Optimal constraints on Primordial non-Gaussianity with the eBOSS DR16 quasars in Fourier space

Abstract We present constraints on the amplitude of local Primordial Non-Gaussianities (PNG), f NL , using the quasar sample in the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16). We analyze the power spectrum monopole, testing for the presence of scale-dependent galaxy bias induced by local PNG. Our analysis makes use of optimal redshift weights that maximize the response of the quasar sample to the possible presence of non-zero PNG. We find -4 < f NL < 27 at 68% confidence level, which is among the strongest bounds with Large Scale Structure data. The optimal analysis reduces the error bar by ~10% compared to the standard one, but this improvement is lower than the one expected from previous forecasts. In addition, the larger volume of this dataset, when compared to previous releases of the eBOSS quasar catalog, does not always correspond to a reduction of the final uncertainty on local PNG. This could suggest the presence of still unknown systematic effects in the data. If the quasars have a lower response to local PNG, our optimal constraint becomes -23 < f NL < 21 at 68%, with an improvement of 30% over standard analyses. We also show how to use the optimal weights to put data-driven priors on the sample's response to local PNG.

Authors

Institutions

Publication Details

Journal
Journal of Cosmology and Astroparticle Physics
Published
2024-08-01
DOI
https://doi.org/10.1088/1475-7516/2024/08/036
Citations
20
Primary Topic
Cosmology and Gravitation Theories
Type
article
Field-Weighted Citation Impact
6.30
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimal constraints on Primordial non-Gaussianity with the eBOSS DR16 quasars in Fourier space

D. Bianchi, Marco Bonici, M. S. Cagliari, Emanuele Castorina
20 citations
Journal of Cosmology and Astroparticle Physics
Cosmology and Gravitation Theories
6.30
article

Optimal constraints on Primordial non-Gaussianity with the eBOSS DR16 quasars in Fourier space

D. Bianchi, Marco Bonici, M. S. Cagliari, Emanuele Castorina
article en
20 citations

Abstract

Abstract We present constraints on the amplitude of local Primordial Non-Gaussianities (PNG), f NL , using the quasar sample in the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16). We analyze the power spectrum monopole, testing for the presence of scale-dependent galaxy bias induced by local PNG. Our analysis makes use of optimal redshift weights that maximize the response of the quasar sample to the possible presence of non-zero PNG. We find -4 < f NL < 27 at 68% confidence level, which is among the strongest bounds with Large Scale Structure data. The optimal analysis reduces the error bar by ~10% compared to the standard one, but this improvement is lower than the one expected from previous forecasts. In addition, the larger volume of this dataset, when compared to previous releases of the eBOSS quasar catalog, does not always correspond to a reduction of the final uncertainty on local PNG. This could suggest the presence of still unknown systematic effects in the data. If the quasars have a lower response to local PNG, our optimal constraint becomes -23 < f NL < 21 at 68%, with an improvement of 30% over standard analyses. We also show how to use the optimal weights to put data-driven priors on the sample's response to local PNG.

Journal of Cosmology and Astroparticle PhysicsVol. 2024(08)
University of Waterloo (CA), University of Milan (IT), Istituto Nazionale di Fisica Nucleare, Sezione di Milano (IT), National Institute for Astrophysics (IT)
Openalex Percentile: Top 3%
Cosmology and Gravitation Theories
6.30
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.