For many of you, the most satisfying (or frustrating?) part of Round 1 was clicking on a synthetic cluster. This post explains what these clusters are and how we’re using them. Synthetic clusters help us to calibrate your cluster clicks. These clusters serve a similar purpose to a control group in biological and psychological experiments. We made the synthetic clusters, so we already know their age, mass, and size. We can use these to understand not only what types of clusters we find, but also what clusters we don’t find. For example, say that we find there are no clusters in Andromeda with ages between 100 and 200 million years old. This could either be because there are no clusters at these ages (an interesting science result!!!) or because we just can’t find them because they aren’t easy to detect. Only through using synthetic clusters can we differentiate between these scenarios.
For Round 1, we generated 3100 of these clusters and inserted them in random locations in 3100 selected images. Here’s an example of a portion of a field without and with a synthetic cluster:
We designed the synthetic clusters to be identified at about a 50% rate in Round 1. You exceeded our expectations by identifying ~65% of synthetic clusters! Here’s a plot showing how you did on identifying each of the Round 1 synthetic clusters:
Each dot in this plot is one of the 3100 synthetic clusters. The horizontal axis of this plot is the cluster’s brightness and the vertical axis is the cluster’s Round 1 clusterfrac (the fraction of all viewers that identified the object as a cluster). Color on this plot is used to indicate cluster age. The bright young clusters were the most easily identified, which you can see as the group in the upper left of the plot. On the other hand, old, reddish and dim clusters were the most difficult to find; these are at the bottom right of the plot. You can see that younger clusters tend to be brighter than older clusters; this is because big hot bright stars burn out quickly, and smaller dimmer stars live much longer lives, so clusters get dimmer as they get older. Younger clusters also often contain large well-resolved blue stars, making them easier to identify, while older clusters have fewer big blue stars and often appear as partially resolved orange patches, making them harder to identify.
One of the most important things we can learn from our cluster sample is what mass of clusters we can detect. The completeness is the fraction of clusters at a given mass that were identified. The plot below shows this completeness as we vary the clusterfrac. This plot includes clusters less than 100 million years old.
The horizontal axis is the cluster’s mass in solar masses and the vertical axis is the completeness, or the fraction of all young synthetic clusters that you identified. If you just look at the blue line it tells you that at 1,000 solar masses, nearly 80% of young synthetic clusters were identified by at least 35% of you. The take home message of this plot is that we’re detecting most of the clusters with masses more than a few hundred times the mass of the sun; this is a much lower mass than we can detect in most galaxies outside the Milky Way.
But our search for the truth is not yet complete! There will be more synthetic clusters in Round 2. We’ll be using these to test for consistency between Round 1 and 2 and to correct for biases in the detection of some clusters.