Related papers: A Foundation Model for the Solar Dynamics Observat…
Earth observation (EO) foundation models have emerged as an effective approach to derive latent representations of the Earth system from various remote sensing sensors. These models produce embeddings that can be used as analysis-ready…
Accurate, reliable solar flare prediction is crucial for mitigating potential disruptions to critical infrastructure, while predicting solar flares remains a significant challenge. Existing methods based on heuristic physical features often…
Smart-home sensor data holds significant potential for several applications, including healthcare monitoring and assistive technologies. Existing approaches, however, face critical limitations. Supervised models require impractical amounts…
In our previous articles (Chertok et al.: 2013, Solar Phys. 282, 175, and 2015, Solar Phys. 290, 627), we presented a preliminary tool for the early diagnostics of the geoeffectiveness of solar eruptions based on the estimate of the total…
Organic Solar Cells are a promising technology for solving the clean energy crisis in the world. However, generating candidate chemical compounds for solar cells is a time-consuming process requiring thousands of hours of laboratory…
The success of large foundation models is catalyzing a new paradigm for AI-native 6G network design: wireless foundation models for physical layer design. However, existing models often operate on channel state information (CSI) in the…
Knowledge of the global magnetic field distribution and its evolution on the Sun's surface is crucial for modeling the coronal magnetic field, understanding solar wind dynamics, computing the heliospheric open flux distribution and…
We have developed a variational data assimilation technique for the Sun using a toy {\alpha}{\Omega} dynamo model. The purpose of this work is to apply modern data assimilation techniques to solar data using a physically based model. This…
The scientific potential of a wide field-of-view, and very-high duty cycle, ground-based gamma-ray detector has been demonstrated by the current generation of instruments, such as HAWC and ARGO, and will be further extended in the Northern…
Since May 1, 2010, we have been able to study (almost) continuously the vector magnetic field in the Sun, thanks to two space-based observatories: the Solar Dynamics Observatory (SDO) and Hinode. Both are equipped with instruments able to…
The rapid advancement of autonomous systems, including self-driving vehicles and drones, has intensified the need to forge true Spatial Intelligence from multi-modal onboard sensor data. While foundation models excel in single-modal…
Advances in hydrodynamical simulations have provided new insights into the effects of convection on the frequencies of solar oscillations. As more accurate observations become available, this may lead to an improved understanding of the…
Foundation models (FMs) are changing the way medical images are analyzed by learning from large collections of unlabeled data. Instead of relying on manually annotated examples, FMs are pre-trained to learn general-purpose visual features…
Solar activity, ranging from the background solar wind to energetic coronal mass ejections (CMEs), is the main driver of the conditions in the interplanetary space and in the terrestrial space environment, known as space weather. A better…
Foundation models (FMs) have emerged as a powerful paradigm, enabling a diverse range of data analytics and knowledge discovery tasks across scientific fields. Inspired by the success of FMs, particularly large language models, researchers…
In this work, we present SoFT: Solar Feature Tracking, a novel feature-tracking tool developed in Python and designed to detect, identify, and track magnetic elements in the solar atmosphere. It relies on a watershed segmentation algorithm…
The great success of Helioseismology resides in the remarkable progress achieved in the understanding of the structure and dynamics of the solar interior. This success mainly relies on the ability to conceive, implement, and operate…
The input of the Solar wind models plays a significant role in accurate solar wind predictions at 1 AU. This work introduces a synthetic magnetogram produced from a dynamo model as an input for Magnetohydrodynamics (MHD) simulations. We…
Basis function learning is the stepping stone towards effective three-dimensional (3D) sound speed field (SSF) inversion for various acoustic signal processing tasks, including ocean acoustic tomography, underwater target…
We briefly discuss some implications of the first solar \nu results from the Sudbury Neutrino Observatory (SNO) experiment in the charged-current channel. We first show that the present SNO response function is very similar to the…