Quantum technology is all about taking advantage of the powerful, and sometimes inexplicable, quantum properties of particles to enhance the precision, speed and security of applications like sensing, computing and communications.
To do this, researchers need to isolate these particles from interference from the outside world, so they embed them in devices called qubits, or quantum bits. Take, for example, a recent Purdue University advance. Experimental physicists there developed an innovative type of qubit by embedding magnetic carbon particles in ultrathin sheets of a material called hexagonal boron nitride, creating defects. Through an optical technique called nuclear magnetic resonance imaging, the researchers could “see” the nuclear spin state of the individual carbon particles—an important step in reading quantum information. At the atomic level, however, the researchers didn’t know the exact structure of the defects, needed to fully understand, replicate, improve—or even apply—the new design.
Enter theoretical and computational expert [person slug=”yuan-ping”, an associate professor of materials science and engineering at the University of Wisconsin-Madison. Using their pioneering first-principles computational tools for analyzing optically detected magnetic resonances, Ping and graduate students Kejun Li and Shimin Zhang identified the chemical structure of the embedded carbon defects in the thin hexagonal boron nitride sheets.
Importantly, their computational analysis provided critical information the Purdue experimental team needed to move forward. Details about this work appeared in the July 2025 issue of the journal Nature.
“One key problem in quantum research is that experimentalists can produce a signal, but they don’t always know the reason for the signal,” says Ping. “If one wants to reproduce a property, or wants it to be scalable, they have to know what is responsible for the optical signal they are getting from the experiment. It’s our job, as theorists, to tell them what is actually happening.”
The process of creating the new qubit was an achievement in and of itself. The Purdue researchers accelerated carbon-13 gas, then “shot” it at a sheet of hexagonal boron nitride, just a few atoms thick. Upon impact, some of the carbon atoms dislodged boron or nitrogen atoms from the sheet, creating internal defects. After the researchers stimulated the carbon atoms using the nuclear magnetic resonance device, they produced a visual signal they could “read” using a spectroscope, an optical instrument for analyzing light.
It was the first time researchers could use a spectroscope to identify and control the nuclear spin of single atoms.
Making the qubit was a feat. However, the Purdue researchers weren’t able to move the project forward without knowing the exact atomic arrangement of the defects, or the carbon, boron and nitrogen atoms.
That’s where Ping and her students played an invaluable role. Using their first-principles tools for spin and optical properties, they painstakingly simulated the behavior of each possible combination of atoms in the material, using quantum mechanics to build each scenario from the ground up. When they compared their simulations with the experimental spectrographic readings, the UW-Madison researchers found two atomic arrangements that correlated with the experimental results.
In short, they identified the qubit’s atomic structures.
“The identification of qubit’s atomic structure is very critical for the Purdue researchers to move forward with the experiment and reproduce what they have seen,” says Ping. “If they want to use this in an application, they have to deliberately put this arrangement in their sample and use it as the qubit.”
The ability to read the nuclear spin information optically and at room temperature is a first step toward using nuclear spin as a quantum sensing and memory technology. Now, with computational confirmation, the experimental team can continue its work.
The project also validates Ping’s spin and optical property tools for spin qubits, which she says can be applied to all sorts of optical quantum systems. “We just need to know the system you’re working on—whether that’s hexagonal boron nitride or silicon or diamond,” she says. “Our toolset can predict the spectrum of the spin qubit. And our tool is not just one last step. If you tell me what you need, we have a framework that can build a structure and calculate the final spectrum of whatever is needed, calculated from first principles.”
Other UW-Madison authors include Kejun Li and Shimin Zhang. Other authors include Xingyu Gao, Sumukh Vaidya, Zhun Ge, Peng Ju, Kunhong Shen, Yuanbin Jin, Tongcang Li, and Saakshi Dikshit of Purdue University, West Lafayette, Indiana.
The UW-Madison authors acknowledge support by the National Science Foundation under grant no. DMR2143233; the Scientific Data and Computing Center, a component of the Computational Science Initiative, at Brookhaven National Laboratory under contract no. DE-SC0012704; the lux supercomputer at UC Santa Cruz, financed by NSF MRI grant no. AST 1828315; the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy Office of Science User Facility operated under contract no. DE-AC02-05CH11231; the TACC Stampede3 system at the University of Texas at Austin through allocation PHY240212 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services and Support (ACCESS) program, which is supported by US National Science Foundation Grants no. 2138259, no. 2138286, no. 2138307, no. 2137603, and no. 2138296.
Top image caption: Using first-principles theoretical and computational methods, Yuan Ping was able to predict the chemical structure of novel single spin defects that could be used a qubits in quantum sensing. Photo: Joel Hallberg