相关论文: A deep-learning algorithm to disentangle self-inte…
The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general…
Upcoming weak lensing surveys require a detailed theoretical understanding of the matter power spectrum in order to derive accurate and precise cosmological parameter values. While galaxy formation is known to play an important role, its…
Models of Cold Dark Matter predict that the distribution of dark matter in galaxy clusters should be cuspy, centrally concentrated. Constant density cores would be strong evidence for beyond-CDM physics, such as Self-Interacting Dark Matter…
Conventional galaxy mass estimation methods suffer from model assumptions and degeneracies. Machine learning, which reduces the reliance on such assumptions, can be used to determine how well present-day observations can yield predictions…
This work aims at assessing the impact of DM self-interactions on the properties of galaxy clusters. In particular, the goal is to study the angular dependence of the cross section by testing rare (large angle scattering) and frequent…
We present a novel method to infer the Dark Matter (DM) content and spatial distribution within galaxies, based on convolutional neural networks trained within state-of-the-art hydrodynamical simulations (Illustris TNG100). The framework we…
We perform numerical simulations of the merging galaxy cluster 1E 0657-56 (the Bullet Cluster), including the effects of elastic dark matter scattering. In a similar manner to the stripping of gas by ram pressure, dark matter…
Machine learning (ML) techniques, in particular supervised regression algorithms, are a promising new way to use multiple observables to predict a cluster's mass or other key features. To investigate this approach we use the \textsc{MACSIS}…
Astrophysical observations spanning dwarf galaxies to galaxy clusters indicate that dark matter (DM) halos are less dense in their central regions compared to expectations from collisionless DM N-body simulations. Using detailed fits to DM…
Gravitational lensing by galaxy clusters has emerged as a powerful tool to probe the standard Cold Dark Matter (CDM) paradigm of structure formation in the Universe. Despite the remarkable explanatory power of CDM on large scales, tensions…
High-velocity collisions between gas-rich ultra-diffuse galaxies present a promising formation channel for dark-matter-deficient galaxies (DMDGs). Using hydrodynamical simulations, we show that the progenitors' baryonic binding energy,…
Self-interacting dark matter is known as one of the most appropriate candidates for dark matter. Due to its excellent success in removing many astrophysical problems, particularly in small scale structure, studying this model has taken on…
The Dark Matter present in the Large-Scale Structure of the Universe is invisible, but its presence can be inferred through the small gravitational lensing effect it has on the images of far away galaxies. By measuring this lensing effect…
If dark matter has a large self-interaction scattering cross section, then interactions among dark-matter particles will drive galaxy and cluster halos to become spherical in their centers. Work in the past has used this effect to rule out…
A galaxy cluster as the most massive gravitationally-bound object in the Universe, is dominated by Dark Matter, which unfortunately can only be investigated through its interaction with the luminous baryons with some simplified assumptions…
Massive neutrinos, due to their free streaming, produce a suppression in the matter power spectrum at intermediate and small scales which could be probed by galaxy clustering and/or weak lensing observables. This effect happens at scales…
We perform a general computational analysis of possible post-collision mass distributions in high-speed galaxy cluster collisions in the presence of weakly self-interacting dark matter. Using this analysis, we show that weakly…
We review theories of dark matter (DM) beyond the collisionless paradigm, known as self-interacting dark matter (SIDM), and their observable implications for astrophysical structure in the Universe. Self-interactions are motivated, in part,…
We develop a statistical method to measure the interaction cross-section of Dark Matter, exploiting the continuous minor merger events in which small substructures fall into galaxy clusters. We find that by taking the ratio of the distances…
Machine learning has the potential to improve the reconstruction of the dark matter profile of galaxies with respect to traditional methods, like rotation curves. We demonstrate on the simulation suite Illustris-TNG that a steerable…