Related papers: Differentiating Warm Dark Matter Models through 21…
Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, leads to a negative creation pressure, which can be used to explain the accelerated expansion of the Universe. Recently, it has been shown that the dynamics of…
We investigate nonlinear structure formation in the fuzzy dark matter (FDM) model in comparison to cold dark matter (CDM) models from a weak lensing perspective using perturbative methods. We use Eulerian perturbation theory (PT) up to…
We use high resolution Hydro$+$N-Body cosmological simulations to compare the assembly and evolution of a small field dwarf (stellar mass ~ 10$^{6-7}$ M$\odot$, total mass 10$^{10}$ M$\odot$ in $\Lambda$ dominated CDM and 2keV WDM…
The growing demand for the internet of things (IoT) makes it necessary to implement computer vision tasks such as object recognition in low-power devices. Convolutional neural networks (CNNs) are a potential approach for object recognition…
We show that Milky Way white dwarfs are excellent targets for dark matter (DM) detection. Using Fermi and H.E.S.S. Galactic center gamma-ray data, we investigate sensitivity to DM annihilating within white dwarfs into long-lived or boosted…
We study the impact of a warm dark matter (WDM) cosmology on dwarf galaxy formation through a suite of cosmological hydrodynamical zoom-in simulations of $M_{\rm halo} \approx10^{10}\,M_{\odot}$ dark matter halos as part of the Feedback in…
The nature of dark matter remains a central question in cosmology, with fuzzy dark matter (FDM) models offering a compelling alternative to the cold dark matter (CDM) paradigm. We explore FDM scenarios by performing 21-cm simulations across…
One alternative to the cold dark matter (CDM) paradigm is the scalar field dark matter (SFDM) model, which assumes dark matter is a spin-0 ultra-light scalar field (SF) with a typical mass $m\sim10^{-22}\mathrm{eV}/c^2$ and positive…
We present the full evolution of the velocity of a massive particle, along with the equation of state we can compute the energy density and pressure evolution for the background evolution. It is also natural to compute the perturbation…
The model reduction problem that eases the computation costs and latency of complex deep learning architectures has received an increasing number of investigations owing to its importance in model deployment. One promising method is…
We explore fundamental properties of the distribution of low mass dark matter halos within the cosmic web using warm dark matter (WDM) and cold dark matter (CDM) cosmological simulations. Using self abundance-matched mock galaxy catalogs,…
In this work, we investigate the value of employing deep learning for the task of wireless signal modulation recognition. Recently in [1], a framework has been introduced by generating a dataset using GNU radio that mimics the imperfections…
Convolutional neural networks (CNNs) have shown great effectiveness in medical image segmentation. However, they may be limited in modeling large inter-subject variations in organ shapes and sizes and exploiting global long-range contextual…
If a subdominant component of dark matter (DM) interacts via long-range dark force carriers it may cool and collapse to form complex structures within the Milky Way galaxy, such as a rotating dark disk. This scenario was proposed recently…
It has been shown that a self-gravitating system of massive keV fermions in thermodynamic equilibrium correctly describes the dark matter (DM) distribution in galactic halos and predicts a denser quantum core towards the center of the…
We propose a new mechanism by which dark matter (DM) can affect the early universe. The hot interior of a macroscopic DM, or macro, can behave as a heat reservoir so that energetic photons are emitted from its surface. This results in…
We aim to develop a state-of-the-art tool to infer detailed star formation histories (SFHs) and age-metallicity relations from realistic observational data, while mitigating classical degeneracies and substantially reducing computational…
Fuzzy dark matter (FDM) is a well motivated candidate for dark matter (DM) as its tiny mass and large de-Broglie wavelength suppress small-scale matter fluctuations, thereby solving some of the small-scale discrepancies in $\Lambda$CDM.…
Beyond reionization epoch cosmic hydrogen is neutral and can be directly observed through its 21 cm line signal. If dark matter (DM) decays or annihilates the corresponding energy input affects the hydrogen kinetic temperature and ionized…
Convolutional neural networks (CNNs) are widely used for image recognition and text analysis, and have been suggested for application on one-dimensional data as a way to reduce the need for pre-processing steps. Pre-processing is an…