I suppose Friday the 13th is as good a day as any to launch a Citizen Science project.
For those of you who helped us classify the previous data set: Welcome back!
And hello to all of our new Sunspotters!
If you haven’t a notion of what Sunspotter is all about, check out our science section. In short, our goal is to determine the complexity of sunspot groups. It is well known (to solar physicists) that more complicated looking sunspot groups produce more solar flares than simple looking ones. But so far, scientists have not found a good way to quantify sunspot group complexity. This is not a task easily accomplished by a computer. Humans, on the other hand, can easily point to the more complex in a pair of objects, ideas, images, and so on.
I’m pretty sure you have an idea of which is the more complex: a graduate text on quantum mechanics, or an Italian cookbook?
On the other hand, it would not be straight-forward for a computer to make that choice. The same is true with sunspot groups.
In round one (lasting only a month!), ~1,600 volunteers helped us to rank ~13,000 images of sunspot groups by choosing the more complex one in ~300,000 pairs of images. This has allowed us to quantify ‘true’ sunspot group complexity for the first time! Now that we have a handle on how to give complexity a number, we want to determine how the complexity of a sunspot group changes over time.
To do this we have automatically detected thousands of sunspot groups and tracked them over time. Each sunspot group has been detected about 15 times per day. Some of these sunspot groups were included in the previous dataset, but now they are being detected in a different way. That means that you will see a number of similar-looking images- but don’t worry if you can’t tell which sunspot group is more complex, just do your best! When graphing the complexity of a sunspot group over time, we are hoping to see clear jumps in the data when the sunspot group became more complex and we expect this to be followed by the occurrence of solar flares.
There are a few ‘biases’ that we could not easily correct for with the previous dataset, that we hope to get a handle on this time. For instance, depending on a sunspot group’s position, it will look more squished as it nears the edge of the Sun. As mentioned in an earlier post, we are now using a projection technique to ‘de-squish’ the sunspot groups. Also, it is likely that the most complex sunspot groups are always the largest. However, humans might also be biased toward thinking bigger things are more complex, even when they are not. So, to help reduce this bias, we have ‘de-scaled’ the images so that all of the sunspot groups, big or small, will appear roughly the same size on your screen.
We think you will find it much easier to focus on complexity with this new data set.
Thanks for listening, and happy classifying!!
After our brief hiatus, we are about to launch the next phase Sunspotter this Friday! As we mentioned before, there will be >200,000 images. Ranking the sunspot group complexity of this new dataset will require literally millions of clicks. This time we are trying to learn about the evolution of complexity in sunspot groups.
Last time, our goal was to obtain a quantitative measure of sunspot group complexity- the results of this are exactly what I presented to the attendees of the 224th American Astrophysical Society meeting in Boston, MA, last week. My talk was well attended by sunspot and solar flare experts who asked a number of insightful questions about the data analysis method, and about how data was presented to the hard-working volunteers.
You can view the slides from the presentation on FigShare. I will be writing an in-depth post explaining the methods and analysis techniques used to get these results as we pull the journal paper together for publication.
Hope to see you all on Talk.Sunspotter.org soon!