Episode 156 Abstract: Can we compute on the quantum processors of today? 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. Switching gears, we next explore the effects of non-unital noise, a physically natural (yet analytically difficult) class of noise that includes amplitude-damping and photon loss. We show that it creates effectively shallow circuits, in the process displaying the strongest known bound on average convergence of quantum states under such noise. Bio: Yihui's research is centered on the questions "How can we exploit the laws of Physics to compute faster, and how can our current explosive computational capacity aid the discovery of new Physics?" Her research uses computational complexity theory to guide the development of small, experimental quantum computers. She is currently a postdoctoral fellow at MIT, having also spent time at the Simons Institute for the Theory of Computing, Harvard University and the Dahlem Center for Complex Quantum Systems in Berlin. She obtained her PhD from Stanford University in Jan 2022 and a BS from MIT in 2016. Her research has been recognized by a Research Excellence award from IBM, a Quantum Creators' Prize from the University of Chicago and the Quantum Innovator accolade from the University of Waterloo.