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We study the dust evolution in galaxies by implementing a detailed dust prescription in the SAGE semi-analytical model for galaxy formation. The new model, called Dusty SAGE, follows the condensation of dust in the ejecta of type II…
We present a novel derivation of scalar cosmological perturbations in the scalar-tensor extension of non-metricity gravity, where the non-metricity scalar $Q$ is non-minimally coupled to a dynamical scalar field. While previous…
In this paper we provide a new analysis of the SEM algorithm. Unlike previous work, we focus on the analysis of a single run of the algorithm. First, we discuss the algorithm for general mixture distributions. Second, we consider Gaussian…
Computation of gas dispersal in urban places or hilly grounds requires a large amount of computer time when addressed with conventional multidimensional models. Those are usually based on two-phase flow or Navier-Stokes equations. Different…
Galaxy populations at different cosmic epochs are often linked together by comoving cumulative number density in observational studies. Many theoretical works, however, have shown that the number densities of tracked galaxy populations…
In order to quantify the error budget in the measured probability distribution functions of cell densities, the two-point statistics of cosmic densities in concentric spheres is investigated. Bias functions are introduced as the ratio of…
In this work we investigate the evolution of matter density perturbations for two different quintessence models. One of them is based on the Einstein theory of gravity, while the other is based on the Brans-Dicke scalar tensor theory. We…
The cosmological dynamics of gravitational clustering satisfies an approximate invariance with respect to the cosmological parameters that is often used to simplify analytical computations. We describe how this approximate symmetry gives…
Recent studies have found a dramatic difference between the observed number density evolution of low mass galaxies and that predicted by semi-analytic models. While models accurately reproduce the z=0 number density, they require that the…
Learning models of complex spatial density functions, representing the steady-state density of mobile nodes moving on a two-dimensional terrain, can assist in network design and optimization problems, e.g., by accelerating the computation…
Computing analytically the $n$-point density correlations in systems of interacting particles is a long-standing problem of statistical physics, with a broad range of applications, from the interpretation of scattering experiments in simple…
We generalize the well-known mixtures of Gaussians approach to density estimation and the accompanying Expectation--Maximization technique for finding the maximum likelihood parameters of the mixture to the case where each data point…
Gaussian mixtures are a powerful and widely used tool to model non-Gaussian estimation problems. They are able to describe measurement errors that follow arbitrary distributions and can represent ambiguity in assignment tasks like point set…
Recent technological advances have led to a flood of new data on cosmology rich in information about the formation and evolution of the universe, e.g., the data collected in Sloan Digital Sky Survey (SDSS) for more than 200 million objects.…
Generalized feed-forward Gaussian models have achieved significant progress in sparse-view 3D reconstruction by leveraging prior knowledge from large multi-view datasets. However, these models often struggle to represent high-frequency…
We give an improved formalism for calculating the evolution of density fluctuations and temperature perturbations in flat universes. Our equations are general enough to treat the perturbations in collisionless relics like massive neutrinos.…
The sub-Gaussian stable distribution is a heavy-tailed elliptically contoured law which has interesting applications in signal processing and financial mathematics. This work addresses the problem of feasible estimation of distributions. We…
Dust is a crucial component of the interstellar medium of galaxies. The presence of dust strongly affects the light produced by stars within a galaxy. As these photons are our main information vector to explore the stellar mass assembly and…
We apply the postquasistatic approximation, an iterative method for the evolution of self-gravitating spheres of matter, to study the evolution of dissipative and electrically charged distributions in General Relativity. We evolve…
Understanding the evolution of dust and molecular hydrogen (H$_2$) is a critical aspect of galaxy evolution, as they affect star formation and the spectral energy distribution of galaxies. We use the $N$-body/smoothed-particle-hydrodynamics…