Detection of spatial clustering in the 1000 richest SDSS DR8 redMaPPer clusters with nearest neighbor distributions

Wang, Yunchong; Banerjee, Arka; Abel, Tom; .,

doi:10.1093/mnras/stac1551

Cited by 12 publications

(3 citation statements)

References 68 publications

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“…are particularly useful integral nearest-neighbor measures, with the k = 1 version of the latter representing the mean nearestneighbor distance between particles. The void nearest neighbor function, H V , has received some attention in cosmology, both historically [66], and in recent works, in particular via the 'kNN' statistics [67][68][69][70], generalizing the above to the k-th nearest neighbor. This has been shown to yield strong constraints on cosmological parameters (cf.…”

Section: Nearest-neighbor Functionsmentioning

confidence: 99%

“…In this section, we consider whether the constraints on such parameters can be improved by adding alternative statistics. We will concentrate on the pair-connectedness function, P 2 (r ), since (a) it is simple to measure from the data, (b) it has a low-dimensional form, unlike the three-particle function, and (c) it has not previously been used in cosmology, unlike void probability or nearest-neighbor functions [70]. An alternative approach is to model the entire galaxy distribution directly (without compressing to statistics such as the correlation functions), either with perturbative methods [e.g., [110][111][112][113] or machine learning approaches [e.g., [114][115][116][117][118][119].…”

Section: The Pair-connectedness Function As a Cosmological Descriptormentioning

confidence: 99%

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The Disordered Heterogeneous Universe: Galaxy Distribution and Clustering Across Length Scales

Philcox¹,

Torquato²

2022

Preprint

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The studies of disordered heterogeneous media and galaxy cosmology share a common goal: analyzing the disordered distribution of particles and/or building blocks at 'microscales' to predict physical properties of the medium at 'macroscales', whether it be a liquid, colloidal suspension, composite material, galaxy cluster, or entire Universe. The theory of disordered heterogeneous media provides an array of theoretical and computational techniques to characterize a wide class of complex material microstructures. In this work, we apply them to describe the disordered distributions of galaxies drawn from realistic simulations. We focus on the determination of lower-order correlation functions, 'void' and 'particle' nearest-neighbor functions, certain cluster statistics, pair-connectedness functions, percolation properties, and a scalar order metric to quantify the degree of order. Compared to analogous homogeneous Poisson and typical disordered systems, the cosmological simulations exhibit enhanced large-scale clustering and longer tails in the void and particle nearest-neighbor functions, due to the presence of quasi-long-range correlations imprinted by early Universe physics, with a minimum particle separation far below the mean nearest-neighbor distance. On large scales, the system appears 'hyperuniform', as a result of primordial density fluctuations, whilst on the smallest scales, the system becomes almost 'antihyperuniform', as evidenced by its number variance. Additionally, via a finite scaling analysis, we compute the percolation threshold of the galaxy catalogs, finding this to be significantly lower than for Poisson realizations (at reduced density ηc = 0.25 in our fiducial analysis compared to ηc = 0.34), with strong dependence on the mean density; this is consistent with the observation that the galaxy distribution contains voids of up to 50% larger radius. However, the two sets of simulations appear to share the same fractal dimension on scales much larger than the average inter-galaxy separation, implying that they lie in the same universality class. We also show that the distribution of galaxies are a highly correlated disordered system (relative to the uncorrelated Poisson distribution), as measured by the τ order metric. Finally, we consider the ability of large-scale clustering statistics to constrain cosmological parameters, such as the Universe's expansion rate, using simulation-based inference. Both the nearest-neighbor distribution and pair-connectedness function (which includes contributions from correlation functions of all order) are found to considerably tighten bounds on the amplitude of quantum-mechanical fluctuations from inflation at a level equivalent to observing twenty-five times more galaxies. This provides a useful alternative to the standard three-particle correlation, and can be computed in a substantially reduced time, though likely requires simulation-based modeling. This work provides the first application of such techniques to cosmology, providing both a novel system to test ...

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Section: Nearest-neighbor Functionsmentioning

confidence: 99%

Section: The Pair-connectedness Function As a Cosmological Descriptormentioning

confidence: 99%

The Disordered Heterogeneous Universe: Galaxy Distribution and Clustering Across Length Scales

Philcox¹,

Torquato²

2022

Preprint

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“…Banerjee et al (2022) demonstrated that the 𝑘NN distributions of biased cosmological tracers, such as halos, can be well modeled on quasi-linear scales using techniques that have been developed already to model the 2PCF on these scales, and that the 𝑘NN-CDFs can improve constraints on cosmological parameters by up to a factor of 3, compared to the 2PCF, from the clustering of such tracers. Wang et al (2022) showed the first application of the 𝑘NN method to a cosmological dataset.…”

Section: Introductionmentioning

confidence: 99%

Cosmological cross-correlations and nearest neighbour distributions

Banerjee

Abel

2021

Monthly Notices of the Royal Astronomical Society

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Cross-correlations between data sets are used in many different contexts in cosmological analyses. Recently, k-nearest neighbour cumulative distribution functions (kNN-CDF) were shown to be sensitive probes of cosmological (auto) clustering. In this paper, we extend the framework of NN measurements to describe joint distributions of, and correlations between, two data sets. We describe the measurement of joint kNN-CDFs, and show that these measurements are sensitive to all possible connected N-point functions that can be defined in terms of the two data sets. We describe how the cross-correlations can be isolated by combining measurements of the joint kNN-CDFs and those measured from individual data sets. We demonstrate the application of these measurements in the context of Gaussian density fields, as well as for fully non-linear cosmological data sets. Using a Fisher analysis, we show that measurements of the halo-matter cross-correlations, as measured through NN measurements are more sensitive to the underlying cosmological parameters, compared to traditional two-point cross-correlation measurements over the same range of scales. Finally, we demonstrate how the NN cross-correlations can robustly detect cross-correlations between sparse samples – the same regime where the two-point cross-correlation measurements are dominated by noise.

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Bounds on galaxy stochasticity from halo occupation distribution modeling

Britt,

Gruen,

Friedrich

et al. 2024

A&A

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The joint probability distribution of matter overdensity and galaxy counts in cells is a powerful probe of cosmology, and the extent to which variance in galaxy counts at fixed matter density deviates from Poisson shot noise is not fully understood. The lack of informed bounds on this stochasticity is currently the limiting factor in constraining cosmology with the galaxy--matter probability distribution function (PDF). We investigate stochasticity in the conditional distribution of galaxy counts along lines of sight with fixed matter density, and we present a halo occupation distribution (HOD)-based approach for obtaining plausible ranges for stochasticity parameters. To probe the high-dimensional space of possible galaxy--matter connections, we derive a set of HODs that conserve the galaxies' linear bias and number density to produce redMaGiC -like galaxy catalogs within the AbacusSummit suite of $N$-body simulations. We study the impact of individual HOD parameters and cosmology on stochasticity and perform a Monte Carlo search in HOD parameter space subject to the constraints on bias and density. In mock catalogs generated by the selected HODs, shot noise in galaxy counts spans both sub-Poisson and super-Poisson values, ranging from 80<!PCT!> to 133<!PCT!> of Poisson variance for cells with mean matter density. Nearly all of the derived HODs show a positive relationship between local matter density and stochasticity. For galaxy catalogs with higher stochasticity, modeling galaxy bias to second order is required for an accurate description of the conditional PDF of galaxy counts at fixed matter density. The presence of galaxy assembly bias also substantially extends the range of stochasticity in the super-Poisson direction. This HOD-based approach leverages degrees of freedom in the galaxy--halo connection to obtain informed bounds on nuisance model parameters and can be adapted to study other parametrizations of shot noise in galaxy counts, in particular to motivate prior ranges on stochasticity for cosmological analyses.

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Detection of spatial clustering in the 1000 richest SDSS DR8 redMaPPer clusters with nearest neighbor distributions

Cited by 12 publications

References 68 publications

The Disordered Heterogeneous Universe: Galaxy Distribution and Clustering Across Length Scales

The Disordered Heterogeneous Universe: Galaxy Distribution and Clustering Across Length Scales

Cosmological cross-correlations and nearest neighbour distributions

Bounds on galaxy stochasticity from halo occupation distribution modeling

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