Laguerre-Gaussian Modes: Final Summary

My freshman Monroe project essentially consisted of two main parts: imaging Laguerre-Gaussian laser modes and their superpositions for Louisiana State University’s machine learning research and testing the coupling of these modes and superpositions into a single-mode optical fiber.

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Laguerre-Gaussian Modes: Post #3

During my last week in the lab, I finished the fiber optic coupling part of my project. The data I collected led to more questions than answers, but that’s science. There’s a special excitement and beauty in knowing that the quest for knowledge will never truly end. This project has sparked my curiosity, and there’s so much more to learn now. Here are my activities and findings from my last days in Small Hall this July:

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Laguerre-Gaussian Modes: Post #2

Early this week, I completed the data collection for all the requested LG modes and their superpositions. I sent the images and matrices to LSU for our collaborators to inspect. We will hear back from them soon about their findings.

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Laguerre-Gaussian Modes: Post #1

Now that I’ve been on campus a week, I have a clearer idea of my project. My research advisor, Professor Novikova, and I modified the research proposal to reflect an exciting development in the lab. It turns out that the Quantum Optics Lab at William and Mary has embarked on a collaboration with its counterpart at Louisiana State University. LSU is currently applying machine learning techniques to optics. Machine learning is a branch of artificial intelligence. It involves algorithms that make decisions by learning patterns from data rather than by relying on specific instructions. Our collaborators at LSU are using machine learning to teach their computers to recognize and analyze laser modes. Right now, they need experimental data to test their algorithm’s accuracy. I get to collect this data. If successful, this algorithm will have applications in quantum computing and quantum information, especially with regards to data storage.

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