# Bayesian inference of cosmic density fields from non-linear, scale-dependent, and stochastic biased tracers

@article{Ata2014BayesianIO, title={Bayesian inference of cosmic density fields from non-linear, scale-dependent, and stochastic biased tracers}, author={Metin Ata and Francisco-Shu Kitaura and Volker Muller}, journal={Monthly Notices of the Royal Astronomical Society}, year={2014}, volume={446}, pages={4250-4259} }

We present a Bayesian reconstruction algorithm to generate unbiased samples of the underlying dark matter field from galaxy redshift data. Our new con tribution consists of implementing a non-Poisson likelihood including a deterministic non-linear and scale-dependent bias. In particular we present the Hamiltonian equations of motions for the negative binomial (NB) probability distribution function. This permits us to efficiently sample the posterior distribution function of density fields given…

## 42 Citations

### Bayesian cosmic density field inference from redshift space dark matter maps.

- PhysicsMonthly notices of the Royal Astronomical Society
- 2019

Novel algorithmic implementations are introduced regarding the mass assignment kernels when defining the dark matter density field and optimization of the time-step in the Hamiltonian equations of motions and the resulting reconstructed fields are isotropic and their power spectra are unbiased compared to the true field defined by the authors' mock observations.

### Cosmology inference from a biased density field using the EFT-based likelihood

- PhysicsJournal of Cosmology and Astroparticle Physics
- 2020

The effective-field-theory (EFT) approach to the clustering of galaxies and other biased tracers allows for an isolation of the cosmological information that is protected by symmetries, in particular…

### Physical Bayesian modelling of the non-linear matter distribution: New insights into the nearby universe

- PhysicsAstronomy & Astrophysics
- 2019

Accurate analyses of present and next-generation cosmological galaxy surveys require new ways to handle effects of non-linear gravitational structure formation processes in data. To address these…

### A rigorous EFT-based forward model for large-scale structure

- PhysicsJournal of Cosmology and Astroparticle Physics
- 2019

Conventional approaches to cosmology inference from galaxy redshift surveys are based on n-point functions, which are under rigorous perturbative control on sufficiently large scales. Here, we…

### Approximate Bayesian computation in large-scale structure : constraining the galaxy-halo connection

- Computer Science, Physics
- 2017

This work demonstrates that ABC is feasible for LSS parameter inference by using it to constrain parameters of the halo occupation distribution (HOD) model for populating dark matter halos with galaxies and suggests that ABC can and should be applied in parameter inference for L SS analyses.

### Joint constraints on galaxy bias and σ8 through the N-pdf of the galaxy number density

- Physics
- 2015

We present a full description of the N-probability density function of the galaxy number density fluctuations. This N-pdf is given in terms, on the one hand, of the cold dark matter correlations and,…

### cosmic birth: efficient Bayesian inference of the evolving cosmic web from galaxy surveys

- Physics
- 2019

We present COSMIC BIRTH: COSMological Initial Conditions from Bayesian Inference Reconstructions with THeoretical models: an algorithm to reconstruct the primordial and evolved cosmic density fields…

### Past and present cosmic structure in the SDSS DR7 main sample

- Physics
- 2014

We present a chrono-cosmography project, aiming at the inference of the four dimensional formation history of the observed large scale structure from its origin to the present epoch. To do so, we…

### A novel estimator for the equation of state of the IGM by Ly α forest tomography

- Mathematics
- 2021

We present a novel procedure to estimate the Equation of State of the intergalactic medium in the quasi-linear regime of structure formation based on Ly$\alpha$ forest tomography and apply it to 31…

### The EFT likelihood for large-scale structure

- Computer ScienceJournal of Cosmology and Astroparticle Physics
- 2020

This work derives, using functional methods and the bias expansion, the conditional likelihood for observing a specific tracer field given an underlying matter field and rigorously derives the corrections to this result, such as those coming from a non-Gaussian stochasticity and higher-derivative terms.

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