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A national research team led by quantum information scientist Gregory Quiroz at the ����ֱ�� Applied Physics Laboratory (APL) in Laurel, Maryland, has earned a competitive quantum computing award from the Department of Energy (DOE) to fund the engineering of potentially game-changing open-source software systems to propel scientific discoveries.

The award — one of 38 the for the development of quantum computing software for solving complex problems currently beyond the reach of today’s supercomputers — is the second this team has won.

“Winning two of these highly competitive awards is an incredible achievement and a testament to Greg’s and the team’s scientific leadership, technical insights and strong partnership,” said Joan Hoffmann, program manager of APL’s Alternative Computing Paradigms program in the Research and Exploratory Development Department (REDD).

Building on the success of their first funded project designing software that combats errors hampering today’s quantum computers, Quiroz and his team of six co-investigators aim to develop modular quantum software stack components to manage noise in the increasingly complex quantum computers planned for the near future. They’ve titled their software stack project SMART Stack — Scalable, Modular, cross-platform Adaptable, dynamically Reconfigurable, and error-Targeted approaches to quantum stack design.

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

“Quantum computers are currently at an inflection point,” Quiroz said. “They can achieve capabilities that promise to propel scientific innovation, but these systems still suffer from errors that obstruct large-scale algorithms and the realization of a quantum advantage over classical computers that will enable scientific discoveries.”

A main problem is noise. Quantum computer hardware is built from basic atomic units called qubits, which rely on engineered quantum particles such as photons, electrons or systems that replicate quantum particles, such as superconducting circuits. Quantum processors use these particles to perform complex calculations, but random molecular movements within and around the qubits generate noise that disrupts their ability to store information, causing errors and making today’s quantum machines unreliable and unpredictable.

Current quantum software stacks have made strides managing errors in currently available hardware through a variety of approaches, Quiroz explained, but they typically don’t possess the versatility required to exploit the rapidly changing technology. The SMART Stack team aims to develop the software infrastructure to bridge this gap.

For their first DOE award, Quiroz and team led a project called , delivering successful error management methods for quantum computers through the development of compilation tools for current-generation quantum computers consisting of tens to hundreds of qubits. The team’s success is represented in its numerous publications, demonstrations on cloud-based systems, DOE testbeds and software tools compatible with existing quantum computing application programming interfaces.

SMART Stack will build on these achievements by preparing for the larger, next-generation quantum processors expected over the next 10 to 20 years. The engineering team’s approach will involve tightly integrating the software stack of operating and control systems with hardware to fortify against errors and improve algorithm performance in emerging systems, including future heterogeneous models that integrate quantum computers with advanced classical computers.

The ambitious project is part of APL’s large quantum computer science portfolio focused on understanding and mitigating quantum noise and errors across the full stack of hardware and software.

“This project brings together large research lab and university partners, which enhances the importance of the fundamental research they’re conducting and results in broad, impactful solutions,” added Kevin Schultz, an assistant program manager for Alternative Computing Paradigms in REDD. “This applied research promises to get us to the point where we can field useful quantum algorithms for solving complex problems facing modern science.”