相关论文: Deep Learning generated observations of galaxy clu…
This paper investigates the hierarchy of baryon physics assembly bias relations obtained from state-of-the-art hydrodynamic simulations with respect to the underlying cosmic web spanned by the dark matter field. Using the Bias Assignment…
We introduce the THE THREE HUNDRED project, an endeavour to model 324 large galaxy clusters with full-physics hydrodynamical re-simulations. Here we present the data set and study the differences to observations for fundamental galaxy…
DBSCAN* and HDBSCAN* are well established density based clustering algorithms. However, obtaining the clusters of very large datasets is infeasible, limiting their use in real world applications. By exploiting the geometry of Euclidean…
The $\Lambda$CDM model of structure formation makes strong predictions on concentration and shape of DM (dark matter) halos, which are determined by mass accretion processes. Comparison between predicted shapes and observations provides a…
We develop a machine learning (ML) framework to populate large dark matter-only simulations with baryonic galaxies. Our ML framework takes input halo properties including halo mass, environment, spin, and recent growth history, and outputs…
Galaxy cluster counts have historically been important for the measurement of cosmological parameters and upcoming surveys will greatly reduce the statistical errors. To exploit the potential of current and future cluster surveys,…
We have performed a series of simulations of clusters of galaxies on the basis of the smoothed particle hydrodynamics technique in a spatially-flat cold dark matter universe with $\Omega=0.3$, $\lambda=0.7$, and H_0=70 km/s/Mpc as one of…
Current efforts in observational cosmology are focused on characterizing the mass-energy content of the Universe. We present results from a geometric test based on strong lensing in galaxy clusters. Based on Hubble Space Telescope images…
We present a new method by which the total masses of galaxies including dark matter can be estimated from the kinematics of their globular cluster systems (GCSs). In the proposed method, we apply the convolutional neural networks (CNNs) to…
We present a simulation-based inference framework using a convolutional neural network to infer dynamical masses of galaxy clusters from their observed 3D projected phase-space distribution, which consists of the projected galaxy positions…
We use the IllustrisTNG cosmological hydrodynamical simulation to study the formation of ultra-diffuse galaxies (UDGs) in galaxy clusters. We supplement the simulations with a realistic mass-size relation for galaxies at the time of infall…
While cosmological dark matter-only simulations relying solely on gravitational effects are comparably fast to compute, baryonic properties in simulated galaxies require complex hydrodynamic simulations that are computationally costly to…
The galaxy luminosity function and galaxy stellar mass function are fundamental statistics in the testing of galaxy formation models. Theoretical predictions based on cosmological simulations can deviate from observations, especially at the…
We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure…
Whilst X-rays and Sunyaev-Zel'dovich observations allow to study the properties of the intra-cluster medium (ICM) of galaxy clusters, their gravitational potential may be constrained using strong gravitational lensing. Although being…
Galaxy groups are more than an intermediate scale between clusters and halos hosting individual galaxies, they are crucial laboratories capable of testing a range of astrophysics from how galaxies form and evolve to large scale structure…
This paper demonstrates that the stellar masses of galaxies in the Galaxy and Mass Assembly (GAMA) survey, originally derived via stellar population synthesis modelling, can be accurately predicted using only their absolute magnitudes and…
We explore galaxy properties and their link with environment and clustering using a population of ~1000 galaxies formed in a high resolution hydrodynamic simulation of the Lambda CDM cosmology. At the redshift we concentrate on, z=1, the…
Upcoming ground and space-based surveys are poised to illuminate low surface brightness tidal features, providing a new observable connection to dark matter physics. From imaging of tidal debris, the morphology of stellar streams can be…
Galaxy clusters offer powerful insights into the large-scale structure of the Universe and the physics of baryons in hot state. Their scientific exploitation, however, hinges on our ability to accurately measure key thermodynamic…