RESEARCH 002
Research Archive
Active research combining scientific machine learning with solar observations from the Aditya-L1 mission.
FEATURED RESEARCH
STATUS: ACTIVE
Physics-Informed Neural Network for Explainable Solar Flare Nowcasting and Forecasting Using SoLEXS and HEL1OS Data from Aditya-L1
METHOD
- Physics-Informed Neural Networks
- Time-Series Forecasting
- Explainable AI
- Uncertainty Quantification
PIPELINE
Data flow
- 01ADITYA-L1
- 02SoLEXS + HEL1OS
- 03Data Processing
- 04Feature Engineering
- 05Physics-Informed AI
- 06Explainable AI
- 07Forecast + Uncertainty
- 08Solar Flare Risk Assessment
INSTRUMENT 01
SoLEXS
Solar Low Energy X-ray Spectrometer
Measures the soft X-ray spectrum of the Sun, tracking how coronal plasma heats and cools across a flare.
INSTRUMENT 02
HEL1OS
High Energy L1 Orbiting X-ray Spectrometer
Observes higher-energy, hard X-ray emission produced during the impulsive phase of a flare.
RATIONALE
Why soft and hard X-rays are read together
Soft X-rays describe the thermal response of the solar atmosphere: how much plasma has been heated, and how that heat decays. On their own they mostly tell you what has already happened.
Hard X-rays trace accelerated, non-thermal electrons and typically peak earlier. Combining both bands gives an earlier and physically richer signal for nowcasting, and lets a physics-informed model reason about energy release rather than fitting a single light curve.