Oral: Near-optimal quantum algorithm to simulate nonlinear fluid flows

Besides their promising advantages, quantum computers come with limiting factors such as errors due measurement as well as noise and decoherence, besides the fact that their innate linearity constrains possibilities of solving problems of practical interest, which are typically nonlinear. In this work we propose a hybrid quantum-classical methodology to solve nonlinear fluid flows, thus marking progress in the desired direction. Some salient features of this work include: (1) An effective linear embedding technique to solve the nonlinear Burgers flow problem; (2) A near-optimal quantum linear solver; (3) End-to-end and near-term strategies to preserve quantum advantage by addressing problems of state preparation, measurements, as well as noise and decoherence; and (4) In-depth analysis of the performance of simulations on high performance quantum simulators (QFlowS) and real quantum devices.