Feature detection in the primordial power spectrum with LSS reconstructions based on Bayesian inference

Guillermo Martínez Somonte; Airam Marcos Caballero; Enrique Martínez González

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Conference object . 2022

License: CC BY

Data sources: Datacite

ZENODO

Conference object . 2022

License: CC BY

Data sources: Datacite

ZENODO

Other literature type . 2022

License: CC BY

Data sources: ZENODO

Feature detection in the primordial power spectrum with LSS reconstructions based on Bayesian inference

descriptionPublicationkeyboard_double_arrow_right Conference object , Other literature type 04 Sep 2022 English Publisher:Zenodo

Authors: Guillermo Martínez Somonte; Airam Marcos Caballero; Enrique Martínez González;

doi: 10.5281/zenodo.7048523 , 10.5281/zenodo.7048524

Feature detection in the primordial power spectrum with LSS reconstructions based on Bayesian inference

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Abstract

In this poster we collect the ongoing results of reconstructing through a bayesian-inference non-parametric model the primordial power spectrum of simulated LSS catalogues. These catalogues have been simulated according to a different feature models, departing from the standard-model predicted power law.

Related Organizations

Spanish National Research Council
Spain

Keywords

Primordial Power Spectrum, Bayesian Inference, Inflationary features in primordial observables, Multi-nest sampling, Non-parametric reconstruction, Cosmology

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