Computing Collaborations

Sandia and Google unleash new possibilities in quantum computing

Physicists from Sandia National Laboratories worked with a team of researchers at Google Quantum AI and other affiliated institutions over the last two years to explore potential applications of a quantum computer in high energy density science.

They were met with groundbreaking success when they produced a quantum algorithm to calculate electronic stopping powers in extreme conditions that are difficult to reliably create and measure in terrestrial labs. Such calculations occupy some of the NNSA’s Advanced Simulation and Computing (ASC) program’s largest supercomputers for 10s to 100s of millions of CPU hours per year, with applications in inertial confinement fusion and stockpile stewardship.

“Quantum computation of stopping power for inertial fusion target design” was recently published in the Proceedings of the National Academy of Sciences.

Sandia’s work is the first major use case for quantum computing in the stockpile stewardship program. “NNSA is committed to bringing the most promising novel and advanced computing technologies to accelerate and transform the science which underpins our national security mission,” said Thuc Hoang, Director of the NNSA’s ASC program which supports this work.

Quantum computing is an emerging technology that utilizes the principles of quantum mechanics to perform complex computational tasks. One of the most promising advantages that such machines might have is in reducing the number of steps required to implement certain calculations—sometimes by exponentially large factors compared to conventional supercomputers.

“Simulating otherwise challenging quantum systems was the original motivation behind Feynman’s initial proposal to build quantum computers; this still remains one of the compelling applications of the technology. However, much work remains to be done to identify exactly what problems will benefit most from quantum computing, and to refine quantum algorithms for those use cases,” said Ryan Babbush, Director of Quantum Algorithms at Google Quantum AI. “Since the Department of Energy is already one of the world’s largest users of classical high-performance computing for simulating quantum systems, we imagine it will be one of the leading consumers of quantum computing as well. Thus, Google is very enthusiastic to partner with Sandia National Labs to jointly explore applications of quantum computers for simulating material science problems of relevance to the Department of Energy.”

Future quantum computers are not only anticipated to solve certain scientific problems faster than the largest existing supercomputers, but they are projected to solve problems that would otherwise be intractable. One such problem is simulating quantum mechanical systems with systematically improvable accuracy. An application of these simulations is calculating stopping powers of the dense plasmas that typify the challenging warm dense matter regime.

“With today’s current supercomputing capabilities, researchers are forced to make the choice between speed and accuracy when simulating quantum physics,” said Andrew Baczewski, a quantum computer scientist at Sandia. “Future fault-tolerant quantum computers will enable quantum simulations that are both fast and accurate. In fact, they will realize accuracies that are infeasible to achieve on conventional supercomputers.”

Even with the promise of such revolutionary capabilities, quantum computing hardware is still relatively immature. Qubits, quantum bits, are extraordinarily susceptible to environmental noise and other sources of error in quantum computations. There are numerous science and engineering challenges that the national labs, industry, and academia will have to solve in scaling up this technology to achieve its full potential. “Current quantum hardware capabilities are still very far from what we would need to actually perform these stopping power calculations or many of the other practically useful simulation applications identified so far,” said Alina Kononov, a quantum computer scientist at Sandia.

In the meantime, researchers are still designing algorithms for these machines and optimizing the resources required for their implementation in the hopes of realizing useful quantum computers sooner.

Designing algorithms that can effectively utilize this unique technology is often counterintuitive. “It is often the case that good design choices for algorithms on conventional computers make for terrible choices for algorithms on quantum computers. And vice versa,” says Baczewski. “Simply translating the algorithm that one would implement on a conventional computer is unlikely to unlock the most significant advantages that quantum computers could achieve.”

The team’s stopping power algorithm exemplifies this. The first-quantized representation that the quantum algorithm relies on would require infeasibly large memories on a conventional computer, but it requires only a few kilobytes worth of qubits on a prospective quantum computer. Still, classical algorithms can provide valuable data to constrain the resource requirements for their quantum counterparts.

“Without large-scale quantum computers around to test quantum algorithms, researchers tend to rely on mathematically rigorous bounds that consider the worst-case scenario. But data from existing HPC calculations can help us analyze more likely scenarios,” said Baczewski. “We used such calculations to reduce resource requirements by several orders of magnitude in the stopping power algorithm,” added Kononov.

The result is a novel algorithm and resource estimates for implementing it for relevant ASC problems. The analysis indicates that quantum computers could achieve significant and useful quantum advantages relevant to our security missions.

As the ultimate limits of conventional supercomputers come into sharper focus, proving practical application of quantum computers is paramount in justifying the investment into the technology.

“This is just one critical step forward into the future of quantum computing,” said Rob Hoekstra, senior manager of the Extreme Scale Computing group at Sandia. “Sandia is excited to continue pushing the boundaries and pursuing all the opportunities this technology holds.”

Sandia has a long history in quantum computing research, including the fabrication of traps that can be used to store qubits in the states of ions floating above intricate arrays of control electrodes. Through recent work funded by the DOE Office of Science and in collaboration with Duke University, Sandia fabricated a trap (a) that is significantly larger than previous devices and employed novel techniques like perforated dielectrics (b) to reduce the amount of power dissipated in the trap. These technologies will need to scale by several orders of magnitude to implement the Google/Sandia algorithm, and pathfinding hardware research complements the theoretical quantum algorithms research highlighted in this article.

About NNSA: Established by Congress in 2000, NNSA is a semi-autonomous agency within the U.S. Department of Energy responsible for enhancing national security through the military application of nuclear science. NNSA maintains and enhances the safety, security, and effectiveness of the U.S. nuclear weapons stockpile; works to reduce the global danger from weapons of mass destruction; provides the U.S. Navy with safe and militarily effective nuclear propulsion; and responds to nuclear and radiological emergencies in the United States and abroad.  

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