Uploaded September 2026 | Updated September 2026, 1 week ago
Argonne National Laboratory is a multidisciplinary science and engineering research center where scientists and engineers pioneer breakthroughs that address some of the world’s most pressing challenges. In this video, physicist Anna McCoy discusses an Argonne-led project under DOE’s Genesis Mission that uses artificial intelligence to automate and optimize the design of quantum computing experiments for nuclear physics.
Quantum computers could eventually enable scientists to simulate nuclear systems that are difficult to study using today’s classical computers. But translating a nuclear physics question into a working quantum computing program is highly complex. Researchers must determine how to encode the problem, select appropriate quantum algorithms, adapt them to specific hardware and fine-tune the resulting circuits — choices that can affect accuracy, computational cost and whether an experiment can successfully run on available quantum systems.
To address this challenge, McCoy and her team, working with Infleqtion, Northwestern University and Dakota State University, are developing an AI agent that automates much of the design process. The system explores different encoding methods, algorithms and hardware configurations, then evaluates the resulting quantum circuits for efficiency and expected accuracy. Using reinforcement learning, the AI identifies promising quantum workflows for a given nuclear physics problem without requiring researchers to manually test every possible combination.
The team’s initial work focuses on fundamental nuclear structure and scattering problems, with the longer-term goal of helping scientists tackle nuclear physics questions that remain difficult for both classical computers and manually designed quantum circuits. By automating and optimizing quantum experiment design, this approach could make advanced quantum computing tools more accessible and effective for nuclear physics research. Learn more about how Argonne is advancing this work under DOE’s Genesis Mission.
Find out more about Argonne’s role supporting the DOE’s Genesis Mission ►► anl.gov/genesis-mission/projects/ai-enabled-optimization-of-quantum-circuit-design-for-realistic-nuclear-problems
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ABOUT ARGONNE
Argonne National Laboratory seeks solutions to pressing national problems in science and technology by conducting leading-edge basic and applied research in virtually every scientific discipline. Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.
ABOUT THE DEPARTMENT OF ENERGY OFFICE OF SCIENCE
The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit the Office of Science website.
Argonne National Laboratory is a multidisciplinary science and engineering research center where scientists and engineers pioneer breakthroughs that address some of the world’s most pressing challenges. In this video, physicist Anna McCoy discusses an Argonne-led project under DOE’s Genesis Mission that uses artificial intelligence to automate and optimize the design of quantum computing experiments for nuclear physics.
Quantum computers could eventually enable scientists to simulate nuclear systems that are difficult to study using today’s classical computers. But translating a nuclear physics question into a working quantum computing program is highly complex. Researchers must determine how to encode the problem, select appropriate quantum algorithms, adapt them to specific hardware and fine-tune the resulting circuits — choices that can affect accuracy, computational cost and whether an experiment can successfully run on available quantum systems.
To address this challenge, McCoy and her team, working with Infleqtion, Northwestern University and Dakota State University, are developing an AI agent that automates much of the design process. The system explores different encoding methods, algorithms and hardware configurations, then evaluates the resulting quantum circuits for efficiency and expected accuracy. Using reinforcement learning, the AI identifies promising quantum workflows for a given nuclear physics problem without requiring researchers to manually test every possible combination.
The team’s initial work focuses on fundamental nuclear structure and scattering problems, with the longer-term goal of helping scientists tackle nuclear physics questions that remain difficult for both classical computers and manually designed quantum circuits. By automating and optimizing quantum experiment design, this approach could make advanced quantum computing tools more accessible and effective for nuclear physics research. Learn more about how Argonne is advancing this work under DOE’s Genesis Mission.
Find out more about Argonne’s role supporting the DOE’s Genesis Mission ►► anl.gov/genesis-mission/projects/ai-enabled-optimization-of-quantum-circuit-design-for-realistic-nuclear-problems
Still haven't subscribed to Argonne National Laboratory on YouTube? ►► bit.ly/2Vyzwvm
Join us on Facebook ► bit.ly/ArgonneFacebook
Follow us on X ► bit.ly/ArgonneTwitter
We’re on Instagram ► bit.ly/ArgonneInstagram
Connect with us on LinkedIn ► bit.ly/ArgonneLinkedIn
ABOUT ARGONNE
Argonne National Laboratory seeks solutions to pressing national problems in science and technology by conducting leading-edge basic and applied research in virtually every scientific discipline. Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.
ABOUT THE DEPARTMENT OF ENERGY OFFICE OF SCIENCE
The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit the Office of Science website.
