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Models of core-collapse supernova explosions powered by the neutrino-driven mechanism have matured considerable in recent years. Explosions at the low-mass end of the progenitor spectrum can routinely be simulated in 1D, 2D, and 3D and…
Supernova (SN) explosions play an important role in the development of galactic structures. The energy and momentum imparted on the interstellar medium (ISM) in so-called "supernova feedback" drives turbulence, heats the gas, enriches it…
We explore the capability of deep learning to classify cosmic structures. In cosmological simulations, cosmic volumes are segmented into voids, sheets, filaments and knots, according to the distribution and kinematics of dark matter (DM),…
We perform two- (2D) and three-dimensional (3D) hydrodynamics simulations of convective oxygen shell-burning that takes place deep inside a massive progenitor star of a core-collapse supernova. Using one dimensional (1D) stellar evolution…
We present numerical simulations that include 1-D Eulerian multi-group radiation-hydrodynamics, 1-D non-LTE radiative transfer, and 2-D polarised radiative transfer for super-luminous interacting supernovae (SNe). Our reference model is a…
Early interaction of supernova blast waves with CSM has the potential to accelerate particles to PeV energies, although this has not yet been detected. Current models for this interaction assume the shock expands into a smooth stellar wind,…
Initially classified as a supernova (SN) type Ib, $\sim$ 100 days after the explosion SN\,2014C made a transition to a SN type II, presenting a gradual increase in the H${\alpha}$ emission. This has been interpreted as evidence of…
Electron microscopy, while reliable, is an expensive, slow, and inefficient technique for thorough size distribution characterization of both mono- and polydisperse colloidal nanoparticles. If rapid in-situ characterization of colloid…
Supernova (SN) blast waves inject energy and momentum into the interstellar medium (ISM), control its turbulent multiphase structure and the launching of galactic outflows. Accurate modelling of the blast wave evolution is therefore…
We carry out three-dimensional hydrodynamic simulations of the supernova remnants (SNRs) produced inside molecular clouds (MCs) near their surface using the HLL code (Harten et al. 1983). We explore the dynamical evolution and the X-ray…
The SILCC project (SImulating the Life-Cycle of molecular Clouds) aims at a more self-consistent understanding of the interstellar medium (ISM) on small scales and its link to galaxy evolution. We simulate the evolution of the multi-phase…
We developed a computer vision-based methodology to achieve precise 3D segmentation and tracking of superbubbles within magnetohydrodynamic simulations of the supernova-driven interstellar medium. Leveraging advanced 3D transformer models,…
We use cosmological simulations in order to study the effects of supernova (SN) feedback on the formation of a Milky Way-type galaxy of virial mass ~10^12 M_sun/h. We analyse a set of simulations run with the code described by Scannapieco…
It is often understood that supernova (SN) feedback in galaxies is responsible for regulating star formation and generating gaseous outflows. However, a detailed look at their effect on the local interstellar medium (ISM) on small mass…
The neutrino-heated "gain layer" immediately behind the stalled shock in a core-collapse supernova is unstable to high-Reynolds-number turbulent convection. We carry out and analyze a new set of 19 high-resolution three-dimensional (3D)…
Some supernova (SN) explosions show evidence for interaction with pre-existing non-spherically symmetric circumstellar medium (CSM) in their light curves, spectral line profiles, and polarization signatures. To better understand the…
We study the evolution of multiple supernova (SN) explosions inside a pre-exiting cavity blown by winds from massive progenitor stars. Hydrodynamic simulations in one-dimensional spherical geometry, including radiative cooling and thermal…
We describe a new method for adding a prescribed amount of kinetic energy to simulated gas modeled on a cartesian grid by directly altering grid cells' mass and velocity in a distributed fashion. The method is explored in the context of…
A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amidst a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results…
Fostered by the possibilities of multi-dimensional computational modeling, in particular the advent of three-dimensional (3D) simulations, our understanding of the neutrino-driven explosion mechanism of core-collapse supernovae (SNe) has…