Related papers: Deep Learning the Morphology of Dark Matter Substr…
Could Machine Learning (ML) make fundamental discoveries and tackle unsolved problems in Cosmology? Detailed observations of the present contents of the universe are consistent with the Cosmological Constant Lambda and Cold Dark Matter…
The inner region of a subhalo's density distribution is particularly sensitive to dark matter microphysics, with alternative dark matter models leading to both cored and steeply-rising inner density profiles. This work investigates how the…
A key prediction of the standard cosmological model -- which relies on the assumption that dark matter is cold, i.e. non-relativistic at the epoch of structure formation -- is the existence of a large number of dark matter substructures on…
Despite their increasing popularity and success in a variety of supervised learning problems, deep neural networks are extremely hard to interpret and debug: Given and already trained Deep Neural Net, and a set of test inputs, how can we…
The capabilities of image probe experiments are rapidly expanding, providing new information about quantum materials on unprecedented length and time scales. Many such materials feature inhomogeneous electronic properties with intricate…
Weak gravitational lensing surveys measure the distortion of the image of distant sources due to the deflections of light rays by the fluctuations of the gravitational potential along the line of sight. Since they probe the non-linear…
Stringent observational constraints on the sub-galactic matter power spectrum would allow one to distinguish between the concordance $\Lambda$CDM and the various alternative dark-matter models that predict significantly different properties…
Joint analyses of small-scale cosmological structure probes are relatively unexplored and promise to advance measurements of microphysical dark matter properties using heterogeneous data. Here, we present a multidimensional analysis of dark…
For nearly 40 years, dark matter has been widely assumed to be cold and collisionless. Cold dark matter models make fundamental predictions for the behavior of dark matter on small (<10 kpc) scales. These predictions include cuspy density…
Models in which the dark matter is very weakly coupled to the observable sector may explain the observed dark matter density, either as a "superWIMP" or as "asymmetric dark matter." Both types of models predict displaced vertices at…
Gravitational lensing has become one of the most interesting tools to study the mass distribution in the Universe. Since gravitational light deflection is independent of the nature and state of the matter, it is ideally suited to…
Gravitational lensing has emerged as a powerful probe of the matter distribution on subgalactic scales, which itself may contain important clues about the fundamental origins and properties of dark matter. Broadly speaking, two different…
Indirect detection of particle dark matter relies upon pair annihilation of Weakly Interaction Massive Particles (WIMPs), which is complementary to the well known techniques of direct detection (WIMP-nucleus scattering) and collider…
The nature of the dark matter remains a mystery. The possibility of an unstable dark matter particle decaying to invisible daughter particles has been explored many times in the past few decades. Meanwhile, weak gravitational lensing shear…
It is widely recognized that cold dark matter models predict abundant dark matter substructure in halos of all sizes. Galaxy-galaxy lensing provides a unique opportunity to directly measure the presence and the mass of such substructures in…
Strong lensing is a powerful tool to address three major astrophysical issues: understanding the spatial distribution of mass at kpc and sub-kpc scale, where baryons and dark matter interact to shape galaxies as we see them; determining the…
Just like light, gravitational waves (GWs) are deflected and magnified by gravitational fields as they propagate through the Universe. However, their low frequency, phase coherence and feeble coupling to matter allow for distinct lensing…
Resonant transmission of light is a surface-wave assisted phenomenon that enables funneling light through subwavelength apertures milled in otherwise opaque metallic screens. In this work, we introduce a deep learning approach to…
Intrinsic image decomposition is the process of separating the reflectance and shading layers of an image, which is a challenging and underdetermined problem. In this paper, we propose to systematically address this problem using a deep…
These lectures are intended to provide a brief pedagogical review of dark matter for the newcomer to the subject. We begin with a discussion of the astrophysical evidence for dark matter. The standard weakly-interacting massive particle…