Related papers: GEAR-RT: Towards Exa-Scale Moment Based Radiative …
Achieving efficient and accurate simulation of the radiative transfer has long been a research challenge. Here we introduce the general synthetic iterative scheme as an easy-to-implement approach to address this issue. First, a macroscopic…
The highly convergent iterative methods developed by Trujillo Bueno and Fabiani Bendicho (1995) for radiative transfer (RT) applications are generalized to spherical symmetry with velocity fields. These RT methods are based on Jacobi,…
The Generalized Integral Representation Method (GIRM) for Space-Time-Separated Method (STSM) and Space-Time-Unified Method (STUM) are discussed. STSM and STUM give explicit and implicit time evolutions, respectively. The algorithm of STSM…
Before the recent success of deep learning methods for automated medical image analysis, practitioners used handcrafted radiomic features to quantitatively describe local patches of medical images. However, extracting discriminative…
We describe a new algorithm to solve the time dependent, frequency integrated radiation transport (RT) equation implicitly, which is coupled to an explicit solver for equations of magnetohydrodynamics (MHD) using {\sf Athena++}. The…
HII regions powered by ionizing radiation from massive stars drive the dynamical evolution of the interstellar medium. Fast radiative transfer methods for incorporating photoionization effects are thus essential in astrophysical…
Parametric radiative transfer equation (RTE) occurs in multi-query applications such as uncertainty quantification, inverse problems, and sensitivity analysis, which require solving RTE multiple times for a range of parameters.…
Large pre-trained models have demonstrated extensive applications across various fields. However, fine-tuning these models for specific downstream tasks demands significant computational resources and storage. One fine-tuning method,…
We present a new implementation of the SFUMATO code, called SFUMATO#, for solving self-gravitational radiation hydrodynamics problems using adaptive mesh refinement (AMR) with the CUDA/HIP programming frameworks. The code incorporates a…
Radiative transfer (RT) modelling is a necessary tool in the interpretation of observations of the thermal emission of interstellar dust. It is also often part of multi-physics modelling. In this context, the efficiency of radiative…
Remote physiological measurement (RPM) is an essential tool for healthcare monitoring as it enables the measurement of physiological signs, e.g., heart rate, in a remote setting via physical wearables. Recently, with facial videos, we have…
We develop a Ly-alpha radiative transfer (RT) Monte Carlo code for cosmological simulations.High resolution,along with appropriately treated cooling can result in simulated environments with very high optical depths.Thus,solving the…
Direct simulation of the von Neumann dynamics for a general (pure or mixed) quantum state can often be expensive. One prominent example is the real-time time-dependent density functional theory (rt-TDDFT), a widely used framework for the…
Sampling-based motion planning has emerged as a powerful approach for robotics, enabling exploration of complex, high-dimensional configuration spaces. When combined with Signal Temporal Logic (STL), a temporal logic widely used for…
We have developed a gravity solver based on combining the well developed Particle-Mesh (PM) method and TREE methods. It is designed for and has been implemented on parallel computer architectures. The new code can deal with tens of millions…
Fine-tuning speech representation models can enhance performance on specific tasks but often compromises their cross-task generalization ability. This degradation is often caused by excessive changes in the representations, making it…
The Geant4 toolkit is the standard for simulating the passage of particles through matter, but its conventional architecture often requires users to modify and recompile C++ code to alter fundamental simulation parameters such as geometry,…
We present a new Krylov subspace recycling method for solving a linear system of equations, or a sequence of slowly changing linear systems. Our approach is to reduce the computational overhead of recycling techniques while still benefiting…
In recent years, deep neural networks, including Convolutional Neural Networks, Transformers, and State Space Models, have achieved significant progress in Remote Sensing Image (RSI) Super-Resolution (SR). However, existing SR methods…
We discuss the architecture and design principles that underpin the latest version of SKIRT, a state-of-the-art open source code for simulating continuum radiation transfer in dusty astrophysical systems, such as spiral galaxies and…