Task 0: Install AstroImageJ. Using Windows Explorer, copy the ZIP file fromAstroImageJ\AstroImageJ.exe ThisPC/shared/Student/PHY_Share/Public , and save it on your computer. Locate the file in Windows Explorer, right-click and choose "Extract All". This will create a folder starting with AstroImageJ. Inside that folder is another folder called AstroImageJ. You can run the program by double-clicking on AstroImageJ\AstroImageJ.exe.

Note: You may get several windows asking for permission to run the program. Click "OK" to these. If you get a window requesting permission for AstroImageJ to get through a FireWall, click cancel on that window only.

Task 1: Open AstroImageJ. You are presented with the main window, as seen in figure 14. Load all of our images by choosing File > Import > Image Sequence... Navigate to the folder that contains all the .fit images, select one, and click Open.

You will be presented with a second window presenting options for loading an image sequence. Here it is extremely important that you tick the Use Virtual Stack box. If you don't the PC will attempt to store every picture at once into it's memory. You may get lucky, or you may cause your PC to grind to a painful halt.

Task 2: Align the images by choosing Process > Align stack using WCS or apertures... This brings up the stack aligner window (figure 3). Make sure the Use previous N apertures box and the Align only to whole pixels boxes are unchecked. Make sure the Show help panel box is checked.

The radii of the object aperture and sky annuli are not too important, but you might want to make sure the object radius is set to a reasonable value, since if the star lies outside this radius, AstroImageJ will not be able to calculate the image shift. Set this value to somewhere in the range 15-20.

Click OK to begin selecting stars to use for alignment. Left click on a star to add an aperture around it. Add two or three bright stars to use for alignment and press Enter or right-click to begin the alignment procedure.

AstroImageJ will now look for a star within each aperture, and measure the centroid of those stars. For each image, it uses the centroid of the stars to estimate the image shift.

When AstroImageJ has finished, you should have a new ImageSequence already loaded called "Aligned". Hit the button to run through the images and check the alignment.

Task 3: In the photometry window, click on a star, then choose Analyze > Plot Seeing Profile... You should end up with a plot like figure 17. Based upon this plot, decide how large you want your aperture sizes to be.

You will need to consider what effect using an aperture that is too small, or one that is too large, may have on your data.

Task 4: Open the Multi-Aperture photometry tool by choosing Analyze > Multi-aperture... Set the radius of the object aperture, and the inner and outer radii of the background annulus to the values chosen earlier.

Make sure the various options boxes are marked as indicated in figure 18, and click Place Apertures to begin. Aperture placement is done in exactly the same way as when you aligned the images.

Figure 19 shows a plot of the sky centred on SZ Lyn. The orientation of this image is not the same as the images from ROSA. Place your first aperture around SZ Lyn, and at least one other aperture around a comparison star. When choosing a comparison star, you should choose an unsaturated, bright star. If possible, it should be brighter than SZ Lyn. Why?

Once you've placed your apertures, right-click or press Enter to start performing photometry.

Task 5: Save your data to a Tab-Separated Values text file by clicking in the Measurements window and choosing File > Save As...

You have two options to make a plot from the data in this file. You can use Excel, or upload the saved file to CoCalc and plot it using Python. If you choose the latter route, you will find the text file hard to read in using NumPy, because some of the columns don't contain numbers. Instead, you can use the Pandas library instead, and use something like the following code snippet to read in the file:

# use the Pandas library 
import pandas as pd

# read in the data, explaining that columns
# are separated by tabs (\t)
data = pd.read_csv(delimiter='\t')

# you can access data directly by column name
x = data['J.D - 2400000']
y = data['rel_flux_T1']

Use your preferred method to make two scatter plots, one of JD vs Source-Sky_T1 and another of JD vs rel_flux_T1.

Notice how using relative photometry has corrected the large jump that occurs in the plot of the counts from the target star. This jump is associated with a change in position of the stars, but it has affected our target and comparison star equally, so it is not present in the count ratio plot.

Task 6: Re-run your aperture photometry with a few different aperture sizes, and save the results. You will need to Clear the Measurements table each time. Leave the sky annulus unchanged for now, and simply change the object aperture radius.

For your new measurements plot JD vs rel_flux_T1 in each case. Try to plot them on the same graph, and add a small offset to each dataset in y, so you can see the curves.

Which aperture size is best? What does the light curve look like when the object aperture is too small? What happens when it is too big? See if you can understand these effects.

One final thing to think about - if you use a small aperture radius like 2 pixels, much of the light from your object is falling outside your aperture. Why do you still get a reasonable lightcurve?