Andromeda Project

“What’s a synthetic cluster?”

In addition to real clusters that appear in the images, the science team has inserted highly-realistic synthetic clusters into a portion of the images. These objects are essential to the scientific results we hope to obtain, as they allow us to determine which kinds of clusters can be detected in the images and which will be overlooked. Careful measurement of these limits will allow us to derive how Andromeda’s stellar clusters have evolved over time. Having you find these clusters is just as important for many of our science goals as the real clusters!

This task requires a significant number of synthetic test objects to make sure we can model how our ability to identify clusters changes due to different competing effects. These factors include cluster size, cluster age, and a cluster’s location in Andromeda and the density of stars in the image.

These synthetic clusters are also a way to provide some feedback on how you’re doing with cluster identification. Unlike the real clusters, we know where these objects are located in the image ahead of time. That allows us to tell you when you’ve correctly identified a synthetic cluster. If you’re finding the synthetic clusters, you are likely identifying new, real clusters as well!

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“What’s that?” Check out the Guide!

Are you curious about why some clusters look different than others? Wondering what’s up with the bright stars? We’ve put together a wealth of information about clusters and other Andromeda objects in the Guide. Check it out — and if you find something you still can’t explain, be sure to bring it up on the Talk site (might I suggest: #weird).

Many people have asked about “sinuous dust lanes” that appear as darker patches in the color images. Indeed, these are caused by the attenuation of light by filaments of dust in Andromeda that are situated between the majority of the stars in the galaxy’s disk and our viewing location. This dust will block more of the blue light than red light, so the presence of dust can be detected as regions where all of the stars are much redder or dimmer than their surroundings. These structures are typically large and extended, making it hard to understand what is going on at the small scale of the Andromeda Project’s search images. Below is an example of a large area cutout from our Hubble Space Telescope imaging to give a better example of what these dust filaments look like on larger scales.

Large scale Hubble Space Telescope images that show the structure of the dust filaments in Andromeda. The red box shows the size of a single search image for the Andromeda Project.

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Site Issues and Bugs

While we do our best to make sure the site is ready for everyone to use, problems will inevitably appear from time to time, particularly during the early days of the project. Please visit the “Help” board on Talk to report any problems – for best results, please provide a detailed description of the problem as well as the versions of your operating system and web browser. The development team is working hard to identify and remedy issues as soon as possible, so if you can’t use the site, please check back in a day or two when we hope to have fixed any problem you run across.

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“Am I doing it right?”

Yes, you’re probably doing great! Once you’ve gone through the tutorial, read the information provided in the Guide, and classified a few images, you have all the training you need to help with this project. The best advice: practice makes perfect! Make sure to use the B/W and Color image toggle button to look at all the available data, but don’t get stuck trying to perfect every image. Do your best and over time you’ll improve as you get the hang of it.

It is important to remember that many people will view every image. If you miss a cluster by accident, hit “Finish” too soon, or otherwise wish you could get a re-do on a particular image: don’t worry. We combine everyone’s classifications together to create the final catalog, and through this collective effort participants make up for any individual small errors that might occur along the way.

In fact, this strategy of averaging over many individuals has already show its usefulness in this project. Results obtained for a small number of images during pre-launch testing of the Andromeda Project show that the “wisdom of the crowd” leads to higher overall catalog quality than those constructed using identifications from professional astronomers. The difference is that instead of only two to four trained astronomers, where innocent mistakes by an individual have a relatively large impact on the final result, the Andromeda Project uses classifications from many people per image. The more people classify an image, the better the result will become!