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High-dimensional multivariate time series are challenging due to the dependent and high-dimensional nature of the data, but in many applications there is additional structure that can be exploited to reduce computing time along with…
We analyze time series data of the fluctuations of slow solar wind velocity using rank order statistics. We selected a total of 18 datasets measured by the Helios spacecraft at a distance of 0.32 AU from the sun in the inner heliosphere.…
This paper presents a methodology for building daily profiles of wind generation and load for different seasons to assess their impacts on voltage violations. The measurement-based wind models showed very high accuracy when validated…
Structured variational inference constitutes a core methodology in modern statistical applications. Unlike mean-field variational inference, the approximate posterior is assumed to have interdependent structure. We consider the natural…
Using Bayesian analyses we study the solar electron density with the NANOGrav 11-year pulsar timing array (PTA) dataset. Our model of the solar wind is incorporated into a global fit starting from pulse times-of-arrival. We introduce new…
The paper presents a Gaussian/kernel process regression method for real-time state estimation and forecasting of phase angle and angular speed in systems with a high penetration of solar generation units, operating under a sparse…
The structure of the turbulence-driven power fluctuations in a wind farm is fundamentally described from basic concepts. A derived tuning-free model, supported with experiments, reveals the underlying spectral content of the power…
Characterizing compressible fluctuations in the solar wind is essential for understanding their role in solar wind acceleration and heating, yet their origin and evolution across different turbulence regimes remain poorly understood. In…
Solar wind fluctuations, such as magnetic field or velocity, show power law power spectra suggestive both of an inertial range of intermittent turbulence (with $\sim -5/3$ exponent) and at lower frequencies, of fluctuations of coronal…
We analyze the combined effect of Poynting-Robertson and solar wind drag on space debris. We derive a model within Cartesian, Gaussian and Hamiltonian frameworks. We focus on the geosynchronous resonance, although the results can be easily…
A novel method for real-time solar generation forecast using weather data, while exploiting both spatial and temporal structural dependencies is proposed. The network observed over time is projected to a lower-dimensional representation…
We reconcile the two worlds of dense and sparse modeling by exploiting the positive aspects of both. We employ a factor model and assume {the dynamic of the factors is non-pervasive while} the idiosyncratic term follows a sparse vector…
Much of our knowledge of quantum systems is encapsulated in the expectation value of Hermitian operators, experimentally obtained by averaging projective measurements. However, dynamical properties are often described by products of…
The power spectrum of the evolving solar wind shows evidence of a spectral break between an inertial range of turbulent fluctuations at higher frequencies and a "$1/f$" like region at lower frequencies. In the ecliptic plane at $\sim 1$ AU,…
One of the main discoveries from the first two orbits of Parker Solar Probe (PSP) was the presence of magnetic switchbacks, whose deflections dominated the magnetic field measurements. Determining their shape and size could provide evidence…
The journey of the Sun through space carries the solar system through a dynamic interstellar environment that is presently characterized by Mach 1 motion between the heliosphere and the surrounding interstellar medium (ISM). The interaction…
Wind turbines often work under complex conditions which result in performance degradation. Accurate performance degradation monitoring is essential to ensure the reliable operation of wind turbines and reduce the maintenance costs. Wind…
In this letter we propose a practical methodology to interpret future Parker Solar Probe (PSP) turbulent time signals even when Taylor's hypothesis is not valid. By extending Kraichnan's sweeping model used in hydrodynamics we derive the…
Geostationary satellites collect high-resolution weather data comprising a series of images which can be used to estimate wind speed and direction at different altitudes. The Derived Motion Winds (DMW) Algorithm is commonly used to process…
We develop a generative neural network for the generation of sparse data in particle physics using a permutation-invariant and physics-informed loss function. The input dataset used in this study consists of the particle constituents of…