U-M part of $7.5 million federal grant to revolutionize quantum stack design

Gokul Ravi, assistant professor of computer science and engineering at the University of Michigan, is co-PI of a project that will receive $7.5 million in funding over five years from the Department of Energy. The project, titled “SMART Stack: Scalable, Modular, Adaptable, Reconfigurable, error-Targeted approaches to quantum stack design,” is being led by Gregory Quiroz of Johns Hopkins University, with several other institutions participating, including Lawrence Livermore National Laboratory and University of Chicago, in addition to U-M.

The funding is part of a recently announced $65 million Department of Energy initiative aimed at advancing quantum computing technology. The initiative spans 10 projects and focuses on components such as software, control systems, and algorithms that are critical to realizing the potential of quantum computers to solve complex problems beyond the abilities of classical supercomputers.

As quantum processors evolve to handle increasingly complex computations, their ability to manage and mitigate errors becomes increasingly critical to the realization of the extended problem-solving capabilities that they offer. To tackle this issue, the SMART Stack team aims to develop a quantum software stack that is resilient to errors, adaptable to a wide range of platforms, and capable of enhancing algorithmic performance in quantum computing systems.

“Quantum computing is nearing a pivotal moment where it could greatly enhance our ability to solve complex scientific problems,” said Ravi. “One of the challenges we face is managing errors, which can rapidly accumulate and limit the power of quantum algorithms.”

The SMART Stack researchers propose a multifaceted approach to address this challenge based on three main thrusts:

• Scalable error characterization and management: the team aims to develop cross-stack strategies that enable efficient error detection and correction, ensuring that quantum algorithms remain robust and reliable.
• Hardware-aware intermediate representations and compilers: the team will construct new intermediate representations (IRs) that provide compilers with essential information about hardware capabilities, enabling the development of compiler processes tailored to manage unique hardware errors.
• Cross-layer integration and evaluation: the team aims to design error management techniques that are scalable, modular, and can adapt to emerging quantum technologies. This includes developing iterative compilation tools to test and refine these methods using SMART Stack simulations and various quantum hardware experiments.

Through these activities, the SMART Stack project will lead to the development of new protocols, strategies, and open-source software to enhance error resilience across various quantum hardware platforms. By improving the accuracy of quantum computations, the project will accelerate breakthroughs essential for tackling significant scientific challenges.

In addition to Ravi as co-PI and Quiroz as lead investigator, the SMART Stack team includes Frederic Chong, University of Chicago; William Zeng and Nathan Shammah, Unitary Fund; Anders Petersson, Lawrence Livermore National Laboratory; and Pranav Gokhale, Infleqtion.

“I am thrilled to be part of this innovative initiative,” said Ravi. “By applying state-of-the-art software engineering principles to quantum hardware, our team is poised to push the boundaries of what’s possible in quantum computing.”