Can we actually constrain $f_NL$ using the scale-dependent bias
effect? An illustration of the impact of galaxy bias uncertainties using the
BOSS DR12 galaxy power spectrum
The scale-dependent bias effect on the galaxy power spectrum is a very
promising probe of the local primordial non-Gaussianity (PNG) parameter $f_\rm
NL$, but the amplitude of the effect is proportional to $f_NLb_\phi$,
where $b_\phi$ is the linear PNG galaxy bias parameter. Our knowledge of
$b_\phi$ is currently very limited, yet nearly all existing $f_NL$
constraints and forecasts assume precise knowledge for it. Here, we use the
BOSS DR12 galaxy power spectrum to illustrate how our uncertain knowledge of
$b_\phi$ currently prevents us from constraining $f_NL$ with a given
statistical precision $\sigma_f_NL$. Assuming different fixed choices
for the relation between $b_\phi$ and the linear density bias $b_1$, we find
that $\sigma_f_NL$ can vary by as much as an order of magnitude. Our
strongest bound is $f_NL = 16 16\ (1\sigma)$, while the loosest is
$f_NL = 230 226\ (1\sigma)$ for the same BOSS data. The impact of
$b_\phi$ can be especially pronounced because it can be close to zero. We
also show how marginalizing over $b_\phi$ with wide priors is not
conservative, and leads in fact to biased constraints through parameter space
projection effects. Independently of galaxy bias assumptions, the
scale-dependent bias effect can only be used to detect $f_NL 0$ by
constraining the product $f_NLb_\phi$, but the error bar
$\sigma_f_NL$ remains undetermined and the results cannot be compared
with the CMB; we find $f_NLb_\phi 0$ with $1.6\sigma$
significance. We also comment on why these issues are important for analyses
with the galaxy bispectrum. Our results strongly motivate simulation-based
research programs aimed at robust theoretical priors for the $b_\phi$
parameter, without which we may never be able to competitively constrain
$f_NL$ using galaxy data.
Описание
Can we actually constrain $f_{\rm NL}$ using the scale-dependent bias effect? An illustration of the impact of galaxy bias uncertainties using the BOSS DR12 galaxy power spectrum
%0 Generic
%1 barreira2022actually
%A Barreira, Alexandre
%D 2022
%K tifr
%T Can we actually constrain $f_NL$ using the scale-dependent bias
effect? An illustration of the impact of galaxy bias uncertainties using the
BOSS DR12 galaxy power spectrum
%U http://arxiv.org/abs/2205.05673
%X The scale-dependent bias effect on the galaxy power spectrum is a very
promising probe of the local primordial non-Gaussianity (PNG) parameter $f_\rm
NL$, but the amplitude of the effect is proportional to $f_NLb_\phi$,
where $b_\phi$ is the linear PNG galaxy bias parameter. Our knowledge of
$b_\phi$ is currently very limited, yet nearly all existing $f_NL$
constraints and forecasts assume precise knowledge for it. Here, we use the
BOSS DR12 galaxy power spectrum to illustrate how our uncertain knowledge of
$b_\phi$ currently prevents us from constraining $f_NL$ with a given
statistical precision $\sigma_f_NL$. Assuming different fixed choices
for the relation between $b_\phi$ and the linear density bias $b_1$, we find
that $\sigma_f_NL$ can vary by as much as an order of magnitude. Our
strongest bound is $f_NL = 16 16\ (1\sigma)$, while the loosest is
$f_NL = 230 226\ (1\sigma)$ for the same BOSS data. The impact of
$b_\phi$ can be especially pronounced because it can be close to zero. We
also show how marginalizing over $b_\phi$ with wide priors is not
conservative, and leads in fact to biased constraints through parameter space
projection effects. Independently of galaxy bias assumptions, the
scale-dependent bias effect can only be used to detect $f_NL 0$ by
constraining the product $f_NLb_\phi$, but the error bar
$\sigma_f_NL$ remains undetermined and the results cannot be compared
with the CMB; we find $f_NLb_\phi 0$ with $1.6\sigma$
significance. We also comment on why these issues are important for analyses
with the galaxy bispectrum. Our results strongly motivate simulation-based
research programs aimed at robust theoretical priors for the $b_\phi$
parameter, without which we may never be able to competitively constrain
$f_NL$ using galaxy data.
@misc{barreira2022actually,
abstract = {The scale-dependent bias effect on the galaxy power spectrum is a very
promising probe of the local primordial non-Gaussianity (PNG) parameter $f_{\rm
NL}$, but the amplitude of the effect is proportional to $f_{\rm NL}b_{\phi}$,
where $b_{\phi}$ is the linear PNG galaxy bias parameter. Our knowledge of
$b_{\phi}$ is currently very limited, yet nearly all existing $f_{\rm NL}$
constraints and forecasts assume precise knowledge for it. Here, we use the
BOSS DR12 galaxy power spectrum to illustrate how our uncertain knowledge of
$b_{\phi}$ currently prevents us from constraining $f_{\rm NL}$ with a given
statistical precision $\sigma_{f_{\rm NL}}$. Assuming different fixed choices
for the relation between $b_{\phi}$ and the linear density bias $b_1$, we find
that $\sigma_{f_{\rm NL}}$ can vary by as much as an order of magnitude. Our
strongest bound is $f_{\rm NL} = 16 \pm 16\ (1\sigma)$, while the loosest is
$f_{\rm NL} = 230 \pm 226\ (1\sigma)$ for the same BOSS data. The impact of
$b_{\phi}$ can be especially pronounced because it can be close to zero. We
also show how marginalizing over $b_{\phi}$ with wide priors is not
conservative, and leads in fact to biased constraints through parameter space
projection effects. Independently of galaxy bias assumptions, the
scale-dependent bias effect can only be used to detect $f_{\rm NL} \neq 0$ by
constraining the product $f_{\rm NL}b_{\phi}$, but the error bar
$\sigma_{f_{\rm NL}}$ remains undetermined and the results cannot be compared
with the CMB; we find $f_{\rm NL}b_{\phi} \neq 0$ with $1.6\sigma$
significance. We also comment on why these issues are important for analyses
with the galaxy bispectrum. Our results strongly motivate simulation-based
research programs aimed at robust theoretical priors for the $b_{\phi}$
parameter, without which we may never be able to competitively constrain
$f_{\rm NL}$ using galaxy data.},
added-at = {2022-05-12T09:02:32.000+0200},
author = {Barreira, Alexandre},
biburl = {https://www.bibsonomy.org/bibtex/2b39b2d51a03b8190c44a91eea0daa4f2/citekhatri},
description = {Can we actually constrain $f_{\rm NL}$ using the scale-dependent bias effect? An illustration of the impact of galaxy bias uncertainties using the BOSS DR12 galaxy power spectrum},
interhash = {2f44456f340ad1dc98deef79884545c8},
intrahash = {b39b2d51a03b8190c44a91eea0daa4f2},
keywords = {tifr},
note = {cite arxiv:2205.05673Comment: 15 pages, 6 figures, 3 tables. Comments welcomed!},
timestamp = {2022-05-12T09:02:32.000+0200},
title = {Can we actually constrain $f_{\rm NL}$ using the scale-dependent bias
effect? An illustration of the impact of galaxy bias uncertainties using the
BOSS DR12 galaxy power spectrum},
url = {http://arxiv.org/abs/2205.05673},
year = 2022
}