Quantum Enabled Predictability for Multiscale Nonlinear Complex Systems
Multiscale nonlinear complex systems are ubiquitous in nature and engineering and are often cursed by high dimensionality. Predicting their emergent behaviour across scales has been a longstanding challenge. Quantum computing promises an exponential speedup in dimension for solving linear systems. However, it cannot efficiently solve strongly nonlinear partial differential equations (PDEs) governing those complex systems due to the linear nature of quantum mechanics. In this talk, we will discuss how to harness the power of quantum computing to break the dimensionality curse of multiscale nonlinear complex systems, such as fluid dynamics, biosciences, and fusion energy science. In turn, we will discuss the fundamental limit of quantum advantage/disadvantage in solving nonlinear dynamics by utilizing the domain-driven development of quantum algorithms.
Bio: Xiangyu Li is a physicist from Pacific Northwest National Laboratory, DOE. Xiangyu earned his PhD from Stockholm University. His main interests are in nonlinear multiscale complex systems and quantum algorithms for differential equations.

