipped shear correlation function using a suite of numerical simulations, and develop methodology to mitigate the impact of masking and shot noise. Future improvements in numerical simulations and mass reconstruction methodology will permit the precise calibration of clipped cosmic shear statistics such that clipping can become a standard tool in weak lensing analyses.

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Unveiling Galaxy Bias via the Halo Model, KiDS and GAMA

We measure the projected galaxy clustering and galaxy-galaxy lensing signals using the Galaxy And Mass Assembly (GAMA) survey and Kilo-Degree Survey (KiDS) to study galaxy bias. We use the concept of non-linear and stochastic galaxy biasing in the framework of halo occupation statistics to constrain the parameters of the halo occupation statistics and to unveil the origin of galaxy biasing. The bias function $Γ_{\text{gm}}(r_{\text{p}})$, where $r_{\text{p}}$ is the projected comoving separation, is evaluated using the analytical halo model from which the scale dependence of $Γ_{\text{gm}}(r_{\text{p}})$, and the origin of the non-linearity and stochasticity in halo occupation models can be inferred. Our observations unveil the physical reason for the non-linearity and stochasticity, further explored using hydrodynamical simulations, with the stochasticity mostly originating from the non-Poissonian behaviour of satellite galaxies in the dark matter haloes and their spatial distribution, which does not follow the spatial distribution of dark matter in the halo. The observed non-linearity is mostly due to the presence of the central galaxies, as was noted from previous theoretical work on the same topic. We also see that overall, more massive galaxies reveal a stronger scale dependence, and out to a larger radius. Our results show that a wealth of information about galaxy bias is hidden in halo occupation models. These models should therefore be used to determine the influence of galaxy bias in cosmological studies.

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