Title: Statistics of Flare Evolution|
Type of Project: Data analysis, statistics
Interest in analyzing observations for a large sample of events. Some programming experience would be useful but is not strictly necessary. The work will be conducted primarily using IDL and Python.
Mentor: Dr. Henry "Trae" Winter III and
Dr. Katharine Reeves
Solar flares are the largest explosions in the solar system. The largest flares can release 1033 ergs of energy. That is 10 million times more energy than all of the nuclear weapons ever created. How the Sun transmits, stores, and then releases so much energy is not well understood. In this project we will study a large number of solar flares in order to better understand the mechanisms of energy storage and release better.
It is difficult to determine exactly when a solar flare will occur.
In the past, the most advanced telescopes had a very limited field
of view and missed the majority of flares. This meant that a very
few flares were studied in great detail. The solar observing
Atmospheric Imaging Array (AIA) suite of telescopes launched
onboard the Solar Dynamics Observatory (SDO) satellite has
drastically changed the nature of flare observations. The full Sun
is now observed in amazing detail 24 hours a day, 7 days a
week providing ~3 terabytes of uncompressed data a day. In order to
handle this massive influx of data automated tools have been
created to detect and analyze events on the Sun. The "Flare
Detective" records about 65 flare events a day or over 23,000
events over the mission lifetime so far. This has created a tremendous data set that has only barely
been mined. In this project, we will study a large number of
flares using advanced statistics. We will study how flares erupt and
their impact on surrounding regions. We will also determine the
relationship between large flares and the smaller "mini-flares" that
are ubiquitous on the Sun.