相关论文: A deep-learning algorithm to disentangle self-inte…
Dwarf galaxies are small, dark matter-dominated galaxies, some of which are embedded within the Milky Way. Their lack of baryonic matter (e.g., stars and gas) makes them perfect test beds for probing the properties of dark matter --…
Galaxy clusters, the most massive, dark-matter-dominated, and most recently assembled structures in the Universe, are key tools for probing cosmology. However, uncertainties in scaling relations that connect cluster mass to observables like…
We constrain the physical nature of dark matter using the newly identified massive merging galaxy cluster MACSJ0025.4-1222. As was previously shown by the example of the Bullet Cluster (1E0657-56), such systems are ideal laboratories for…
In our current best cosmological model, the vast majority of matter in the Universe is dark, consisting of yet undetected, non-baryonic particles that do not interact electro-magnetically. So far, the only significant evidence for dark…
A simple way to accommodate dark matter is to postulate the existence of a hidden sector. That is, a set of new particles and forces interacting with the known particles predominantly via gravity. In general this leads to a large set of…
The prospects of indirect detection of dark matter at the galactic center depend sensitively on the mass profile within the inner parsec. We calculate the distribution of dark matter on sub-parsec scales by integrating the time-dependent…
The subtle and unique imprint of dark matter substructure on extended arcs in strong lensing systems contains a wealth of information about the properties and distribution of dark matter on small scales and, consequently, about the…
Self-interacting dark matter resolves the issue of cuspy profiles that appear in non-interacting cold dark matter simluations; it may additionally resolve the so-called "too big to fail" problem in structure formation. Asymmetric dark…
We compile a sample of 38 galaxy clusters which have both X-ray and strong lensing observations, and study for each cluster the projected offset between the dominant component of baryonic matter center (measured by X-rays) and the…
Modern Cosmology offers us a great understanding of the universe with striking precision, made possible by the modern technologies of the newest generations of telescopes. The standard cosmological model, however, is not absent of…
We train deep learning models on thousands of galaxy catalogues from the state-of-the-art hydrodynamic simulations of the CAMELS project to perform regression and inference. We employ Graph Neural Networks (GNNs), architectures designed to…
Galaxy clusters are a promising probe of late-time structure growth, but constraints on cosmology from cluster abundances are currently limited by systematics in their inferred masses. One unmitigated systematic effect in weak-lensing mass…
We demonstrate a machine learning approach designed to extract hidden chemistry/physics to facilitate new materials discovery. In particular, we propose a novel method for learning latent knowledge from material structure data in which…
We use semi-analytic models of galaxy formation combined with high resolution N-body simulations to make predictions for galaxy-dark matter correlations and apply them to galaxy-galaxy lensing. We analyze cross-correlation spectra between…
TThe fundamental properties of the postulated dark matter (DM) affect the internal structure of gravitationally-bound structures. In the cold dark matter paradigm, DM particles interact only via gravity. Their distribution is well…
We have performed a series of N-body experiments on Connection Machine-5 in order to simulate the formation of galaxy clusters gravitationally dominated by a massive dark background. In accordance with previous authors we find an extremely…
A new method for measuring gravitational lensing with high redshift type Ia supernovae is investigated. The method utilizes correlations between foreground galaxies and supernova brightnesses to substantially reduce possible systematic…
We investigate the impact of AGN feedback on the gravitational lensing properties of a sample of galaxy clusters with masses in the range 10^14 - 10^15 Msol, using state-of-the-art simulations. Adopting a ray-tracing algorithm, we compute…
Image denoising based on deep learning has witnessed significant advancements in recent years. However, existing deep learning methods lack quantitative control of the deviation or error on denoised images. The neural networks Self2Self is…
Recent observations in galaxies and clusters indicate dark matter density profiles exhibit core-like structures which contradict to the numerical simulation results of collisionless cold dark matter. The idea of self-interacting cold dark…