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FAQ
General FAQ
What if we don't find anything?
Firstly, be optimistic! Secondly, regardless of whether or not we find a melt-patch, your classifications will be making a valuable contribution to the study of what dark matter could be. The less we find, the more that we're able to constrain the space of possible sizes and masses of macroscopic dark matter particles. Of course, we're all hoping that something will be found, but don't feel discouraged when submitting "no" classifications; they're useful all the same.
How can I learn more about macro dark matter?
Those looking for a more in-depth understanding of macro dark matter as it relates to this project are encouraged to take a look at the Education section and this this academic paper. This paper has more information on macro dark matter and its motivation more broadly.
Classifying FAQ
When marking a melt-patch, should I be exact?
Yes, it's important that your marking reflects the size and shape of the feature that you see, so please take your time when doing this.
If I'm not sure if something is a melt-patch, should I still mark it?
Yes, if you see a patch that is:
- A perfect ellipse (with possible small irregularities at the edge), and
- Black in color (with possible small variations in lightness),
even if you're not completely confident about its validity, you absolutely should mark it. Your markings will be compared with those of others to draw the final conclusions, so you shouldn’t worry much about making a mistake.
How do I know if I'm doing things right?
There is no proven, best way to search for melt-patches. So long as you're taking the time to look at each part of the images (even if just in your peripheral vision), and learning from the training images, you'll be doing alright. The field guide has some tips.
What if I see a melt-patch in a training image, but was told that I'm wrong?
If something like this happens, let us know about it by hitting "Talk" after submitting your classification and using the tag #trainingmistake in your post. It's quite possible that you're right and that we missed something when making the training images.
What if I see multiple melt-patches in one image?
Mark the one you're most confident about. Statistically, it's very unlikely that two would be found in such close proximity, but if you're reasonably sure about both, let us know by hitting "Talk" after submitting your classification.