Kowalski’s project is one of 29 to receive a total of $73 million in funding
Karol Kowalski selected to receive U.S. DOE funding for QIS research.
(Photo by Andrea Starr | Pacific Northwest National Laboratory)
Quantum information science (QIS) plays an integral role in shaping the future of our nation’s energy and national security landscape. The U.S. Department of Energy (DOE) recently announced a total of $73 million in funding to advance quantum science. The project “Embedding quantum computing into many‐body frameworks for strongly correlated molecular and materials systems” led by Laboratory Fellow Karol Kowalski from Pacific Northwest National Laboratory is one of 29 to be awarded this funding.
QIS merges quantum mechanics with computer and information sciences to understand how information can be analyzed, processed, and transmitted on the quantum scale. This has the potential to revolutionize many areas of science and technology, including computation and communications. The projects selected to receive this funding specifically focus on experimental and theoretical efforts to advance understanding of quantum phenomena in systems that could be used for QIS and the use of quantum computing in chemical and materials sciences research.
Kowalski aims to develop a hybrid classical and quantum computing infrastructure to study complex chemical processes in catalysis, photochemistry, and other fields. During these chemical reactions, molecular systems can be excited to various electronic states characterized by complex electron correlation effects. Their behavior can be observed using spectroscopic techniques at DOE X-ray light sources, such as the Advanced Light Source at Lawrence Berkeley National Laboratory and the Advanced Photon Source at Argonne National Laboratory. However, the spectra can be very complex to analyze. Kowalski’s methodology combines theory, high-performance computing, and QIS to generate novel algorithms and formulations to explain the behavior of electrons. These can be integrated into existing—and future—quantum computers to resolve challenges in the analysis of spectroscopic data.
“Ultimately, we want to provide a theoretical framework to make sense of experimental data and go beyond what computational simulations can do now,” said Kowalski. “We want to combine classical and quantum computing to address urgent needs in the Basic Energy Sciences portfolio.”
Published: August 19, 2021