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Climate change is one of the defining challenges of the 21st century, and many in the robotics community are looking for ways to contribute. This paper presents a roadmap for climate-relevant robotics research, identifying high-impact…
The study of photoionised gas in planetary nebulae (PNe) has played a major role achieving, over the years, a better understanding of a number of physical processes pertinent to a broader range of fields than just PNe studies, ranging from…
In this paper a spatially resolved, fully self-consistent SSC model is presented. The observable spectral energy distribution (SED) evolves entirely from a low energetic delta distribution of injected electrons by means of the implemented…
The increasing frequency of extreme weather events due to global climate change urges accurate weather prediction. Recently, great advances have been made by the \textbf{end-to-end methods}, thanks to deep learning techniques, but they face…
We present a new 1-D multi-physics simulation code with use cases intended for, but not limited to, hydrodynamic escapeproblems of planetary atmospheres and planetary accretion models. Our formulation treats an arbitrary number of species…
Climate and weather prediction traditionally relies on complex numerical simulations of atmospheric physics. Deep learning approaches, such as transformers, have recently challenged the simulation paradigm with complex network forecasts.…
The Surface Enhancement of the IceTop air-shower array will include the addition of radio antennas and scintillator panels, co-located with the existing ice-Cherenkov tanks and covering an area of about 1 km$^2$. Together, these will…
Electron self-injection and acceleration until dephasing in the blowout regime is studied for a set of initial conditions typical of recent experiments with 100 terawatt-class lasers. Two different approaches to computationally efficient,…
Successful engineering requires environmentally adapted procedural and architectural approaches. While dealing with complicated issues has become an engineering standard mastering uncertainties in complex environment is still a major issue.…
SWELTO -- Space WEather Laboratory in Turin Observatory is a conceptual framework where new ideas for the analysis of space-based and ground-based data are developed and tested. The input data are (but not limited to) remote sensing…
Interstellar medium widely exists in the universe at multi-scales. In this study, we introduce the {\it Multi-scale Decomposition Reconstruction} method, an equation-based model designed to derive width maps of interstellar medium…
Field emission coupled with molecular dynamics simulation (FEcMD) software package is a computational tool for studying the electron emission characteristics and the atomic structure evolution of micro- and nano-protrusions made of pure…
We present a model for the interaction between dust and radiation fields in the radiation hydrodynamic code AREPO-RT, which solves the moment-based radiative transfer equations on an unstructured moving mesh. Dust is directly treated using…
Context. Relativistic jets in active galactic nuclei are known for their exceptional energy output, and imaging the synthetic synchrotron emission of numerical jet simulations is essential for a comparison with observed jet polarization…
We present a computational tool, TweedleDEE, for empirically modeling diffuse gamma-ray background emission in a 1 degree region of the sky, using publicly available gamma-ray data off-axis from the region of interest. This background model…
Particle dynamics in Earth's outer radiation belt can be modelled using a diffusion framework, where large-scale electron movements are captured by a diffusion equation across a single adiabatic invariant, $L^{*}$ $``(L)"$. While ensemble…
The growing ambition for space exploration demands robust autonomous systems that can operate in unstructured environments under extreme extraterrestrial conditions. The adoption of robot learning in this domain is severely hindered by the…
In this paper, we propose a novel deep architecture tailored for 3D point cloud applications, named as SPE-Net. The embedded ``Selective Position Encoding (SPE)'' procedure relies on an attention mechanism that can effectively attend to the…
Scientists generate petabytes of data daily to help uncover environmental trends or behaviors that are hard to predict. For example, understanding climate simulations based on the long-term average of temperature, precipitation, and other…
We develop multiple Deep Learning (DL) models that advance the state-of-the-art predictions of the global auroral particle precipitation. We use observations from low Earth orbiting spacecraft of the electron energy flux to develop a model…