Related papers: A deep-learning algorithm to disentangle self-inte…
Motivated by the collisionless cold dark matter small scale structure problem, we propose an asymmetric dark matter model where dark matter particle interact with each other via a massive dark gauge boson. This model easily avoid the strong…
Strong gravitational lensing is a promising probe of the substructure of dark matter halos. Deep learning methods have the potential to accurately identify images containing substructure, and differentiate WIMP dark matter from other well…
(Abridged) We compare recent results from X-ray, strong lensing, weak lensing, and optical observations with numerical simulations of the merging galaxy cluster 1E0657-56. X-ray observations reveal a bullet-like subcluster with a prominent…
Images from the next generation of telescopes will enable strikingly detailed reconstruction of the dark matter distributions in galaxy cluster cores using strong gravitational lensing analysis. This will provide a key test of Lambda-CDM…
We demonstrate that self-interacting dark matter models with interactions mediated by light particles can have significant deviations in the matter power-spectrum and detailed structure of galactic halos when compared to a standard cold…
The science behind galaxy interaction and mergers has a fundamental role and gives us an insight into galaxy formation and its evolution. Fluctuating angular momentum is responsible for extraordinary events like polar rings, tidal tails,…
Merging galaxy clusters present a unique opportunity to study the properties of dark matter in an astrophysical context. These are rare and extreme cosmic events in which the bulk of the baryonic matter becomes displaced from the dark…
While dark matter (DM) is the key ingredient for a successful theory of structure formation, its microscopic nature remains elusive. Indirect detection may provide a powerful test for some strongly motivated DM particle models.…
The spatial distribution of matter in clusters of galaxies is mainly determined by the dominant dark matter component, however, physical processes involving baryonic matter are able to modify it significantly. We analyse a set of 500 pc…
Self-Interacting Dark Matter (SIDM) has long been proposed as a solution to small scale problems posed by standard Cold Dark Matter (CDM). We use numerical simulations to study the effect of dark matter interactions on the morphology of…
Herein, we present a deep-learning technique for reconstructing the dark-matter density field from the redshift-space distribution of dark-matter halos. We built a UNet-architecture neural network and trained it using the COmoving…
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…
We calculate the radial profiles of galaxies where the nuclear region is self-gravitating, consisting of self-interacting dark matter (SIDM) with $F$ degrees of freedom. For sufficiently high density this dark matter becomes collisional,…
Gravitational lensing by galaxy clusters provides a powerful probe of the spatial distribution of dark matter and its microphysical properties. Strong and weak lensing constraints on the density profiles of subhalos and their truncation…
We present the results from combining machine learning with the profile likelihood fit procedure, using data from the Large Underground Xenon (LUX) dark matter experiment. This approach demonstrates reduction in computation time by a factor…
We revisited the decaying dark matter (DDM) model, in which one collisionless particle decays early into two collisionless particles, that are potentially dark matter particles today. The effect of DDM will be manifested in the cosmic…
Terrestrial particle accelerators collide charged particles, then watch the trajectory of outgoing debris - but they cannot manipulate dark matter. Fortunately, dark matter is the main component of galaxy clusters, which are continuously…
We probe the self-interactions of dark matter using observational data of relaxed galaxy groups and clusters. Our analysis uses the Jeans formalism and considers a wider range of systematic effects than in previous work, including adiabatic…
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…
We use the "Evolution and Assembly of GaLaxies and their Environments" ( EAGLE ) suite of hydrodynamical cosmological simulations to measure offsets between the centres of stellar and dark matter components of galaxies. We find that the…