Organizer: 刘锦鹏

Abstract: Can we compute on small quantum processors? In this talk, I explore the extent to which noise presents a barrier to this goal by quickly drowning out the information in a quantum computation. Noise is a tough adversary: we show that a large class of error mitigation algorithms -- proposals to "undo" the effects of quantum noise through mostly classical post-processing – can never scale up. Then we'll journey into the wild west of non-unital noise, a theoretically understudied class of noise (including damping and photon loss) that predominates on certain physical platforms, and study the task of estimating expectation values in its presence. Having presented some no-go theorems about inference in the presence of noise, I'll attempt to make lemons out of lemonade by turning to cryptography, where I will propose a new hardness conjecture, based on the task of decoding random stabilizer codes.

Brief bio: Yihui Quek is a postdoctoral fellow at MIT, working with Peter Shor and Aram Harrow, and in August 2025, she will start as an Assistant Professor at EPFL in Switzerland. In the last three years, she has also been a visitor at the Simons Institute for the Theory of Computing, a Harvard Quantum Initiative research fellow at Harvard University and a Alexander von Humboldt fellow at the Free University of Berlin. She is driven by the question: "What can theoretical computer science teach us about physics in the age of supercomputers?" To the question of whether she is a physicist or a computer scientist, no computationally bounded algorithm can have a significant advantage over random guessing.