相关论文: Deep Learning generated observations of galaxy clu…
Upcoming 21cm surveys will map the spatial distribution of cosmic neutral hydrogen (HI) over very large cosmological volumes. In order to maximize the scientific return of these surveys, accurate theoretical predictions are needed.…
The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology. It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass…
We develop a machine learning algorithm to infer the 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel'dovich effect maps. We generate around 73,000 mock images along various lines of sight…
Observations of bright protoplanetary disks often show annular gaps in their dust emission. One interpretation of these gaps is disk-planet interaction. If so, fitting models of planetary gaps to observed protoplanetary disk gaps can reveal…
Numerical simulations have become a necessary tool to describe the complex interactions among the different processes involved in galaxy formation and evolution, unfeasible via an analytic approach. The last decade has seen a great effort…
For a complete picture of galaxy cluster formation, it is important that we start probing the early epoch of z~2-7 during which clusters and their galaxies first began to form. Because the study of these so-called "proto-clusters" is…
Forthcoming cosmological imaging surveys, such as the Rubin Observatory LSST, require large-scale simulations encompassing realistic galaxy populations for a variety of scientific applications. Of particular concern is the phenomenon of…
For a galaxy, given its observed rotation curve, can one directly infer parameters of the dark matter density profile (such as dark matter particle mass $m$, scaling parameter $s$, core-to-envelope transition radius $r_t$ and NFW scale…
We demonstrate the potential of Deep Learning methods for measurements of cosmological parameters from density fields, focusing on the extraction of non-Gaussian information. We consider weak lensing mass maps as our dataset. We aim for our…
Galaxy clusters are excellent probes to study the effect of environment on galaxy formation and evolution. Along with high-quality observational data, accurate cosmological simulations are required to improve our understanding of galaxy…
Using N-body+hydro simulations we study relations between the local environments of galaxies on 0.5 Mpc scale and properties of the luminous components of galaxies. Our numerical simulations include effects of star formation and supernova…
We propose a lightweight deep convolutional neural network (lCNN) to estimate cosmological parameters from simulated three-dimensional dark matter (DM) halo distributions and associated statistics. The training dataset comprises 2000…
We present the "DARKSKIES" suite of one hundred, zoom-in hydrodynamic simulations of massive ($M_{200}>5\times10^{14}{\rm M}_\odot)$ galaxy clusters with self-interacting dark matter (SIDM). We super-sample the simulations such that $m_{\rm…
Context: Several observations of the local Universe (LU) point towards the existence of very prominent structures. The presence of massive galaxy clusters and local super clusters on the one hand, but also large local voids and…
Machine learning is becoming a popular tool to quantify galaxy morphologies and identify mergers. However, this technique relies on using an appropriate set of training data to be successful. By combining hydrodynamical simulations,…
Cosmological simulations are powerful tools in the context of structure formation. They allow us to explore the assembly and clustering of dark matter halos, to validate or reject possible scenarios of structure formation, and to…
Strong gravitational lensing observations can test structure formation models by constraining the masses and concentrations of subhaloes in massive galaxy clusters. Recent work has concluded that cluster subhaloes are more abundant and/or…
Numerical simulations play an important role in current astronomy researches. Previous dark-matter-only simulations have represented the large-scale structure of the Universe. However, nowadays, hydro-dynamical simulations with baryonic…
The abundance and structure of dark matter subhalos has been analyzed extensively in recent studies of dark matter-only simulations, but comparatively little is known about the impact of baryonic physics on halo substructures. We here…
The analysis of optical images of galaxy-galaxy strong gravitational lensing systems can provide important information about the distribution of dark matter at small scales. However, the modeling and statistical analysis of these images is…