The following is from Gabriel Weiderpass after TAing the lab for the first time in Spring quarter 2024.

“Hello Mark,

I TAyed the lab yesterday and you mentioned that you wanted some feedback on how it went. In general the experiment was great! It was interesting, getting the picture was non-trivial, the students took a reasonable time to finish, etc. Now more detailed comments about specific points

1) First the main problem that we faced is that the wiki and the phyton code were a bit too vague on what they had to do. So the students struggled a long time to even figure out what they were supposed to do.

For example after they “Split Channels to create three separate grey scale images from the R, G and B values.” they get three pictures in scales of R, G, and B. First, is the splitting in R, G, B the same as the one we defined on the phyton code, that is in Phyton we used 660nm for red, 530 for green, and 450 for blue. Is this what Image J is using? How do we even compare these R, G, and B splits of Image J with the phyton code? After that what are they supposed to do with these images? Can I get a table of intensity as a function of pixel distance to plot that on phyton? But then there is no part in the phyton code to import any data.

They were also very confused on what they should be doing on the last part. I told them that they were suppose to compare the peaks of their RGB split with the theoretical value of the plot above and therefore get the thickness of the film as a function of where you are in the image. This is what I understood and what I remembered from the lab training but it would be good if there was a bit more information on the wiki about their objectives.

2) The format of having the students read the paper beforehand worked. There were only two students (out of 11) that I noticed that hadn’t read the paper. One because he was destroyed in the quiz and the other because he was reading it when I arrived at lab.

3) Another small issue is that the students struggled to understand the importance of having good pictures to improve the data analysis. Even though I explained to them many times that having a good picture would produce a better reading in FIJI J and then would lead to more well defined peaks and make the whole analysis better, a lot of them didn’t got it. In the end I actually open the computer and analyzed a bad and a good picture and showed them the difference, in the bad picture the peaks are supper jagged and ill defined. It might be worth including in the wiki a small discussion on the importance of getting a good picture for the data analysis.

Those are all the points that I remember from yesterday.


Gabriel Weiderpass”


End of Quarter TA Evaluation

Before we start today's lab, we are asking all students to complete a short (<5 minute) survey in which you will have a chance to provide feedback on your TA. Your answers are anonymous and will not affect your grade in any way. You may access the survey from your personal computer, a lab computer, or your phone.

At the end of the quarter, TAs will receive average scores and comments (without identifying information) from their lab section(s).

Do not include any identifying information in your responses. If you have any feedback to provide to which you would like a response, please send it to Mark Chantell (

If you cannot or do not want to complete the survey now, you may complete it at home. The survey will remain open until Saturday, May 11 at 5:00 pm.

Thin Film Interference

For your final PHYS143 lab you will perform an experiment to measure the thickness profile of a thin film. Your work will be based on a paper published in the American Journal of Physics titled Investigating Thin Film Interference With A Digital Camera, Am. J. Phys. 78, 1248–1253 (2010).

A copy of this paper can be downloaded here.

You will do this final lab in a style which is more analogous to the way in which physicists do research in an experimental lab. You will begin by reading the paper before coming to lab. Your time in the lab will be spent reviewing the details of the experiment as presented in the paper, including building a model to represent the behavior of your detector system. Interestingly your detector is comprised of your eyes as sensors and your brain as an image processor. Once you understand how light interacts with a thin film, and you have modeled the response of your detector, you will use your cell phone and image analysis software on the lab computer to collect and analyze data to confirm the accuracy of your model, and then to measure the thickness profile of the thin film.



Lab Notebook

Click here to get a copy of the lab notebook. Don't forget you need to be logged into your UChicago google account to access the document.

Detector Modeling



FIJI (Also known as ImageJ)

Open files using File Open.

To obtain an RGB profile

  • Use the Line tool to draw a line through the section of the image you want to generate a profile along.
  • From the Plugins menu, select RGB Profiler.

To separate out the Red, Green and Blue channels

  • The image will need to be oriented so that the interference bands run left to right instead of top to bottom. From the Image > Transform you can select one of several options to rotate the image.
  • Use Image > Color > Split Channels to create three separate grey scale images from the R, G and B values.
  • Use the Rectangle tool to draw a narrow rectangle across the interference fringes you want to analyze.

To read X and Y pixel values from an image in FIJI

  • Unordered List Itemse the Point tool.