Portrait of Shi Jie Samuel Tan '23. Photo by Patrick Montero

What They Learned: Samuel Tan ’23

In his thesis, the double major in physics and computer science focuses on quantum error correction.

Shi Jie Samuel Tan, an international student from Singapore, majored in physics and computer science at Haverford and mathematics at Bryn Mawr College. His interest in quantum computing spans the disciplines and he focused on what’s called ‘quantum error correction,’ which is key to building fault-tolerant quantum computers that can run quantum algorithms.

Given the scope of his thesis, it fulfilled the major requirements for both computer science and physics. He was advised by both Professor Steven Lindell (from the Department of Computer Science) and Assistant Professor Daniel Grin (from the Department of Physics and Astronomy). However, his thesis topic was first introduced to him by his research mentors at the California Institute of Technology. 

“In the summer of 2022, I spent 10 weeks at Caltech and worked on my thesis research under the mentorship of Prof. John Preskill and Christopher Pattison,” Tan said. “It was during those 10 weeks when I was first introduced to the theory of quantum error correction and how it is essential for the construction of fault-tolerant quantum computers. Even after the summer, my mentors at Caltech continue to help me refine my research question and provide feedback and suggestions on the numerical methods I could use to extract insights from my research work. Both Prof. Preskill and Chris Pattison are theorists that ground their analytical and numerical work with strong experimental and practical relevance. I learned a lot about the importance of having regular conversations with experimentalists to understand the necessary theoretical breakthroughs that complement practical experiments by providing theoretical guarantees for experimental success. 

“While they were not experts in the field of quantum information, Prof. Lindell and Prof. Grin were extremely willing to discuss this subject matter with me. In fact, I was very inspired by the deep curiosity and desire to learn that they exhibited in our weekly meetings. Even though quantum error correction was not in their field of expertise, their well-posed questions were critical in helping me better understand the field of quantum information. I learned an incredible amount just from trying to explain my research work and crafting a clear exposition of the background information in my thesis. I believe that is the beauty of working with both off-campus and on-campus thesis advisors because you get the wonderful opportunity of working on cutting-edge research work that may lie beyond the expertise of Haverford thesis advisors but you still get the close interactions and support from your on-campus advisors that do not hesitate to learn the subject matter alongside you!”

Tan’s thesis work studies how resilient surface codes, a particularly promising quantum error correction code, is against error bursts—large surges in errors that arise in a single time step. 

“Quantum computing experimentalists have recently developed a strong interest in understanding what is the maximum error that surface codes can withstand as they attempt to protect the quantum information used by quantum computers.” Tan said. “My work establishes some of the theoretical foundation for understanding quantum errors that occur in a non-uniform way and provides concrete numerics that quantify the errors that the surface code can protect against. This helps quantum computing experimentalists to better understand the amount of physical resources required to insulate the quantum computers from error bursts to facilitate the construction of large, reliable quantum computers. However, more work needs to be done to understand the theoretical limits for how well we can correct errors that correspond to real world situations.”

One of Tan’s biggest takeaways was a chance to explain what he’s passionate about to the people around him. 

“Prior to writing my thesis, I often find myself shying away from sharing the quantum information research that I have been doing in fear that my explanation might be too cryptic or boring. In fact, I believe this is a common problem that STEM students might face because some of the work we do might be quite removed from the things we see and hear on a day-to-day basis. However, we have this wonderful year-long opportunity to hone our skills to craft a piece of writing or/and a presentation that attempts to demystify what we are passionate about. Throughout the process, I really enjoyed condensing the knowledge that lies within the field of my interest and designing the piece of writing that prepares my audience for my research work by building up bits and pieces of prerequisite information. I think it is a beautiful skill to be able to communicate what we love to our friends and family even when what we love might not be extremely accessible. The whole process of thesis-writing helped me to become closer with my friends and loved ones simply because we now share a deeper appreciation of what each of us is invested in. As a first-generation student, it can sometimes be hard to explain what I do in school to my parents. While my thesis on its own might still be very cryptic, I am now much more familiar with the ways I can go about simplifying the concepts of quantum computing so that I can share what I do with my parents. In some sense, it has really helped breach what seemed to be an insurmountable gap in the past.”

Tan will pursue a PhD in Computer Science at the University of Maryland, College Park in the coming fall, in addition to continuing his summer research work on quantum algorithms at the Theoretical Division of the Los Alamos National Laboratory.

“I will be working in the Joint Center for Quantum Information and Computer Science (QuICS) where I hope to perform research in the intersection of physics, computer science, and mathematics,” Tan said. “My thesis work has made me certain that I hope to deepen my understanding of quantum information—in particular, quantum error correction. However, I am also interested in quantum algorithms and quantum complexity theory and hope to explore those subfields of quantum information during my time at the University of Maryland.”

Looking back on his time at Haverford, Tan reflects on the people who have helped him most.

“I am not only grateful to my thesis advisors but also Joe Cammisa from Haverford who has helped me to set up my account for hannah, Haverford’s High-Performance Computing cluster,” Tan concluded. “Without his help, I would not be able to generate the important numerics that quantify the error burst rates that surface codes are resilient against.”

“What They Learned” is a blog series exploring the thesis work of recent graduates.