Morphological evidence for nanoflares heating warm loops in the solar corona

Y Bi, JY Yang, Y Qin, ZP Qiang, JC Hong… - Astronomy & …, 2023 - aanda.org
Context. Nanoflares are impulsive energy releases that occur due to magnetic reconnection
in the braided coronal magnetic field, which is a potential mechanism for heating the corona …

Probabilistic Prediction of Dst Storms One‐Day‐Ahead Using Full‐Disk SoHO Images

A Hu, C Shneider, A Tiwari, E Camporeale - Space weather, 2022 - Wiley Online Library
We present a new model for the probability that the disturbance storm time (Dst) index
exceeds− 100 nT, with a lead time between 1 and 3 days. Dst provides essential information …

Attention-based generative neural image compression on solar dynamics observatory

A Zafari, A Khoshkhahtinat, PM Mehta… - 2022 21st IEEE …, 2022 - ieeexplore.ieee.org
NASA's Solar Dynamics Observatory (SDO) mission gathers 1.4 terabytes of data each day
from its geosynchronous orbit in space. SDO data includes images of the Sun captured at …

Deep solar ALMA neural network estimator for image refinement and estimates of small-scale dynamics

H Eklund - Astronomy & Astrophysics, 2023 - aanda.org
Context. The solar atmosphere is highly dynamic, and observing the small-scale features is
valuable for interpretations of the underlying physical processes. The contrasts and …

Instrument-To-Instrument translation: Instrumental advances drive restoration of solar observation series via deep learning

R Jarolim, AM Veronig, W Pötzi… - arXiv preprint arXiv …, 2024 - arxiv.org
The constant improvement of astronomical instrumentation provides the foundation for
scientific discoveries. In general, these improvements have only implications forward in time …

Multi-Spectral Entropy Constrained Neural Compression of Solar Imagery

A Zafari, A Khoshkhahtinat, PM Mehta… - 2023 International …, 2023 - ieeexplore.ieee.org
Missions studying the dynamic behaviour of the Sun are defined to capture multi-spectral
images of the sun and transmit them to the ground station in a daily basis. To make …

Impact and Challenges of Intelligent IoT in Meteorological Science

Y Chen, K Hayawi, J He, H Song… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The abundant data in meteorological science has facilitated applying big data techniques.
The data collection was achieved by researchers using different atmospheric sounding …

[PDF][PDF] Machine Learning in Space

AG Baydin - 2023 - space.ox.ac.uk
● About● Frontier Development Lab (NASA, ESA, Oxford)● Machine learning and
space● Case I: constellations and collision avoidance● Case II: thermospheric density …

Accelerating Open Science for AI in Heliophysics

D Garcia, PJ Wright, R Jarolim, MCM Cheung… - … on Trustworthy and … - openreview.net
Rarely are Artificial Intelligence (AI) projects packaged in a way where scientists and non-AI
specialists can easily pick up advanced Machine Learning (ML) workflows. Similarly, AI …

[图书][B] A Novel Machine Learning Methodology to Calibrate SDO/AIA and Unveil the Internal Magnetic Structure of ICMEs

LFG dos Santos - 2021 - search.proquest.com
Instruments onboard heliophysics space missions provide a pool of information about the
Sun's activity and the interplanetary medium via the measurement of the magnetic field …