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Related papers: On Recovering the Nonlinear Bias Function from Cou…

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We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation…

Cosmology and Nongalactic Astrophysics · Physics 2019-09-09 Ben Hoyle , Markus Michael Rau

We present a simple method for evaluating the nonlinear biasing function of galaxies from a redshift survey. The nonlinear biasing is characterized by the conditional mean of the galaxy density fluctuation given the underlying mass density…

Astrophysics · Physics 2009-10-31 Yair Sigad , Enzo Branchini , Avishai Dekel

We present a Bayesian reconstruction algorithm to generate unbiased samples of the underlying dark matter field from halo catalogues. Our new contribution consists of implementing a non-Poisson likelihood including a deterministic…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 Metin Ata , Francisco-Shu Kitaura , Volker Müller

We propose a strategy to measure the dark matter power spectrum using minimal assumptions about the galaxy distribution and the galaxy-dark matter cross-correlations. We argue that on large scales the central limit theorem generically…

Astrophysics · Physics 2009-10-30 Ue-Li Pen

Starting from a very accurate model for density-in-cells statistics of dark matter based on large deviation theory, a bias model for the tracer density in spheres is formulated. It adopts a mean bias relation based on a quadratic bias model…

Accurate analyses of present and next-generation galaxy surveys require new ways to handle effects of non-linear gravitational structure formation in data. To address these needs we present an extension of our previously developed algorithm…

Cosmology and Nongalactic Astrophysics · Physics 2019-05-15 Jens Jasche , Guilhem Lavaux

We investigate how well the redshift distributions of galaxies sorted into photometric redshift bins can be determined from the galaxy angular two-point correlation functions. We find that the uncertainty in the reconstructed redshift…

Astrophysics · Physics 2008-11-26 M. Schneider , L. Knox , H. Zhan , A. Connolly

We extend existing methods for using cross-correlations to derive redshift distributions for photometric galaxies, without using photometric redshifts. The model presented in this paper simultaneously yields highly accurate and unbiased…

Cosmology and Nongalactic Astrophysics · Physics 2018-03-07 Marcel P. van Daalen , Martin White

Combining redshift and galaxy shape information offers new exciting ways of exploiting the gravitational lensing effect for studying the large scales of the cosmos. One application is the three-dimensional reconstruction of the matter…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-13 Patrick Simon , Andy Taylor , Jan Hartlap

We present a Bayesian reconstruction method which maps a galaxy distribution from redshift-space to real-space inferring the distances of the individual galaxies. The method is based on sampling density fields assuming a lognormal prior…

We measured the bias and correlation factor of galaxies with respect to the dark matter using the aperture statistics including the aperture mass from weak gravitational lensing. The analysis was performed for three galaxy samples selected…

The dark sirens method combines gravitational waves and catalogs of galaxies to constrain the cosmological expansion history, merger rates and mass distributions of compact objects, and the laws of gravity. However, the incompleteness of…

Cosmology and Nongalactic Astrophysics · Physics 2024-12-09 Konstantin Leyde , Tessa Baker , Wolfgang Enzi

We study whether the bias factors of galaxies can be unbiasedly recovered from their power spectra and bispectra. We use a set of numerical N-body simulations and construct large mock galaxy catalogs based upon the semi-analytical model of…

Cosmology and Nongalactic Astrophysics · Physics 2009-08-17 Hong Guo , Y. P. Jing

The clustering of matter on cosmological scales is an essential probe for studying the physical origin and composition of our Universe. To date, most of the direct studies have focused on shear-shear weak lensing correlations, but it is…

Cosmology and Nongalactic Astrophysics · Physics 2010-07-26 Tobias Baldauf , Robert E. Smith , Uros Seljak , Rachel Mandelbaum

The counts-in-cells (CIC) galaxy probability distribution depends on both the dark matter clustering amplitude $\sigma_8$ and the galaxy bias $b$. We present a theory for the CIC distribution based on a previous prescription of the…

Cosmology and Nongalactic Astrophysics · Physics 2020-09-02 Andrew Repp , István Szapudi

We describe a new, non-parametric, method for reconstructing lensing mass distributions in multiple-image systems, and apply it to PG1115, for which time delays have recently been measured. It turns out that the image positions and the…

Astrophysics · Physics 2015-06-24 Prasenjit Saha , Liliya L. R. Williams

We develop a method for performing a weak lensing analysis using only measurements of galaxy position angles. By analysing the statistical properties of the galaxy orientations given a known intrinsic ellipticity distribution, we show that…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-17 Lee Whittaker , Michael L. Brown , Richard Battye

We present a general expression for a lognormal filter given an arbitrary nonlinear galaxy bias. We derive this filter as the maximum a posteriori solution assuming a lognormal prior distribution for the matter field with a given mean field…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-14 Francisco S. Kitaura , Jens Jasche , R. Benton Metcalf

We present a new method that simultaneously solves for cosmology and galaxy bias on non-linear scales. The method uses the halo model to analytically describe the (non-linear) matter distribution, and the conditional luminosity function…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-05 Frank van den Bosch , Surhud More , Marcello Cacciato , Houjun Mo , Xiaohu Yang
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