Related papers: Martian Ionosphere Electron Density Prediction Usi…

Knowledge of Mars's ionosphere has been significantly advanced in recent years by observations from Mars Express (MEX) and lately MAVEN. A topic of particular interest are the interactions between the planet's ionospheric plasma and its…

We examine the history of the loss and replenishment of the Martian atmosphere using elemental and isotopic compositions of nitrogen and noble gases. The evolution of the atmosphere is calculated by taking into consideration various…

Calibrating for direction-dependent ionospheric distortions in visibility data is one of the main technical challenges that must be overcome to advance low-frequency radio astronomy. In this paper, we propose a novel probabilistic,…

A diagnosis of the Ar densities measured by the Neutral Gas and Ion Mass Spectrometer aboard the Mars Atmosphere and Volatile EvolutioN (MAVEN) and the temperatures derived from these densities shows that solar activity, solar insolation,…

In this Letter, we make use of sophisticated 3D numerical simulations to assess the extent of atmospheric ion and photochemical losses from Mars over time. We demonstrate that the atmospheric ion escape rates were significantly higher (by…

A fundamental limitation of traditional Neural Networks (NN) in predictive modelling is their inability to quantify uncertainty in their outputs. In critical applications like positioning systems, understanding the reliability of…

In contemporary magnetic confinement devices, the density distribution is sensed with interferometers and actuated with feedback controlled gas injection and open-loop pellet injection. This is at variance with the density control for ITER…

Mars Exospheric Neutral Composition Analyzer (MENCA) of Mars Orbiter Mission (MOM) measures the \emph{in-situ} neutral upper atmospheric constituents of Mars. Martian lower atmosphere predominated by the presence of $CO_2$ which…

We implement machine learning algorithms to nuclear data. These algorithms are purely data driven and generate models that are capable to capture intricate trends. Gradient boosted trees algorithm is employed to generate a trained model…

Our research objective is to characterize Mars' low-altitude (250 km) induced magnetic fields using data from NASA's MAVEN (Mars Atmosphere and Volatile EvolutioN) Mission. We aim to assess how the induced magnetic fields behave under…

We present an atmospheric model tailored for the interactive visualization of planetary surfaces. As the exploration of the solar system is progressing with increasingly accurate missions and instruments, the faithful visualization of…

Thermal (<1 eV) electron density measurements, derived from the Mars Atmosphere and Volatile Evolution's (MAVEN) Langmuir Probe and Waves (LPW) instrument, are analyzed to produce the first statistical study of the thermal electron…

Aims. We study the soft X-ray emission induced by charge exchange (CX) collisions between solar-wind, highly charged ions and neutral atoms of the Martian exosphere. Methods. A 3D multi species hybrid simulation model with improved spatial…

Merging satellite products and ground-based measurements is often required for obtaining precipitation datasets that simultaneously cover large regions with high density and are more accurate than pure satellite precipitation products.…

We propose a new method to estimate ion escape from unmagnetized planets that combines observations and models. Assuming that upstream solar wind conditions are known, a computer model of the interaction between the solar wind and the…

We present an automated approach for identifying magnetospheric regions using supervised machine learning techniques applied to Magnetospheric MultiScale mission data. Our method utilizes ion energy spectra, total magnetic field, total ion…

The troposphere is one of the atmospheric layers where most weather phenomena occur. Temperature variations in the troposphere, especially at 500 hPa, a typical level of the middle troposphere, are significant indicators of future weather…

Machine learning (ML) has often been applied to space weather (SW) problems in recent years. SW originates from solar perturbations and is comprised of the resulting complex variations they cause within the systems between the Sun and…

Space weather observations and modeling at Mars have begun but they must be significantly increased to support the future of Human Exploration on the Red Planet. A comprehensive space weather understanding of a planet without a global…

Atmospheric neutral density is a crucial component to accurately predict and track the motion of satellites. During periods of elevated solar and geomagnetic activity atmospheric neutral density becomes highly variable and dynamic. This…