相关论文: Towards Accurate Field-Level Inference of Massive …
Forthcoming large galaxy cluster surveys will yield tight constraints on cosmological models. It has been shown that in an idealized survey, containing > 10,000 clusters, statistical errors on dark energy and other cosmological parameters…
We use cosmological gas dynamic simulations to investigate the accuracy of galaxy cluster mass estimates based on X-ray observations. The experiments follow the formation of clusters in different cosmological models and include the effects…
We present a set-based machine learning framework that infers posterior distributions of galaxy cluster masses from projected galaxy dynamics. Our model combines Deep Sets and conditional normalizing flows to incorporate both positional and…
Precise determination of galaxy cluster masses is crucial for establishing reliable mass-observable scaling relations in cluster cosmology. We employ graph neural networks (GNNs) to estimate galaxy cluster masses from radially sampled…
In the $\Lambda$CDM paradigm, the masses of the galaxy clusters inferred using background galaxies via weak-lensing shear should agree with the masses measured using the galaxy projected radius-velocity phase-space data via the escape…
One emerging application of machine learning methods is the inference of galaxy cluster masses. In this note, machine learning is used to directly combine five simulated multiwavelength measurements in order to find cluster masses. This is…
Bayesian clustering typically relies on mixture models, with each component interpreted as a different cluster. After defining a prior for the component parameters and weights, Markov chain Monte Carlo (MCMC) algorithms are commonly used to…
The formation, inner properties, and spatial distribution of galaxy groups and clusters are closely related to the background cosmological model. We use numerical simulations of variants of the CDM model with different cosmological…
Comparison of peculiar velocities of galaxies with their gravitational accelerations (induced by the density field) is one of the methods to constrain the redshift distortion parameter \beta=(\Omega_m^0.55)/b, where \Omega_m is the…
Cosmological inference from cluster number counts is systematically limited by the accuracy of the mass calibration, i.e. the empirical determination of the mapping between cluster selection observables and halo mass. In this work we…
Clusters of galaxies are powerful cosmological probes, particularly if their masses can be determined. One possibility for mass determination is to study the cosmic microwave background (CMB) on small angular scales and observe deviations…
We present a Bayesian inference approach to estimating the cumulative mass profile and mean squared velocity profile of a globular cluster given the spatial and kinematic information of its stars. Mock globular clusters with a range of…
Weak gravitational lensing has been used extensively in the past decade to constrain the masses of galaxy clusters, and is the most promising observational technique for providing the mass calibration necessary for precision cosmology with…
We implement an adaptation of the COLA approach, a hybrid scheme that combines Lagrangian perturbation theory with an N-body approach, to model non-linear collapse in chameleon and symmetron modified gravity models. Gravitational screening…
Gravitational lensing by massive galaxy clusters distorts the observed cosmic microwave background (CMB) on arcminute scales, and these distortions carry information about cluster masses. Standard approaches to extracting cluster mass…
We present optimal Bayesian field-level cosmological constraints from nonlinear tracers of the large-scale structure, specifically the amplitude $\sigma_8$ of linear matter fluctuations inferred from rest-frame simulated dark matter halos…
We study the efficiency and reliability of cluster mass estimators that are based on the projected phase-space distribution of galaxies in a cluster region. To this aim, we analyse a data-set of 62 clusters extracted from a concordance LCDM…
We present the first simulation-based inference (SBI) of cosmological parameters from field-level analysis of galaxy clustering. Standard galaxy clustering analyses rely on analyzing summary statistics, such as the power spectrum, $P_\ell$,…
Cosmology inference of galaxy clustering at the field level with the EFT likelihood in principle allows for extracting all non-Gaussian information from quasi-linear scales, while robustly marginalizing over any astrophysical uncertainties.…
The mass measurement of galaxy clusters is an important tool for the determination of cosmological parameters describing the matter and energy content of the Universe. However, the standard methods rely on various assumptions about the…