Solar Loop Mining for the Coronal Heating Problem







Data sets



 This work is supported by NASA Grant No. AISR-03-0077-0139,  issued through the Office of Space Sciences and by NSF Grant IIS-0431128


Goals and Objectives:


    We propose a data driven learning approach based on data mining to quickly sift through massive data sets downloaded from the online NASA solar image databases and automatically discover the rare but interesting images containing solar loops, which are essential in studies of the Coronal Heating Problem.


    The Coronal Heating Problem is one of the longest standing unsolved mysteries in astrophysics. Measurements of the temperature distribution along the loop length can be used to support or eliminate various classes of coronal temperature models. The temperature analysis of coronal loops is a state-of-the-art astronomy. In order to make progress, scientific analysis requires data observed by instruments such as EIT, TRACE, and SXT. The combination of EIT, TRACE, and SXT information provides a powerful data set that will yield unprecedented detail on the plasma parameters of a variety of coronal loop structures. The biggest obstacle to completing this project is putting the data set together. The search for interesting images (with coronal loops) is by far the most time consuming aspect of this project. Currently, this process is performed manually, and is therefore extremely tedious, and hinders the progress of science in this field. Our project aims to accelerate and automate the discovery of the rare but interesting images with solar loops.



The proposed solar loop mining scheme will rely on the following components:

  1.  Collection and labeling of a sample data set of images coming from both categories (with and without solar loops)
  2. An optimal feature selection strategy that will facilitate the retrieval task.
  3.  A classification strategy to classify the transformed image into the correct class.
  4.  Appropriate measures to validate the effectiveness of the loop mining process.


    This project will be implemented in three main phases that target the image databases collected by two different instruments, the Extreme UV Imaging Telescope (EIT) aboard the NASA/European Space Agency spacecraft called SOHO (Solar and Heliospheric Observatory) and NASAs Transition Region and Coronal Explorer (TRACE).


    Each phase will involve collecting and labeling a small sample of the images from the targeted instrument, for which a solar loop mining strategy is to be designed. This project will help support existing and future projects that attempt to answer one of the newest basic questions in solar physics: are coronal loops isothermal? The distribution of temperature in and along the loop may be an important constraint on the coronal heating mechanism. The improved understanding of the role of loops in the coronal energy balance from this project will enhance the science return from the SOHO and TRACE space missions, major assets of the solar physics community.


    Our contribution to solar image mining has the potential to accelerate scientific discovery in solar physics, and opens opportunities for similar applications in other problems that rely on massive image databases.


    Research that advances state of the art in solar physics will have a significant impact on society and other scientific fields because of the following reasons:

(i)                 The climate connection: the sun is a source of light and heat for life on Earth. Scientists strive to understand how it works, why it changes, and how these changes influence the Earth,

(ii)               Space weather: The sun is the source of the solar wind: flow of gases from the sun that streams past the Earth at speeds exceeding a million miles per hour. Disturbances in the solar wind shake the Earth’s magnetic field and pump energy into the radiation belts. Space weather can change the orbits of satellites and shorten mission lifetimes. Excess radiation can physically damage satellites and poses a threat to astronauts, in addition to power surges and outages on Earth, and hence needs to be predicted.

(iii)              The sun as a physical laboratory: the sun produces its energy by nuclear fusion, a process that scientists have strived for decades to reproduce by involving hot plasmas in strong magnetic fields. Much of solar astronomy involves observing and understanding plasmas under similar conditions.