相关论文: The BACCO Simulation Project: A baryonification em…
We utilize the Magneticum suite of state-of-the-art hydrodynamical, as well as dark-matter-only simulations to investigate the effects of baryonic physics on cosmic voids in the highest-resolution study of its kind. This includes the size,…
We generalize the `renormalized' perturbation theory (RPT) formalism of Crocce & Scoccimarro (2006a) to deal with multiple fluids in the Universe and here we present calculations up to the one-loop level. We apply the approach to the…
We present the Aemulus $\nu$ simulations: a suite of 150 $(1.05 h^{-1}\rm Gpc)^3$ $N$-body simulations with a mass resolution of $3.51\times 10^{10} \frac{\Omega_{cb}}{0.3} ~ h^{-1} M_{\odot}$ in a $w\nu$CDM cosmological parameter space.…
We present an analysis of the effects of baryon physics on the halo mass function. The analysis is based on simulations of a cosmological volume. Besides a Dark Matter (DM) only simulation, we also carry out two other hydrodynamical…
Precision measurements of the large scale structure of the Universe require large numbers of high fidelity mock catalogs to accurately assess, and account for, the presence of systematic effects. We introduce and test a scheme for…
We study the robustness of the Baryon Acoustic Oscillation (BAO) feature in galaxy clustering in the presence of massive neutrinos. In the standard BAO analysis pipeline a reference cosmological model is assumed to boost the BAO peak…
Constructing a general-purpose framework for mapping between dark matter simulations and observable hydrodynamical simulation outputs is a long-standing problem in modern astrophysics. In this work, we present a new approach utilizing…
The role of baryonic physics, star formation, and stellar feedback, in shaping the galaxies and their host halos is an evolving topic. The dark matter aspects are illustrated in this work by showing distribution features in a…
We present $\it{CosmoPower}$, a suite of neural cosmological power spectrum emulators providing orders-of-magnitude acceleration for parameter estimation from two-point statistics analyses of Large-Scale Structure (LSS) and Cosmic Microwave…
Cosmological constraints on the sum of neutrino masses and on the effective number of neutrino species in standard and non-standard scenarios are computed using the most recent available cosmological data. Our cosmological data sets include…
To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables.…
In this paper, we use The Quijote simulations in order to extract the cosmological parameters through Bayesian Neural Networks. This kind of model has a remarkable ability to estimate the associated uncertainty, which is one of the ultimate…
The linear matter power spectrum is an essential ingredient in all theoretical models for interpreting large-scale-structure observables. Although Boltzmann codes such as CLASS or CAMB are very efficient at computing the linear spectrum,…
Cosmological constraints derived from weak lensing (WL) surveys are limited by baryonic effects, which suppress the non-linear matter power spectrum on small scales. By combining WL measurements with data from external tracers of the gas…
Optimal transport theory has recently reemerged as a vastly resourceful field of mathematics with elegant applications across physics and computer science. Harnessing methods from geometry processing, we report on the efficient…
A covariant energy density functional is calibrated using a principled Bayesian statistical framework informed by experimental binding energies and charge radii of several magic and semi-magic nuclei. The Bayesian sampling required for the…
Based on a suite of state-of-the-art high-resolution $N$-body simulations, we revisit the so-called halofit model (Smith et al. 2003) as an accurate fitting formula for the nonlinear matter power spectrum. While the halofit model has been…
We study the capacity of Bayesian Neural Networks (BNNs) to detect new physics in the dark matter power spectrum. As in previous studies, the Bayesian Cosmological Network (BaCoN) classifies spectra into one of 5 classes: $\Lambda$CDM,…
Near-future cosmological observations targeted at investigations of dark energy pose stringent requirements on the accuracy of theoretical predictions for the clustering of matter. Currently, N-body simulations comprise the only viable…
Galaxy clustering and galaxy-galaxy lensing are two of the main observational probes in Stage-IV large-scale structure surveys. Unfortunately, the complicated relationship between galaxies and matter limits the exploitation of this data.…