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Author: William Carroll | Major: Physics | Semester: Fall 2023
During the fall of 2023, I worked with my research professor Dr. Hiro Nakamura to develop collinear and noncollinear autocorrelators for the analysis of ultrashort light pulses.
Ultrashort light pulses are very intriguing because they are some of the shortest events on the planet that we can control. They typically last on the order of picoseconds (10-12 seconds), femtoseconds (10-15 seconds), or even attoseconds (10-18 seconds). One use of ultrashort light pulses is the ability to be able to study ultrafast dynamics, such as the behavior of electrons or excitons (electron-hole pairs).
In order to measure an event, you need a shorter event to be able to compare it with. For example, if you were to take a picture of a bubble popping, the shutter speed of your camera would have to be faster than the bubble or else you won’t be able to capture the event. This becomes much trickier as we deal with shorter and shorter. Since there aren’t any cameras nearly that fast, we will need another method to measure these ultrashort pulses.
This is where autocorrelation comes in. Autocorrelators bypass this problem by measuring the pulse with the pulse itself. This is accomplished by splitting the beam with a beam splitter. After the beam is split, it will hit 2 mirrors equal distances apart, but one mirror will be oscillating back and forth in order to delay the beam. As the beams recombine and are focused into a photodetector, you can measure the interference between the two beams. When we analyze this interference data, we can extract details about the pulse duration and shape.
Figures 1 & 2: Pictures of the noncollinear autocorrelator. The tsunami beam is first split by the beam splitter. The beam that travels to silver mirror one is delayed by oscillation. The beams are then recombined and the parabolic mirror focuses the beam into the Gallium phosphide photodetector.
Parts of the noncollinear autocorrelator were set up by a previous student, Skyler, who I worked under my first few months in Dr. Nakamura’s lab. This is initially how I became interested in autocorrelation. After he graduated, I began working with his setup by first collecting autocorrelation data with his setup in order to confirm that the laser we were using was pulsing in the femtosecond regime. A few things on the setup had to be modified to achieve the desired data. First, the system had to be realigned because a beam splitter was added, splitting the initial laser to allow for another student to use the laser at the same time as me. This process took a shockingly long time. Optics require very precise alignment, especially when trying to achieve interference (getting the two separate beams on top of each other when they recombine. You know you have achieved this when you see little slits(fringes) in the beam). Working with the beam splitter also made it hard to achieve the angles I was trying to get. Thankfully, Sudeep, the person sharing the laser with me, is very knowledgeable and even more patient. With his help, we changed the beam splitter being used to a smaller one in order to achieve the desired angle for interference for my setup. Another graduate student, Seth, helped me achieve interference with the autocorrelator. I also had to change the spring that oscillated the first silver mirror. Although this might seem simple, I had to try many springs that did not work. They were either too strong and didn’t allow the mirror to oscillate, or they were too weak and wouldn’t pull the mirror back. Also, many of the springs were too short or too long.
The next step after I acquired the autocorrelation data was to analyze it. I did this using python. The goal with this was to turn the raw data from a csv file into a usable graph by fitting the pulse shape. To start this, I used code from another graduate student, Sneha, and some sample data from her project. Once I was able to fit the curves with her data, I began attempting to do it for my data.
Figure 3 & 4: Sneha’s data with the fit curve overlaid on it. The left picture is a Lorentzian fit and the right picture is a Gaussian fit.
Unfortunately, I was unable to fit the curves for my data or build the collinear autocorrelator before the end of the semester. However, I learned a lot about autocorrelation as well as nonlinear optics as a whole. I also got a lot of experience with python which I had never used before the start of this semester. Thank you so much to the Honors College for the funding which allowed me to focus on this research during this semester. I’d also like to give a huge thank you to Dr. Nakamura for helping me every step of the way. Also, thank you to Sudeep, Seth, Sneha, Skyler, Ram, Ethan, and Kate for answering all of the questions I have not only about research, but college as well. I stand on the shoulders of giants and without you all, I would not even be close to where I am now.