When Christian Arenz started teaching quantum mechanics at Arizona State University (ASU), he expected the freshmen to look confused. But after a few weeks, that uncertainty often turned into excitement. Arenz, an assistant professor in the School of Electrical, Computer and Energy Engineering, came to ASU from Princeton and witnessed students gradually understanding the potential of quantum computing. This is a rapidly developing field aimed at solving complex problems beyond the capability of today's supercomputers, accelerating new drug development, and improving cybersecurity and financial modeling.
At ASU, scientists have applied quantum computing to accelerate materials discovery, optimize supply chain logistics, and develop new methods for artificial intelligence. They are also tackling underlying technical challenges to make quantum technology more practical.
"When people hear the word 'quantum,' they think, 'Oh, that must be very complex and mathematically difficult,'" Arenz said. "It largely depends on motivation and approach... Everyone can learn it."
Although quantum computing is still in the experimental stage, global interest is growing rapidly. According to a report by McKinsey & Company, quantum computing could generate up to $72 billion in revenue by 2035.
Quantum computers are expensive to build and maintain—estimated at tens of millions of dollars—and are extremely complex. ASU does not have its own quantum computer, but through the support of the Research Technology Office, researchers and students can use tools to simulate quantum computing algorithms on classical high-performance computers and potentially connect remotely to quantum computers, said Gil Speyer, director of the ASU Computing Research Accelerator.
The university also leads quantum collaborations connecting national labs, corporations, academic institutions, and startups. Through this cooperation, students gain direct access to top-tier education and training opportunities, acquiring the skills needed to be at the forefront of quantum innovation.
ASU is committed to cultivating talent in the quantum field. Arenz's introductory course is part of a series and one of many programs on campus, including research projects and workshops aimed at developing the next generation of quantum scientists.
Supporting Student Discovery
Most students who take Gennaro De Luca's course start with no quantum experience. He is a lecturer in the School of Computing and Augmented Intelligence, and his course covers everything from the basics of quantum computing to his own research field—quantum generative models. To introduce concepts, he starts with cats.
De Luca guides students through a thought exercise: given only a limited set of cat images, how can you generate entirely new cat images? Essentially, generative models analyze patterns of details (fur, shape, and color) to produce new cat pictures. "In theory, a quantum computer can learn from fewer images than a classical computer," De Luca said.His students use university resources to carry out quantum projects—from educational programs that simplify quantum machine learning to building a Lego robot car entirely controlled by quantum image processing algorithms. One of the tools they use is Nvidia's CUDA-Q software package, which leverages the accelerated processing power of specialized chips (GPUs). CUDA-Q can simulate a quantum environment, and it can run on a laptop or be used for large projects on ASU's Sol supercomputer—one of the most powerful supercomputers in the world, nearly 2,000 times more powerful than a modern laptop. Additionally, CUDA-Q supports access to real quantum computing platforms via the cloud, such as IBM's quantum computers.
Another tool is an accelerator card called Vector Engine, which simulates "a dedicated quantum computing platform for quantum optimization," says Speyer. This tool was recently used by a research team in the Supply Chain Management Department of the W. P. Carey School of Business to solve transportation logistics problems.
Inside a Quantum Computer
In ordinary computers (from phones to supercomputers), all information is stored as bits, each either 0 or 1. Quantum computers use qubits. Qubits can represent not only 0 or 1 but also both states simultaneously—like a coin in midair, which could land heads or tails—a state called superposition. Qubits can also become entangled, meaning they are intrinsically linked in superposition. These properties allow quantum computers to perform vast numbers of calculations simultaneously, with potentially exponential performance improvements.
Super Material Discovery
Discovering new materials usually takes years of trial and error. At ASU's School for Engineering of Matter, Transport and Energy, Associate Professor Houlong Zhuang is using quantum computing to dramatically accelerate this process. In recent years, he has used this emerging technology to develop high-entropy alloys—materials that do not melt or weaken under extreme heat, stress, and radiation, often used in advanced defense systems such as hypersonic vehicles and nuclear-powered submarines. Quantum computing can significantly speed up the design and production of new materials in the lab. "Usually simulations take weeks, but now with a hybrid strategy, it can be done in days," says Zhuang. As quantum computing develops, "ideally, we can shorten days to a day or even hours." Zhuang is also applying these methods to sustainability research, seeking materials that can capture carbon dioxide, store and transport hydrogen, and develop new semiconductors for solar energy conversion.