This lab is based on a paper on the subject from AmJ. As the final lab of the PHYS140's sequence I have the following goals:

• Provide the experience of reading a journal paper and conducting an experiment based on it.
• Using a model to describe the expected behavior of the phenomena, and then using that to sanity check observations made during the experiment.
• Understanding that there any model for a phenomena has underlying assumptions baked into it, recognizing these assumptions and taking them into consideration while figuring out how to do the experiment.
• Demonstrating some “interesting” aspects of how sensors, including the human eye impact what you observe.

I want students to read the paper before coming to lab. To do this I ask the TA's and faculty to distribute the paper to the students during the week before the lab, and inform them that there will be a 5 minute quiz on the content of the paper at the start of the lab. The quiz is only there to motivate students to read the paper before the start of lab. Nominally I assign 1 point out of 8 for the quiz, but I tell TA's not to even bother grading it. The point is not how many right answers do they get, the point is having read the paper.

The quiz itself consists of 4 T/F questions which are trivial if you have read the paper. I tell TA's to give the students 5 minutes at the start of the class for the quiz. The questions are:

1) The sequence of colors produced by thin film interference is the same as what you see in a rainbow. (F)

2) The color sensors in the human eye and a digital camera both record light as Cyan, Magenta and Yellow values. (F)

3) Where the film is very thin (<50nm) all reflected wavelengths interfere destructively and there is no reflected light. (T)

4) The color of the reflected light depends on the thickness of the film. (T)

Students have seen interference, so the basic physics does not have to be presented by the TA. They should however be prepared to go over addititive color mixing as it applies to camera sensors and the human eye, both of which have R, G & B color sensors. An interesting aspect of this is that we (humans) perceive colors that do not exist in nature in the sense that they have no wavelength. Magenta for example is a mix of red and blue and does not appear anywhere in the spectrum of light. But since the camera and our eyes both combine information from R, G & B color sensors, we perceive magenta as a color.

To emphasize this fact I ask students to google a picture of a rainbow or white light spectrum and compare the colors and they sequence to what appears from thin film interference (TFI). This is a qualitative show & tell exercise, but I want them to notice that while the TFI pattern might at first appear to be the same as the visible light spectrum, they are not the same.

I provide a colab notebook that uses the model presented in the paper to calculate and plot both the interference pattern for three different wavelengths, and produce an appropriate color map. The notebook mostly duplicates what is in the paper and students do not use it to do anything quantitative. It is really more of a show and tell demonstration of how to use python to do this type of calculation. I do ask students to compare the color map produced by the notebook with the color sequence from their TFI photograph as a sanity check sort of thing. Yes, the paper does this but the moral of the story is that when possible you check these things yourself. I know giving the students code to do it is not the same as having them do it, but it provides a talking point for the TA's to engage with the students.

I also ask students to find on the internet an image of a rainbow or the spectrum from a prism to compare with the color map from TFI. The question is are they the same? I have found that many if not most students assume TFI produces a rainbow effect. But rainbows and prisms do not produce colors that do not exist.

Doing the actual experiment is pretty straight forward.

1. Put some soapy water in your plastic dish.
2. Dip the open end of the 35mm film canister into the soapy water, remove and lay on its side at the edge of the table.
3. Illuminate the soap film with the lamp using the LED bulb.
4. Correctly position your camera and take a good photo of the interference pattern.
5. Return to step 2 each time the soap film breaks before you get a photo.
6. Return to step 2 each time you end up with a crappy photo.
7. Upload the photo to your gsuite or email it to yourself.
8. Log into your UChicago Gmail account on the lab computer and download the photo.
9. Open the photo in FIJI and begin analyzing.
10. Return to step 2 when you find out your data sucks because you took a poor photo.

There are lots of ways that students will take bad photos, and they will tend to try to use them and complain when their data sucks. TA's need to pay close attention to the photos students are getting and mentor them to think about what they need in order to be able to get good data from their photo. The main considerations are:

• The camera should be as orthogonal to the plane of the bubble as possible, and centered on the middle of the bubble.
• Angle of incidence equals angle of reflection, so the light source needs to be as orthogonal to the plane of the bubble as possible, and centered on the middle of the bubble as possible.
• The above two points constitute a mutually exclusive phase space. But with practice and over multiple attempts you can get pretty close. Remember an assumption in the model is that the angle of incidence is small enough that it can be treated as being normal to the surface of the film.
• Best results are obtained when both the light source and camera are positioned as close as possible to the film.
• The image of the film needs to fill maybe 1/3 of the frame. So placing the camera as close as possible and using a long focal length lens (telephoto) works best.
• The interference bands will need to be as horizontal as possible.
• Small, off axis, rotated and poorly illuminated photos will be the default for many students.

The tools needed for the analysis are described in the wiki. Basically what needs to be done is..

• Rotate the image so the interference bands are horizontal.
• Use the line tool to create a line running the vertical length of the film over a region where the interference bands are clear, well illuminated and free of bubbles.
• Run the RGB profiler to get an intensity plot of the three color channels.
• Use the cursor tool to measure distances on the plot.

Using RGB profiler is easy, but unless the student got a really good image there will be a lot of noise on the intensity profiles making peak location less certain. A potentially better way of doing the analysis is:

• Rotate the image so that the interference bands are vertical.
• Use Image → Color → Split Channel function to create three separate grey scale images, each corresponding to one of the 3 color channels.
• Use the rectangle tool to draw a narrow rectangle across the film horizontally for one of the color channels.
• Use the plot profile function to generate the intensity plot of the interference profile.
• Use the cursor tool to make measurements.

This method generates less noisy interference profiles by averaging the data in each column of pixels.

The final result that students hand in and comment on is a plot showing the film thickness, optical thickness, vs location on the vertical axis in pixel units. An issue with this that was pointed out by Harry Fosbinder-Elkins is that the locations for each color are relative to the location of the first interference peak for that color.

I did not have time to figure out what to do about this so I left it as is. Going forward it would be worth thinking about whether or not there is a way to establish a non-arbitrary reference point for all of the colors. It might be possible to tease something out of the computational exercise that would make that a more meaningful part of the lab.