May 27, 2026
Junyu Liu, an assistant professor for the Department of Computer Science, was recently awarded an NSF grant for his research collaboration with the professors from the Pitt Swanson School of Engineering.
Liu, along with Swanson professors Juan Jose Arenas Mendoza and Peyman Givi, are currently using their awarded NSF grant to support their research project, titled “Simulating fluid dynamics using hybrid quantum-classical devices.” The grant gives this team $543,305 to work with, which began Feb. 1, 2026, and is estimated to end Jan. 31, 2029.
Liu and his collaborators are using the grant to explore how emerging quantum technologies can help address some of the most difficult computational problems in classical physics and engineering; some of these problems include the Navier-Stokes equations, reaction-convection-diffusion equations, turbulence, combustion, direct numerical simulation, and large eddy simulation. Liu said looking for a solution to these issues is critical for multiple different fields.
“These are central problems in engineering and applied science, but they are extremely challenging for conventional computing because they involve many interacting length and time scales,” Liu said. “Turbulence and combustion remain among the most challenging problems in science and engineering.”
To address these issues, the team is bringing together their personal experiences in quantum computing, computational fluid dynamics, turbulence, and combustion. The project allows Liu to use his focus on quantum computing, quantum algorithms, and quantum technologies for scientific applications, to support this new research.
“This grant supports that direction by allowing us to connect quantum computing with a concrete and important class of scientific problems: nonlinear partial differential equations and fluid dynamics,” Liu said.
The research project includes looking at two different, complementary approaches to learn more about hybrid quantum-classical devices simulating fluid dynamics. Liu explained the two approaches being used include tensor networks and analog quantum simulation.
“Tensor networks can compress very large scientific datasets and may allow fluid dynamics problems to be represented efficiently on quantum computers,” Liu said. “The second [approach] uses analog quantum simulation, including Koopman-von Neumann-based methods, to represent nonlinear dynamical systems on quantum hardware.”
The effects of this research go farther than simply solving computational problems. Liu explained that what his research team learns will then be able to support other research fields.
“Advances in this area could eventually affect aerospace engineering, energy systems, propulsion, atmospheric modeling, plasma physics, and other fields where fluid flow and transport phenomena are important,” Liu said.
Liu said the project even has an important educational impact on future quantum computing learning.
“Quantum computing is becoming increasingly relevant across science and engineering, and this grant helps train students to work across computer science, physics, and engineering,” Liu said.
The monetary support for this interdisciplinary and quantum computing research is significant because it supports such a collaborative project. Liu said this funding importantly supports the newer quantum computing field and interaction between different fields.
“Funding like this is essential because quantum computing is still an emerging field, and many of its most important applications require sustained, high-risk, high-reward research,” Liu said. “It allows us to pursue ideas that may not fit neatly into one traditional field but have the potential to create new directions for computing, engineering, and science.”
Liu and his fellow research team members have created a project that not only will have far-reaching effects on other scientific fields but also supports the focus and research passions of those involved.