Related papers: Distinguishing Orbiting and Infalling Dark Matter …
Dark matter haloes have long been recognized as one of the fundamental building blocks of large scale structure formation models. Despite their importance -- or perhaps because of it! -- halo definitions continue to evolve towards more…
The density profiles of dark matter haloes can potentially probe dynamics, fundamental physics, and cosmology, but some of the most promising signals reside near or beyond the virial radius. While these scales have recently become…
The properties of the matter density field in the initial conditions have a decisive impact on the features of the large-scale structure of the Universe as observed today. These need to be studied via $N$-body simulations, which are…
The simple, conventional dark matter halo mass definitions commonly used in cosmological simulations ("virial" mass, FoF mass, $M_{50,100,200,...}$) only capture part of the collapsed material and are therefore inconsistent with the halo…
We train a machine learning algorithm to learn cosmological structure formation from N-body simulations. The algorithm infers the relationship between the initial conditions and the final dark matter haloes, without the need to introduce…
We present a deep-learning-based approach for identifying dark matter haloes in cosmological N-body simulations. Our framework consists of a volumetric Convolutional Neural Network to classify individual simulation particles as either halo…
Despite the Milky Way's proximity to us, our knowledge of its dark matter halo is fairly limited, and there is still considerable uncertainty in its halo mass. Many past techniques have been limited by assumptions such as the Galaxy being…
We show that most particle and subhalo orbits in simulated cosmological cold dark matter halos are surprisingly regular and periodic: The phase space structure of the outer halo regions shares some of the properties of the classical…
We measure the clustering of dark matter halos in a large set of collisionless cosmological simulations of the flat LCDM cosmology. Halos are identified using the spherical overdensity algorithm, which finds the mass around isolated peaks…
The spectrum of cold dark matter particles on Earth is expected to have peaks in velocity space associated with particles which are falling onto the Galaxy for the first time and with particles which have fallen in and out of the Galaxy…
We examine the properties of dark matter halos within a rich galaxy cluster using a high resolution simulation that captures the cosmological context of a cold dark matter universe. The mass and force resolution permit the resolution of 150…
We investigate the possibility of applying machine learning techniques to images of strongly lensed galaxies to detect a low mass cut-off in the spectrum of dark matter sub-halos within the lens system. We generate lensed images of systems…
The balance of evidence indicates that individual galaxies and groups or clusters of galaxies are embedded in enormous distributions of cold, weakly interacting dark matter. These dark matter 'halos' provide the scaffolding for all luminous…
For many analyses in cosmology it is necessary to reconstruct the likely distribution of unobserved fields, such as dark matter or non-luminous baryons, from observed luminous tracers. The dominant approach in cosmology has been to use the…
The evolution of a dark matter halo in a dark matter only simulation is governed purely byNewtonian gravity, making a clean testbed to determine what halo properties drive its fate.Using machine learning, we predict the survival, mass loss,…
Dark matter haloes form from small perturbations to the almost homogeneous density field of the early universe. Although it is known how large these initial perturbations must be to form haloes, it is rather poorly understood how to predict…
We present a pedagogical review of the halo model, a flexible framework that can describe the distribution of matter and its tracers on non-linear scales for both conventional and exotic cosmological models. We start with the premise that…
Accurate modelling of the one-to-two halo transition has long been difficult to achieve. We demonstrate that physically motivated halo definitions that respect the bimodal phase-space distribution of dark matter particles near halos…
We investigate unbound dark matter particles in halos by tracing particle trajectories in a simulation run to the far future (a = 100). We find that the traditional sum of kinetic and potential energies is a very poor predictor of which…
We present a new exploratory framework to model galaxy formation and evolution in a hierarchical universe by using machine learning (ML). Our motivations are two-fold: (1) presenting a new, promising technique to study galaxy formation, and…