arXiv subjects

Enrique Paillas

Publications and source records attributed to Enrique Paillas.

At least 19 recordsLinked to original sources

arXiv2026

Cosmic Pairs: A DESI Census of Dual and Offset AGN as Precursors to Massive Black Hole Binaries

We present a systematic census of dual and offset active galactic nuclei (AGN) using spectroscopic data from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). After correcting for observational systematics, our final sample contains $>7,000$ dual AGN and 27,000 galaxy pairs containing one AGN over the redshift range $0 \lesssim z \lesssim 3.6$. This sample expands the known dual AGN sample by $\sim 1-2$ orders of magnitude at $0.2 \lesssim z \lesssim 0.4$, includes $\sim 50$ dwarf dual AGN candidates in a regime where only a handful were previously known, and triples the census at $z>2$. Dual AGN are preferentially found at small separations, consistent with merger-driven triggering of AGN activity. The two members of a pair differ in their star formation response: the more massive (primary) host changes little with separation, while the less massive (secondary) lies $\sim 0.3$ dex above matched inactive and one-AGN companions at the same projected separation in main-sequence offset. Using ASTRID simulations, we predict that the fraction of DESI dual AGN whose central black holes will merge by $z \sim 0$ increases with redshift, reaching $\sim 76\%$ by $z \sim 2$, while the fraction producing LISA-detectable mergers peaks at $\sim 37\%$ near $z \sim 0.9$. These results provide the largest uniformly selected spectroscopic sample of kpc-scale dual and offset AGN candidates from a single survey, connecting their host-galaxy and AGN demographics to the progenitor population of massive black hole mergers detectable by LISA.

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arXiv2026

A Parameter-Masked Mock Data Challenge for Beyond-Two-Point Galaxy Clustering Statistics

The last few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge "Beyond-2pt", initiated during the Aspen 2022 Summer Program "Large-Scale Structure Cosmology beyond 2-Point Statistics," whose first round of results we present here. The challenge dataset consists of high-precision mock galaxy catalogs for clustering in real space, redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown ("masked") cosmological parameters of the underlying $Λ$CDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available and we welcome future submissions from methods that are not yet represented.

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arXiv2026

Nonlinear Information from DESI Luminous Red Galaxies: An Emulator-Based Analysis of Pre- and Post-Reconstruction Power Spectra

We present joint measurements of the pre- and post-reconstruction power spectra, $P_{\rm pre}$ and $P_{\rm post}$, together with their cross-power spectrum, $P_{\rm cross}$, for the Luminous Red Galaxies (LRGs) in the DESI Data Release 1 (DR1). We jointly analyse these observables with an emulator-based full-shape modeling framework, thereby, for the first time, we extract complementary nonlinear information from the galaxy density field before and after reconstruction in real survey data. Specifically, including $P_{\rm post}$ and $P_{\rm cross}$ in addition to $P_{\rm pre}$ (hereafter $P_{\rm all}$) yields an improvement of approximately $18$-$27\%$ in the $σ_8$ constraint in both $Λ$CDM and $w$CDM, depending on the redshift bin, relative to the $P_{\rm pre}$-only analysis with the cosmic microwave background distance priors (hereafter CMB). In $w$CDM, the joint CMB+$P_{\rm all}$ analysis can tighten the constraints on $w$ by approximately $5$-$15\%$ across the two LRG redshift bins, compared to the CMB+$P_{\rm pre}$ combination. Further incorporating the Type Ia supernova dataset and comparing the cosmological constraints in $w$CDM from each individual power-spectrum component with those from the full combination, we find that $P_{\rm all}$ consistently provides the tightest constraints. From the joint CMB+$P_{\rm all}$+DES-Dovekie dataset, we obtain $Ω_m = 0.314 \pm 0.0048$ and $w = -0.988 \pm 0.023$ for the \texttt{LRG1} sample, and $Ω_m = 0.318 \pm 0.0046$ and $w = -0.988 \pm 0.025$ for \texttt{LRG2}. These results demonstrate that combining pre- and post-reconstruction power spectra with their cross-correlation enables DESI to harvest additional nonlinear information, leading to tighter constraints on cosmological parameters.

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arXiv2025

What Galaxy Clusters Have to Say About Dynamical Dark Energy and $H_0$

We show that, in flat $Λ$CDM, low-redshift structure probes -- cluster abundances, 3$\times$2-point analyses, and full-shape clustering -- are mutually consistent, jointly delivering precise constraints on $σ_8$ and $Ω_{\rm m}$ that agree with geometrical datasets (CMB+BAO+SN). In $w_0w_a$CDM, adding clusters to the geometry dataset reduces the evidence for evolving dark energy while relaxing the $H_0$ tension, suggesting a $Λ$CDM evolution of the late-time Universe and a sound horizon that differs from its standard value.

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arXiv2025

A theoretical approach to density-split clustering

We present an analytical model for density-split correlation functions, that probe galaxy clustering in different density environments. Specifically, we focus on the cross-correlation between density-split regions and the tracer density field. We show that these correlation functions can be expressed in terms of the two-point probability density function (PDF) of the density field. We derive analytical predictions using three levels of approximation for the two-point PDF: a bivariate Gaussian distribution, a bivariate shifted log-normal distribution, and a prediction based on the Large Deviation Theory (LDT) framework. For count-in-cell densities, obtained through spherical top-hat smoothing, one can leverage spherical collapse dynamics and LDT to predict the density two-point PDF in the large-separation regime relative to the smoothing radius. We validate our model against dark matter N-body simulations in real space, incorporating Poisson shot noise and galaxy bias. Our results show that the LDT prediction outperforms the log-normal approximation, and agrees with simulations on large scales within the cosmic variance of a typical DESI DR1 sample, despite relying on only one degree of freedom.

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arXiv2025

Cosmological constraints from the Minkowski functionals of the BOSS CMASS galaxy sample

For the first time, we develop a simulation-based model for the Minkowski functionals (MFs) of large-scale structure, which allows us to extract the full information available from the MFs (including both the Gaussian and non-Gaussian part), and apply it to the BOSS DR12 CMASS galaxy sample. Our model is based on high-fidelity mock galaxy catalogs constructed from the \textsc{Abacus}\textsc{Summit} simulations using the halo occupation distribution (HOD) framework, which include the redshift-space distortions and Alcock-Paczynski distortions, incorporate survey realism, including survey geometry and veto masks, and account for angular plus radial selection effects. The cosmological and HOD parameter dependence of the MFs is captured with a neural network emulator trained from the galaxy mocks with various cosmological and HOD parameters. To benchmark the constraining power of the MFs, we also train an emulator for the galaxy 2-point correlation function (2PCF) using the same pipeline. Having validated our approach through successful parameter recovery tests on both internal and external mocks, including non-HOD forward models of the halo-galaxy connection, we apply our forward model to analyze the CMASS data in the redshift range $0.45<z<0.58$. We find the MFs provide stronger constraints on the cosmological parameters than the 2PCF. The combination of the two gives $ω_{\rm cdm}=0.1172^{+0.0020}_{-0.0023}$, $σ_8=0.783\pm 0.026$, and $n_s=0.966^{+0.019}_{-0.015}$, which are tighter by a factor of 2.0, 1.9, and 1.6 than the 2PCF alone. The derived constraint $fσ_8=0.453 \pm 0.016$ is also improved by a factor of 1.9, compared to the 2PCF, and agrees well with Planck 2018 predictions and other results from a series of studies in the literature.

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arXiv2025

Modelling the BOSS void-galaxy cross-correlation function using a neural-network emulator

We introduce an emulator-based method to model the cross-correlation between cosmological voids and galaxies. This allows us to model the effect of cosmology on void finding and on the shape of the void-galaxy cross-correlation function, improving on previous template-based methods. We train a neural network using the AbacusSummit simulation suite and fit to data from the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey sample. We recover information on the growth of structure through redshift-space distortions (RSD), and the geometry of the Universe through the Alcock-Paczyński (AP) effect, measuring $Ω_{\rm m} = 0.330\pm 0.020$ and $σ_8 = 0.777^{+0.047}_{-0.062}$ for a $Λ\rm{CDM}$ cosmology. Comparing to results from a template-based method, we find that fitting the shape of the void-galaxy cross-correlation function provides more information and leads to an improvement in constraining power. In contrast, we find that errors on the AP measurements were previously underestimated if void centres were assumed to have the same response to the AP effect as galaxies - a common simplification. Overall, we recover a $28\%$ reduction in errors for $Ω_{\rm{m}}$ and similar errors on $σ_8$ with our new, more comprehensive, method. Given the statistical power of future surveys including DESI and Euclid, we expect the method presented to become the new baseline for the analysis of voids in these data.

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arXiv2024

Cosmological parameters from the joint analysis of Density Split and Second Order Statistics: an Emulator based on the Halo Occupation Distribution

In this work, we develop a simulation-based model to predict the density split (DSS) and second-order shear and clustering statistics. A simulation-based model has the potential to model highly non-linear scales where current DSS models fail. To build this model, we use the $\texttt{AbacusSummit}$ N-body simulation suite from which we measure all necessary statistics and train an emulator based on $\texttt{CosmoPower}$. In that context, we discuss possible improvements for future emulators to make the measurement less noisy and biased, resulting in more accurate and precise model predictions. Regarding the emulator's accuracy, we find that the most important aspect is the average of the summary statistics over multiple-shot noise realizations of the foreground galaxies. However, these results probably depend on the chosen number density of the foreground galaxies. Regarding the parameter forecast based on preliminary LOWZxUNIONS data, we find that DSS has more constraining power to derive cosmological parameters and that the joint analysis with second-order statistics is particularly useful for extracting parameters of the galaxy-halo connection.

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arXiv2024

Constraining Primordial Non-Gaussianity with Density-Split Clustering

Obtaining tight constraints on primordial non-Gaussianity (PNG) is a key step in discriminating between different models for cosmic inflation. The constraining power from large-scale structure (LSS) measurements is expected to overtake that from cosmic microwave background (CMB) anisotropies with the next generation of galaxy surveys including the Dark Energy Spectroscopic Instrument (DESI) and Euclid. We consider whether Density-Split Clustering (DSC) can help improve PNG constraints from these surveys for local, equilateral and orthogonal types. DSC separates a surveyed volume into regions based on local density and measures the clustering statistics within each environment. Using the Quijote simulations and the Fisher information formalism, we compare PNG constraints from the standard halo power spectrum, DSC power spectra and joint halo/DSC power spectra. We find that the joint halo/DSC power spectra outperform the halo power spectrum by factors of $\sim$ 1.4, 8.8, and 3.6 for local, equilateral and orthogonal PNG, respectively. This is driven by the higher-order information that DSC captures on small scales. We find that applying DSC to a halo field does not allow sample variance cancellation on large scales by providing multiple tracers of the same volume with different local PNG responses. Additionally, we introduce a Fourier space analysis for DSC and study the impact of several modifications to the pipeline, such as varying the smoothing radius and the number of density environments and replacing random query positions with lattice points.

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arXiv2024

Constraining modified gravity with weak lensing peaks

It is well established that maximizing the information extracted from upcoming and ongoing stage-IV weak-lensing surveys requires higher-order summary statistics that complement the standard two-point statistics. In this work, we focus on weak-lensing peak statistics to test two popular modified gravity models, $f(R)$ and nDGP, using the FORGE and BRIDGE weak-lensing simulations, respectively. From these simulations we measure the peak statistics as a function of both cosmological and modified gravity parameters simultaneously. Our findings indicate that the peak abundance is sensitive to the strength of modified gravity, while the peak two-point correlation function is sensitive to the nature of the screening mechanism in a modified gravity model. We combine these simulated statistics with a Gaussian Process Regression emulator and a Gaussian likelihood to generate stage-IV forecast posterior distributions for the modified gravity models. We demonstrate that, assuming small scales can be correctly modelled, peak statistics can be used to distinguish GR from $f(R)$ and nDGP models at the two-sigma level with a stage-IV survey area of $300 \, \rm{deg}^2$ and $1000 \, \rm{deg}^2$, respectively. Finally, we show that peak statistics can constrain $\log_{10}\left(|f_{R0}|\right) = -6$ to 2\% precision, and $\log_{10}(H_0 r_c) = 0.5$ to 25\% precision.

astro-ph.CO↗

arXiv2024

Alcock-Paczyński effect on void-finding: Implications for void-galaxy cross-correlation modelling

Under the assumption of statistical isotropy, and in the absence of directional selection effects, a stack of voids is expected to be spherically symmetric, which makes it an excellent object to use for an Alcock-Paczyński (AP) test. This is commonly done using the void-galaxy cross-correlation function (CCF), which has emerged as a competitive probe, especially in combination with the galaxy-galaxy auto correlation function. Current studies of the AP effect around voids assume that the void centre positions transform under the choice of fiducial cosmology in the same way as galaxy positions. We show that this assumption, though prevalent in the literature, is complicated by the response of void-finding algorithms to shifts in tracer positions. Using stretched simulation boxes to emulate the AP effect, we investigate how the void-galaxy CCF changes under AP, revealing an additional effect imprinted in the CCF that must be accounted for. The effect comes from the response of void finders to the distorted tracer field, reducing the amplitude of the AP signal in the CCF, and thus depends on the specific void finding algorithm used. We present results for four different void finding packages: $\texttt{revolver}$, $\texttt{vide}$, $\texttt{voxel}$, and the spherical void finder in the $\texttt{Pylians3}$ library, demonstrating how incorrect treatment of the AP effect results in biases in the recovered parameters for all of them. Finally, we propose a method to alleviate this issue without resorting to complex and finder-specific modelling of the void finder response to AP.

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arXiv2023

SUNBIRD: A simulation-based model for full-shape density-split clustering

Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point correlation function (2PCF) analyses. However, modelling these density-dependent statistics down to the non-linear regime has so far remained challenging. We present a simulation-based model that is able to capture the cosmological dependence of the full shape of the density-split clustering (DSC) statistics down to intra-halo scales. Our models are based on neural-network emulators that are trained on high-fidelity mock galaxy catalogues within an extended-$Λ$CDM framework, incorporating the effects of redshift-space, Alcock-Paczynski distortions and models of the halo-galaxy connection. Our models reach sub-percent level accuracy down to $1\,h^{-1}{\rm Mpc}$ and are robust against different choices of galaxy-halo connection modelling. When combined with the galaxy 2PCF, DSC can tighten the constraints on $ω_{\rm cdm}$, $σ_8$, and $n_s$ by factors of 2.9, 1.9, and 2.1, respectively, compared to a 2PCF-only analysis. DSC additionally puts strong constraints on environment-based assembly bias parameters. Our code is made publicly available on Github.

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arXiv2023

Cosmological constraints from density-split clustering in the BOSS CMASS galaxy sample

We present a clustering analysis of the BOSS DR12 CMASS galaxy sample, combining measurements of the galaxy two-point correlation function and density-split clustering down to a scale of $1\,h^{-1}{\rm Mpc}$. Our theoretical framework is based on emulators trained on high-fidelity mock galaxy catalogues that forward model the cosmological dependence of the clustering statistics within an extended-$Λ$CDM framework, including redshift-space and Alcock-Paczynski distortions. Our base-$Λ$CDM analysis finds $ω_{\rm cdm} = 0.1201\pm 0.0022$, $σ_8 = 0.792\pm 0.034$, and $n_s = 0.970\pm 0.018$, corresponding to $fσ_8 = 0.462\pm 0.020$ at $z \approx 0.525$, which is in agreement with Planck 2018 predictions and various clustering studies in the literature. We test single-parameter extensions to base-$Λ$CDM, varying the running of the spectral index, the dark energy equation of state, and the density of massless relic neutrinos, finding no compelling evidence for deviations from the base model. We model the galaxy-halo connection using a halo occupation distribution framework, finding signatures of environment-based assembly bias in the data. We validate our pipeline against mock catalogues that match the clustering and selection properties of CMASS, showing that we can recover unbiased cosmological constraints even with a volume 84 times larger than the one used in this study.

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arXiv2023

Cosmological measurements from void-galaxy and galaxy-galaxy clustering in the Sloan Digital Sky Survey

We present the cosmological implications of measurements of void-galaxy and galaxy-galaxy clustering from the Sloan Digital Sky Survey (SDSS) Main Galaxy Sample (MGS), Baryon Oscillation Spectroscopic Survey (BOSS), and extended BOSS (eBOSS) luminous red galaxy catalogues from SDSS Data Release 7, 12, and 16, covering the redshift range $0.07 < z < 1.0$. We fit a standard $Λ$CDM cosmological model as well as various extensions including a constant dark energy equation of state not equal to $-1$, a time-varying dark energy equation of state, and these same models allowing for spatial curvature. Results on key parameters of these models are reported for void-galaxy and galaxy-galaxy clustering alone, both of these combined, and all these combined with measurements from the cosmic microwave background (CMB) and supernovae (SN). For the combination of void-galaxy and galaxy-galaxy clustering, we find tight constraints of $Ω_\mathrm{m} = 0.356\pm 0.024$ for a base $Λ$CDM cosmology, $Ω_\mathrm{m} = 0.391^{+0.028}_{-0.021}, w = -1.50^{+0.43}_{-0.28}$ additionally allowing the dark energy equation of state $w$ to vary, and $Ω_\mathrm{m} = 0.331^{+0.067}_{-0.094}, w=-1.41^{+0.70}_{-0.31},\ \mathrm{and}\ Ω_\mathrm{k} = 0.06^{+0.18}_{-0.13}$ further extending to non-flat models. The combined SDSS results from void-galaxy and galaxy-galaxy clustering in combination with CMB+SN provide a 30% improvement in parameter $Ω_\mathrm{m}$ over CMB+SN for $Λ$CDM, a 5% improvement in parameter $Ω_\mathrm{m}$ when $w$ is allowed to vary, and a 32% and 68% improvement in parameters $Ω_\mathrm{m}$ and $Ω_\mathrm{k}$ when allowing for spatial curvature.

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arXiv2023

Constraining νΛCDM with density-split clustering

The dependence of galaxy clustering on local density provides an effective method for extracting non-Gaussian information from galaxy surveys. The two-point correlation function (2PCF) provides a complete statistical description of a Gaussian density field. However, the late-time density field becomes non-Gaussian due to non-linear gravitational evolution and higher-order summary statistics are required to capture all of its cosmological information. Using a Fisher formalism based on halo catalogues from the Quijote simulations, we explore the possibility of retrieving this information using the density-split clustering (DS) method, which combines clustering statistics from regions of different environmental density. We show that DS provides more precise constraints on the parameters of the $νΛ$CDM model compared to the 2PCF, and we provide suggestions for where the extra information may come from. DS improves the constraints on the sum of neutrino masses by a factor of $7$ and by factors of 4, 3, 3, 6, and 5 for $Ω_{\rm m}$, $Ω_{\rm b}$, $h$, $n_s$, and $σ_8$, respectively. We compare DS statistics when the local density environment is estimated from the real or redshift-space positions of haloes. The inclusion of DS autocorrelation functions, in addition to the cross-correlation functions between DS environments and haloes, recovers most of the information that is lost when using the redshift-space halo positions to estimate the environment. We discuss the possibility of constructing simulation-based methods to model DS clustering statistics in different scenarios.

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arXiv2022

Revealing the properties of void galaxies and their assembly using the EAGLE simulation

We explore the properties of central galaxies living in voids using the EAGLE cosmological hydrodynamic simulations. Based on the minimum void-centric distance, we define four galaxy samples: inner void, outer void, wall, and skeleton. We find that inner void galaxies with host halo masses $<10^{12}M_\odot$ have lower stellar mass and stellar mass fractions than those in denser environments, and the fraction of galaxies with star formation (SF) activity and atomic hydrogen (HI) gas decreases with increasing void-centric distance, in agreement with observations. To mitigate the influence of stellar (halo) mass, we compare inner void galaxies to subsamples of fixed stellar (halo) mass. Compared to denser environments, inner void galaxies with $M_{*}= 10^{[9.0-9.5]}M_\odot$ have comparable SF activity and HI gas fractions, but the lowest quenched galaxy fraction. Inner void galaxies with $M_{*}= 10^{[9.5-10.5]}M_\odot$ have the lowest HI gas fraction, the highest quenched fraction and the lowest gas metallicities. On the other hand, inner void galaxies with $M_{*}>10^{10.5}M_\odot$ have comparable SF activity and HI gas fractions to their analogues in denser environments. They retain the highest metallicity gas that might be linked to physical processes that act with lower efficiency in underdense regions, such as AGN feedback. Furthermore, inner void galaxies have the lowest fraction of positive gas-phase metallicity gradients, which are typically associated with external processes or feedback events, suggesting they have more quiet merger histories than galaxies in denser environments. Our findings shed light on how galaxies are influenced by their large-scale environment.

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arXiv2021

Redshift-space distortions with split densities

Accurate modelling of redshift-space distortions (RSD) is challenging in the non-linear regime for two-point statistics e.g. the two-point correlation function (2PCF). We take a different perspective to split the galaxy density field according to the local density, and cross-correlate those densities with the entire galaxy field. Using mock galaxies, we demonstrate that combining a series of cross-correlation functions (CCFs) offers improvements over the 2PCF as follows: 1. The distribution of peculiar velocities in each split density is nearly Gaussian. This allows the Gaussian streaming model for RSD to perform accurately within the statistical errors of a ($1.5\,h^{-1}$Gpc)$^3$ volume for almost all scales and all split densities. 2. The PDF of the density field at small scales is non-Gaussian, but the CCFs of split densities capture the non-Gaussianity, leading to improved cosmological constraints over the 2PCF. We can obtain unbiased constraints on the growth parameter $fσ_{12}$ at the per-cent level, and Alcock-Paczynski (AP) parameters at the sub-per-cent level with the minimal scale of $15\,h^{-1}{\rm Mpc}$. This is a $\sim$30 per cent and $\sim$6 times improvement over the 2PCF, respectively. The diverse and steep slopes of the CCFs at small scales are likely to be responsible for the improved constraints of AP parameters. 3. Baryon acoustic oscillations (BAO) are contained in all CCFs of split densities. Including BAO scales helps to break the degeneracy between the line-of-sight and transverse AP parameters, allowing independent constraints on them. We discuss and compare models for RSD around spherical densities.

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arXiv2020

Optimal void finders in weak lensing maps

Cosmic voids are a key component of the large-scale structure that contain a plethora of cosmological information. Typically, voids are identified from the underlying galaxy distribution, which is a biased tracer of the total matter field. Previous works have shown that 2D voids identified in weak lensing maps -- weak lensing voids -- correspond better to true underdense regions along the line of sight. In this work, we study how the properties of weak lensing voids depend on the choice of void finder, by adapting several popular void finders. We present and discuss the differences between identifying voids directly in the convergence maps, and in the distribution of weak lensing peaks. Particular effort has been made to test how these results are affected by galaxy shape noise, which is a dominant source of noise in weak lensing observations. By studying the signal-to-noise ratios (SNR) for the tangential shear profile of each void finder, we find that voids identified directly in the convergence maps have the highest SNR but are also the ones most affected by galaxy shape noise. Troughs are least affected by noise, but also have the lowest SNR. The tunnel algorithm, which identifies voids in the distribution of weak lensing peaks, represents a good compromise between finding a large tangential shear SNR and mitigating the effect of galaxy shape noise.

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