Lab 5
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Oregon State University, Corvallis *
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Course
206
Subject
Astronomy
Date
Apr 3, 2024
Type
docx
Pages
3
Uploaded by loganrenee11
Black holes are something taught in science classes, but do we really know as much as we think we do about them and what their importance is? We can view data from the Transiting Exoplanet Survey Satellite, or the TESS satellite, to compare how a star’s brightness evolves over time. Just viewing from the naked eye may not show much, but being able to see graphs and specific data points gives us an idea of just how bright these stars really are and how that can change. While viewing these graphs, it will be pertinent to look for gravitational lensing. Gravitational lensing is how the black hole’s gravity affects the light of its surrounding stars. By viewing various graphs, we can determine the peaks that could be indicative of a hidden black hole. White circles and red squares help us see the peaks in the graph that lead to a black hole. The peaks could be hard to discover, it takes a close and careful eye to locate them accurately. Using this method, I expect to find a decent amount of blackholes. While I think I will locate blackholes, I also except to look over
some of the holes in the graph. I also expect to make errors on locating black holes. I will likely identify what is believed to be a black hole, but it really is not a black hole. Procedure
Begin by reading the background information on Black Hole Hunters. The research tab, team tab, results tab, and FAQ tab are all great places to read prior to conducting the lab. Once information has been gathered and you have a general understanding of the research, continue to “classify” the data. Looking at the graph can be tricky as there are many data points to look at. The data points are red squares, which show broad measurements of brightness, and white circles, which show a closer representation of data.
Within these points, there are peaks that will form. These peaks are indicators of a black hole formation. Highlight the peaks discovered and select done. If no peaks are detected, simply select done. Any graph images that you could be unsure of you can post in the discussion chat
for others to look. Having a fresh set of eyes could help point something out that you could miss after staring at numerous images back-to-back. Results
The first time I sat down with the images I viewed ten and figured I had discovered seven indications of black holes. After taking a break and coming back later and rereading the background information, I decided to start over as I don’t believe I truly discovered seven black holes. On my
second attempt at looking for black holes I viewed fifteen images. I kept going back and forth between the images and the examples I should be looking for. A lot of the points are grouped together and could look like peaks. This is very confusing, especially when you are looking at so many points at once. After viewing the fifteen images, I believe I maybe could have discovered two black holes.
It is extremely difficult to pinpoint exactly where the black holes are. So many of the points look like they could be peaks, but they are not. I learned that while black holes are not able to be seen by the naked eye, we are able to see them in graphs using data points. These graphs show light curves that suggest a black hole could be present. I learned that black holes are very hard to identify. We cannot see them; we must rely on data point and graphs to identify the peaks that could potentially indicate a black hole’s presence. I hypothesized that I would identify a good number of black holes. I only found what I believe to be two black holes of fifteen images. I did, however, make errors on locating black holes, as I also mentioned in the introduction. Summary
After reading background information on black holes, the team involved, and the process that is being used, you should get a brief understanding of how the team has been discovering black holes. The Transiting Exoplanet Survey Satellite (TESS) gives us data points to view and graph. These graphs allow us to identify peaks in the data set easier than simply looking at the dataset. While the data points look like they could create
peaks, I only discovered two possible black holes of the fifteen images I viewed.
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