Related papers: SEDONA-GesaRaT: an AI-Accelerated Radiative Transf…
We present two types of numerical prescriptions that accelerate the radiative transfer calculation around point sources within a three-dimensional Cartesian grid by using the oct-tree structure for the distribution of radiation sources. In…
Aims. We present MCFOST-art, a new non-local thermodynamic equilibrium radiative transfer solver for multilevel atomic systems. The code is embedded in the 3D radiative transfer code MCFOST and is compatible with most of the MCFOST modules.…
Dust is a major component of the interstellar medium. Through scattering, absorption and thermal re-emission, it can profoundly alter astrophysical observations. Models for dust composition and distribution are necessary to better…
Objective: Real-time adaptive proton range verification systems based on produced neutrons require accurate information on their non-isotropic momentum distributions within short times, for which Monte Carlo (MC) methods are too…
We present a novel methodology of augmenting the scattering data measured by small angle neutron scattering via an emerging deep convolutional neural network (CNN) that is widely used in artificial intelligence (AI). Data collection time is…
We present a radiative transfer code to model the nebular phase spectra of supernovae (SNe) in non-local thermodynamic equilibrium (NLTE). We apply it to a systematic study of Type Ia SNe using parameterized 1D models and show how nebular…
Transfer learning is a popular technique for improving the performance of neural networks. However, existing methods are limited to transferring parameters between networks with same architectures. We present a method for transferring…
Following up on earlier work on this topic (Reinecke et al. 1999, A&A 347, pp. 724 and 739), we present an improved set of numerical models for simulations of white dwarfs exploding as Type Ia supernovae (SNe Ia). Two-dimensional…
We simulate convection near the solar surface, where the continuum optical depth is of order unity. Hence, to determine the radiative heating and cooling in the energy conservation equation, we must solve the radiative transfer equation…
The next great leap toward improving treatment of cancer with radiation will require the combined use of online adaptive and magnetic resonance guided radiation therapy techniques with automatic X-ray beam orientation selection.…
A two-dimensional hydrodynamics code for Type Ia supernovae (SNIa) simulations is presented. The code includes a fifth-order shock-capturing scheme WENO, detailed nuclear reaction network, flame-capturing scheme and sub-grid turbulence. For…
A simple and self-consistent approach has been proposed for simulation of the proton-induced soft error rate based on the heavy ion induced single event upset cross-section data and vice versa. The approach relies on the GEANT4 assisted…
Context. Type Ia supernovae (SN Ia) have become an invaluable cosmological tool as their exceptional brightness makes them observable even at very large distances (up to redshifts around z~1). To investigate possible systematic differences…
We present a new relativistic radiative-transfer code for $\gamma$-rays of energy less than 5 MeV in supernova (SN) ejecta. This code computes the opacities, the prompt emissivity (i.e. decay), and the scattering emissivity, and solves for…
Auto-scheduling for tensor programs is a process where a search algorithm automatically explores candidate schedules (program transformations) for a given program on a target hardware platform to improve its performance. However this can be…
Deep neural networks achieve remarkable performance in many computer vision tasks. Most state-of-the-art (SOTA) semantic segmentation and object detection approaches reuse neural network architectures designed for image classification as…
The computational difficulty of six-dimensional neutrino radiation hydrodynamics has spawned a variety of approximations, provoking a long history of uncertainty in the core-collapse supernova explosion mechanism. Under the auspices of the…
We present new models for the forward and reverse shock thermal X-ray emission from core-collapse and Type Ia supernova remnants (SNRs) which include the efficient production of cosmic rays via non-linear diffusive shock acceleration (DSA).…
Deep neural networks achieve remarkable performance in many computer vision tasks. Most state-of-the-art (SOTA) semantic segmentation and object detection approaches reuse neural network architectures designed for image classification as…
Resonant lines are powerful probes of the interstellar and circumgalactic medium of galaxies. Their transfer in gas being a complex process, the interpretation of their observational signatures, either in absorption or in emission, is often…