Research Scientist, Google Quantum AI
In this talk I will discuss our result on scaling surface code logical qubits which was recently published in Nature. I will give an introduction to quantum error correction, and explain why we see it as a key milestone towards our goal of a fault-tolerant quantum computer. I will then present our particular scheme, and explain why this result, where a larger code was implemented and outperformed a smaller code, is so significant. I will also present some results which help us look to the future and predict how our systems will behave in the future, as we improve in both system size and qubit quality.
Dripto Debroy is a Research Scientist with Google Quantum AI, focused on quantum error correction, calibration, and benchmarking. His interests lie in taking advantage of the structure found in physical error models to improve reliability in quantum computers. He has also done work on near term error correction, error mitigation through gate compilation, and development of physical error models.
He grew up in NYC and received his BS in Physics from the University of California, Santa Barbara in 2016. He then worked under Prof. Ken Brown at Duke University for my PhD, which he received in 2021.