Avi Vadali: The High School Researcher Making Waves in Quantum Computing
Quantum computing has long been a domain reserved for seasoned scientists and academic researchers. However, Avi Vadali, a high school student at the time, challenged this norm by not only joining a research lab at the U.S. Department of Energy’s Fermi National Accelerator Laboratory but also co-authoring a research paper on machine learning and quantum computing. His work has gone through the rigorous peer-review process and is set to be published in the esteemed journal Quantum Machine Intelligence.
Vadali’s journey into the world of quantum computing began during the summer before his senior year of high school when he decided to explore research opportunities in the field. With a keen interest in physics and a background in math research, Vadali reached out to various professors and researchers across universities and national labs. Among them was Fermilab scientist Gabriel Perdue, who had previously delivered a compelling lecture on quantum computing during the Saturday Morning Physics program.
Impressed by Vadali’s enthusiasm and prior engagement with the subject matter, Perdue invited him to join his research team. However, Perdue remained skeptical about the productivity of a high school student, ensuring that Vadali’s academic performance remained his top priority. Nonetheless, Vadali surpassed expectations, proving himself capable of tackling complex tasks and approaching problems with a level of maturity beyond his years.
The focus of Vadali and the Fermilab team’s research was to develop a program that could predict the reliability of a quantum computer in solving specific problems. While quantum computers are exponentially faster than traditional high-performance supercomputers, they suffer from high error rates. Running complex calculations on quantum computers can be risky due to the lack of guaranteed reliability and the abundance of resources required.
To address this issue, the researchers utilized machine learning algorithms to predict the potential error in quantum computer calculation results. By assessing the predicted error, researchers could determine if running an experiment on a quantum computer would yield accurate and valuable results. Vadali played a crucial role in developing and implementing these machine learning algorithms, leveraging his prior coding experience and coursework in machine learning.
Reflecting on his time at Fermilab, Vadali emphasized the significant learning curve he experienced. From navigating scientific jargon to understanding the intricacies of conducting research at a high level, the experience provided him with invaluable insights into the world of academic research. Vadali credits his time at Fermilab as a decisive factor in his decision to pursue further research at the California Institute of Technology, focusing on studying fracton phases of matter, a subfield of condensed matter theory.
Vadali encourages other high school students to seek out research opportunities and not be disheartened by initial rejections. He believes that reaching out to professors and researchers can lead to significant opportunities and an early exposure to the scientific research process.
Avi Vadali’s journey serves as an inspiration to aspiring young scientists, demonstrating that age should not be a barrier to pursuing research in cutting-edge fields. His accomplishments highlight the importance of nurturing young talent and giving them opportunities to contribute to the scientific community. With his passion, determination, and early experiences in quantum computing, Vadali is undoubtedly a rising star in the world of scientific research.
Fermi National Accelerator Laboratory, supported by the U.S. Department of Energy’s Office of Science, continues to foster groundbreaking research and address some of the most pressing challenges of our time. Vadali’s story is just one example of the transformative impact of this institution and the importance of offering research opportunities to young minds.
For more information on Fermilab and the Office of Science, please visit science.energy.gov.