相关论文: 3D-Spatiotemporal Forecasting the Expansion of Sup…

Simulating reactive dissolution of solid minerals in porous media has many subsurface applications, including carbon capture and storage (CCS), geothermal systems and oil & gas recovery. As traditional direct numerical simulators are…

We use spherically symmetric hydrodynamic simulations to study the dynamical evolution and internal structure of superbubbles (SBs) driven by clustered supernovae (SNe), focusing on the effects of thermal conduction and cooling in the…

Supernova remnants (SNRs) play a central role in shaping the interstellar medium. Core-Collapse Supernova (CCSN) progenitors are massive stars, which produce a dense circumstellar medium (CSM) through intense mass loss in post-main sequence…

We discuss an implementation of a deep learning framework to gain insight into dark matter (DM) structure formation. We investigate the contribution of velocity and density field information to the construction of the halo mass function…

Accurate modeling of supernova (SN) feedback in galaxy formation simulations is complicated by energy conservation violations arising from the vector nature of momentum injection. We present a mechanical feedback scheme addressing two key…

Supernova explosions and their remnants (SNRs) drive important feedback mechanisms that impact considerably the galaxies that host them. Then, the knowledge of the SNRs evolution is of paramount importance in the understanding of the…

Some interacting supernovae (SNe) of type IIn show a sizeable continuum polarisation suggestive of a large scale asymmetry in the circumstellar medium (CSM) and/or the SN ejecta. Here, we extend the recent work of Dessart et al. on…

Non-spherical structure in massive stars at the point of iron core collapse can have a qualitative impact on the properties of the ensuing core-collapse supernova explosions and the multi-messenger signals they produce. Strong perturbations…

The core-collapse supernova (CCSN) mechanism is fundamentally three-dimensional with instabilities, convection, and turbulence playing crucial roles in aiding neutrino-driven explosions. Simulations of CCNSe including accurate treatments of…

We present a seven-minute long $4\pi$-3D simulation of a shell merger event in a non-rotating $18.88\, M_\odot$ supernova progenitor before the onset of gravitational collapse. The key motivation is to capture the large-scale mixing and…

We present a Supernova (SN) feedback model that succeeds at describing the chemical and energetic effects of SN explosions in galaxy formation simulations. This new SN model has been coupled to GADGET-2 and works within a new multiphase…

The overwhelming evidence that the core collapse supernova mechanism is inherently multidimensional, the complexity of the physical processes involved, and the increasing evidence from simulations that the explosion is marginal presents…

We extend a machine learning (ML) framework presented previously to model galaxy formation and evolution in a hierarchical universe using N-body + hydrodynamical simulations. In this work, we show that ML is a promising technique to study…

Predicting the spatio-temporal progression of brain tumors is essential for guiding clinical decisions in neuro-oncology. We propose a hybrid mechanistic learning framework that combines a mathematical tumor growth model with a guided…

Stellar collisions in dense galactic nuclei might play an important role in fueling supermassive black holes (SMBHs) and shaping their environments. The gas released during these collisions can contribute to SMBH accretion, influencing…

Neutrino-driven convection plays a crucial role in the development of core-collapse supernova (CCSN) explosions. However, the complex mechanism that triggers the shock revival and the subsequent explosion has remained inscrutable for many…

With the advent of modern neutrino and gravitational wave detectors, the promise of multi-messenger detections of the next galactic core-collapse supernova has become very real. Such detections will give insight into the core-collapse…

We present a new exploratory framework to model galaxy formation and evolution in a hierarchical universe by using machine learning (ML). Our motivations are two-fold: (1) presenting a new, promising technique to study galaxy formation, and…

We perform smoothed-particle hydrodynamical simulations of the explosion of a helium star in a close binary system, and study the effects of the explosion on the companion star as well as the effect of the presence of the companion on the…

Supernovae (SN), the most energetic stellar feedback mechanism, are crucial for regulating the interstellar medium (ISM) and launching galactic winds. We explore how supernova remnants (SNRs) create a multiphase medium by performing 3D…