相关论文: Estimating galaxy masses from kinematics of globul…
We investigate the ability of machine learning to infer the virial mass ($M_{\rm vir}$) and the scale radius ($r_{\rm s}$) of galaxy clusters from their observables. Using the Uchuu--UniverseMachine galaxy catalog at $z=0.093$, we generate…
The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…
We present a modern machine learning approach for cluster dynamical mass measurements that is a factor of two improvement over using a conventional scaling relation. Different methods are tested against a mock cluster catalog constructed…
We present a new application of deep learning to reconstruct the cosmic microwave background (CMB) temperature maps from the images of microwave sky, and to use these reconstructed maps to estimate the masses of galaxy clusters. We use a…
The dynamics of globular cluster systems (GCSs) around galaxies are often used to assess the total enclosed mass, and even to constrain the dark matter distribution. The globular cluster system of a galaxy is typically assumed to be in…
The vast quantity of strong galaxy-galaxy gravitational lenses expected by future large-scale surveys necessitates the development of automated methods to efficiently model their mass profiles. For this purpose, we train an approximate…
Maps of cosmic structure produced by galaxy surveys are one of the key tools for answering fundamental questions about the Universe. Accurate theoretical predictions for these quantities are needed to maximize the scientific return of these…
We train deep learning models on thousands of galaxy catalogues from the state-of-the-art hydrodynamic simulations of the CAMELS project to perform regression and inference. We employ Graph Neural Networks (GNNs), architectures designed to…
We collected radial velocities of more than 50.000 individual stars in 156 Galactic globular clusters (GGC) and matched them with HST photometry and Gaia DR2 proper motions. This allowed us to derive the GGC's mean proper motions and space…
We present a new application of deep learning to infer the masses of galaxy clusters directly from images of the microwave sky. Effectively, this is a novel approach to determining the scaling relation between a cluster's Sunyaev-Zel'dovich…
Generative deep learning methods built upon Convolutional Neural Networks (CNNs) provide a great tool for predicting non-linear structure in cosmology. In this work we predict high resolution dark matter halos from large scale, low…
Galaxy clusters are important cosmological probes that have helped to establish the $\mathrm{\Lambda}$CDM paradigm as the standard model of cosmology. However, recent tensions between different types of high-accuracy data highlight the need…
We present a new method for estimating galaxy cluster masses using weak-lensing magnification. The effect of weak-lensing magnification introduces a correlation between the position of foreground galaxy clusters and the density of…
Globular clusters (GCs) are powerful tracers of the galaxy assembly process, and have already been used to obtain a detailed picture of the progenitors of the Milky Way. Using the E-MOSAICS cosmological simulation of a (34.4 Mpc)$^3$ volume…
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…
Context. Convolutional neural networks (CNNs) have been proven to perform fast classification and detection on natural images and have potential to infer astrophysical parameters on the exponentially increasing amount of sky survey imaging…
We explore the effectiveness of deep learning convolutional neural networks (CNNs) for estimating strong gravitational lens mass model parameters. We have investigated a number of practicalities faced when modelling real image data, such as…
The mass of a cluster of galaxies can be estimated from its lens magnification, which can be determined from the variation in number counts of background galaxies. In order to derive the mass one needs to make assumptions for the lens…
The relation between the total mass contained in the globular clusters of a galaxy and the mass of its dark matter halo has been found observationally to be nearly linear over five decades of mass. However, the high-mass end of this…
Magnetic fields play a crucial role in various astrophysical processes within the intracluster medium, including heat conduction, cosmic ray acceleration, and the generation of synchrotron radiation. However, measuring magnetic field…