Reconstructing the cosmological density and velocity fields from redshifted galaxy distributions using V-net

F Qin, D Parkinson, SE Hong… - Journal of Cosmology and …, 2023 - iopscience.iop.org
The distribution of matter that is measured through galaxy redshift and peculiar velocity
surveys can be harnessed to learn about the physics of dark matter, dark energy, and the …

Autodifferentiable likelihood pipeline for the cross-correlation of CMB and large-scale structure due to the kinetic Sunyaev-Zeldovich effect

Y Kvasiuk, M Münchmeyer - Physical Review D, 2024 - APS
We develop an optimization-based maximum likelihood approach to analyze the cross-
correlation of the cosmic microwave background (CMB) and large-scale structure induced …

Local Primordial Non-Gaussian Bias at the Field Level

JM Sullivan, SF Chen - arXiv preprint arXiv:2410.18039, 2024 - arxiv.org
Local primordial non-Gaussianity (LPNG) couples long-wavelength cosmological
fluctuations to the short-wavelength behavior of galaxies. This coupling is encoded in bias …

Massive s through the CNN lens: interpreting the field-level neutrino mass information in weak lensing

M Golshan, AE Bayer - arXiv preprint arXiv:2410.00914, 2024 - arxiv.org
Modern cosmological surveys probe the Universe deep into the nonlinear regime, where
massive neutrinos suppress cosmic structure. Traditional cosmological analyses, which use …

On the Detectability of the Moving Lens Signal in CMB Experiments

SC Hotinli, E Pierpaoli - arXiv preprint arXiv:2401.12280, 2024 - arxiv.org
Upcoming cosmic microwave background (CMB) experiments are expected to detect new
signals probing interaction of CMB photons with intervening large-scale structure. Among …

[图书][B] Towards an Optimal Cosmological Detection of Neutrino Mass with Bayesian Inference

AE Bayer - 2023 - search.proquest.com
High-precision measurements of large-scale cosmic structure are expected to revolutionize
our understanding of fundamental physics, for example by the quantifying neutrino mass …

[PDF][PDF] Joint cosmological parameter inference and initial condition reconstruction with Stochastic Interpolants

C Cuesta-Lazaro, AE Bayer, MS Albergo… - ml4physicalsciences.github.io
In this work, we present a unified approach to cosmological parameter inference and initial
condition reconstruction using Stochastic Interpolants and normalizing flows. We apply this …

[PDF][PDF] Bayesian inference for cosmology: Inferring initial conditions of the local cosmic web

P CHAINAIS, J SORCE, PA THOUVENIN - madics.fr
1 uncertainty quantification. This motivates the use of Markov chain Monte-Carlo (MCMC)
algorithms to access posterior distributions. The hierarchical model relies on a costly …