IRIS BIG DATA


Automatic Analysis of Solar Eruptions
in Data from the NASA space telescope IRIS
using machine learning methods

ROLE OF THE INSTITUTE FOR DATA SCIENCE


> Computer science: software architecture, machine learning, algorithms

> Solar Physics: Physics on the sun, characteristics of the data collected by NASA’s IRIS instrument

Project lead at i4Ds: Martin Melchior, Säm Krucker

Partners: UniGE

Funding: National Research Programme NRP 75 „Big Data”
NRP75 project description

Start: 2017
Status: ongoing


Keywords: data science, big data, machine learning, space weather, heliophysics, IRIS

    

SUMMARY

Current telescopes deliver huge amounts of data which cannot be handled by traditional methods anymore. This project uses machine learning to detect and analyse solar flares in data from the NASA space telescope IRIS. The new methods are expected to significantly contribute to the understanding of the physics behind solar flares. They will also improve capabilities to predict them, a core element in space weather prediction.

Interface Region Imaging Spectrograph (IRIS) is a NASA Small Explorer Mission designed to observe the transition region between the solar chromosphere and corona. It records around 12 GB of image data every day, amounting to a current total of >35 TB of available data.

PEOPLE @I4DS WHO WORK ON IRIS BIG DATA

Dr. Cédric Huwyler

Data Scientist, Astrophysicist

Brandon Panos

Doctoral Student

Dr. Lucia Kleint

Astrophysicist

Prof. Dr. Säm Krucker

Astrophysicist

more information

Prof. Dr. Martin Melchior

Physicist, Deputy Head I4DS

more information

OPEN RESOURCES AND RESULTS

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

 
 

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

Presentation Dublin 2018

VISUALS AND AUDIO

IRIS is a NASA solar mission launched in 2013. It produces about 12 GB of data every day. Scientists use them to determine the thermodynamical properties on the Sun.

IRIS records the Sun in unprecedented details, both in the form of images and as spectra. The IRIS Big Data project aims at better understanding the physics behind solar flares and at developing an algorithm that automatically detects solar flares among the huge amount of data.

As a first step, an algorithm for classifying UV-spectra on the solar surface was developed (image right). The classification was layered over a close up of the sun as coloured dots (image left).

MEDIA COVERAGE

Sonneneruptionen besser verstehen mit Machine Learning

Dr. Cédric Huwyler, Institut für Data Science I4DS, Fachhochschule Nordwestschweiz

Big Data Dialog, 3. Dezember 2018