Post Contributors: Carlee Markle & Christina Hollyday
In this module, we focused on stars, especially star clusters. We measured their brightness and colors based on their distance from our observation point. Luminosity and intrinsic color were also studied, these elements being universal and not dependent on the position of the observer. We observed three different clusters of different ages, one young, one intermediate, and one old.
We also looked at HR diagrams, in which the cluster’s luminosity distribution is compared to the cluster’s intrinsic colors. These HR diagrams are used to measure the stars’ age and metallicity. We actually used these HR diagrams to improve our images– from the diagrams we were able to obtain the E(B-V) Reddening value which we input into Afterglow during photometry to ensure our images are presented in true color.
Cluster images
Young (NGC 3293)
Intermediate (NGC 4349)
Old (NGC 3201)
Like I mentioned in the introduction, all of these photos are in true color, meaning if we were to throw you into space somehow these are the colors your human eye would pick up on. We did this by balancing our colors using photometry and eliminating some dust reddening after we made our HR diagrams-- but I'll get to that in a second.
Image acquisition / processing
The data for NGC 3292 and NGC 3201 was all taken on PROMPT-6.
The data for NGC 4349 was taken on both PROMPT-6 and PROMPT-MO-1.
We used the following filters: B, V, R, and I. The following chart shows the filter, amount of exposures, and the time for the exposure.
Filter | Number of Exposures | Exposure Time (sec) |
B | 1 | 30 |
V | 1 | 20 |
R | 1 | 10 |
I | 1 | 15 |
We repeated this set of exposures five times with 30-minute delays so we actually ended up with five exposures in each filter. We did this to avoid “ghost” images from previous observations.
As far as processing goes, we first cleaned and aligned the images in Afterglow in order to ultimately stack our images by filter. We grouped the B, V, R, and I filtered stacks and colored the B blue, V green, and R red. The I filter was turned off and is not visible in our final image. In order to color balance the stacks, we compared the three stacks to the known colors and brightnesses of background stars. We set the brightest star to be white, causing all other colors in the image to become relative to it. We then used Photometric Color Calibration to calibrate the colors, with the reference layer being the bright star in our image. We then adjusted different levels in the image such as midtone level, background level, etc. until we were happy with the final image.
HR Diagrams
We used Cluster Pro Plus to upload our photometry file in order to plot two HR diagrams. These are intrinsic HR diagrams, therefore we use the following axis for our graph: The x-axis of each diagram is the temperature/color (the difference of the objects magnitude in a shorter wavelength filter and its magnitude in a longer wavelength filter). The y-axis is the quantity of the star’s brightness, its luminosity.
We created two HR diagrams for each cluster, one with just our captured data and one including archival data from Gaia and 2MASS. To create them, we uploaded our photometry data and then tweaked different settings in Cluster Pro Plus to best fit our data to the model (isochrone). To ensure we were actually viewing the data for our clusters and not just field stars acting as obstacles we limited the RA/DEC we were looking at to best fit the most condensed areas of data. The different settings we tweaked to fit our data to the isochrone were age, metallicity, and E(B-V) reddening.
View our HR diagrams below.
SKYNET DATA ONLY
SKYNET + ARCHIVAL DATA
After creating all of these HR Diagrams we went back into Afterglow and utilized our new measurement of E(B-V) reddening to color-correct our images into the ones you previously saw at the beginning of the post. For reference, here is a side by side of NGC 3201 before and after this color correction.
Analysis
Here is our calculated average of our measured Age (in log years), Metallicity, and Reddening for both Skynet and Skynet + Archival data. We obtained these numbers by averaging the values each of our group members collected.
We regard the Skynet + Archival data findings to be the most accurate as they have larger sample sizes than just the Skynet data findings.
Taking one quick step back to HR diagrams, we ran a little experiment in class to see if we could match/identify the ages of another group's images based off of the HR diagrams they created. How might this be done? Well, the age of the cluster can tell us a lot about the color of the stars inside of it -- or the other way around. Younger stars appear bluer in color while older stars appear red. Anyways, both our group and the group we swapped data with were able to correctly identify all three images in order from youngest to oldest and get within ballpark range for age guesses as well.
Final remarks
This project was very fun and informative. I enjoyed the HR diagrams and how we could actually use the data from them to create a true color image. The class experiment was also very cool, it was nice to put our learning and observations into action to test what we actually have learned.
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