Baryonic feedback and intrinsic alignments in profile: a frequentist view of DES Y3 cosmic shear

Current cosmic shear surveys primarily constrain $S_8$ and $Ω_\mathrm{m}$, while most other model parameters remain dominated by priors. Consequently, marginal posteriors are vulnerable to prior-volume effects, particularly through degeneracies among $S_8$, baryonic feedback, and intrinsic alignment (IA) model parameters. To isolate data-driven constraints from prior volume effects, we compare profile likelihoods with Bayesian posteriors for DES Y3 cosmic shear under the DES Y3+KiDS-1000 Hybrid model. For cosmic shear alone, the profile global best fit and the marginal posterior mean agree in $S_8$, but the profile likelihood reveals a strong degeneracy between feedback strength and $S_8$, leaving the upper $1σ$ limit on $S_8$ determined by the assumed feedback range. External CMB information on parameters other than $Ω_\mathrm{m}$ and $S_8$ breaks this degeneracy, suppressing prior-volume effects and reconciling the profiles with the posteriors. With CMB data included, small-scale cosmic shear data prefers moderate baryonic feedback strengths consistent with hydrodynamical simulations calibrated to observed gas fractions. Furthermore, additional unconstrained parameters in the tidal alignment and tidal torquing (TATT) model result in weaker constraints, shifting and broadening the $S_8$ profile relative to the nonlinear linear alignment (NLA) model. Adding DES Y3 shear ratios mitigates this degeneracy, bringing profile likelihood and marginal posteriors into close agreement.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-02
DOI
https://doi.org/10.48550/arxiv.2611.03537
Primary Topic
Cosmology and Gravitation Theories
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Baryonic feedback and intrinsic alignments in profile: a frequentist view of DES Y3 cosmic shear

Anoma Ganguly, Tanvi Karwal, E. Krause, Vivian Miranda
arXiv (Cornell University)
Cosmology and Gravitation Theories
preprint

Baryonic feedback and intrinsic alignments in profile: a frequentist view of DES Y3 cosmic shear

Anoma Ganguly, Tanvi Karwal, E. Krause, Vivian Miranda
preprint en

Abstract

Current cosmic shear surveys primarily constrain $S_8$ and $Ω_\mathrm{m}$, while most other model parameters remain dominated by priors. Consequently, marginal posteriors are vulnerable to prior-volume effects, particularly through degeneracies among $S_8$, baryonic feedback, and intrinsic alignment (IA) model parameters. To isolate data-driven constraints from prior volume effects, we compare profile likelihoods with Bayesian posteriors for DES Y3 cosmic shear under the DES Y3+KiDS-1000 Hybrid model. For cosmic shear alone, the profile global best fit and the marginal posterior mean agree in $S_8$, but the profile likelihood reveals a strong degeneracy between feedback strength and $S_8$, leaving the upper $1σ$ limit on $S_8$ determined by the assumed feedback range. External CMB information on parameters other than $Ω_\mathrm{m}$ and $S_8$ breaks this degeneracy, suppressing prior-volume effects and reconciling the profiles with the posteriors. With CMB data included, small-scale cosmic shear data prefers moderate baryonic feedback strengths consistent with hydrodynamical simulations calibrated to observed gas fractions. Furthermore, additional unconstrained parameters in the tidal alignment and tidal torquing (TATT) model result in weaker constraints, shifting and broadening the $S_8$ profile relative to the nonlinear linear alignment (NLA) model. Adding DES Y3 shear ratios mitigates this degeneracy, bringing profile likelihood and marginal posteriors into close agreement.

arXiv (Cornell University)
Cosmology and Gravitation Theories
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.

Laika access coming soon