Quantum unmasking simulations reveal the history of atomic-scale qubits

A recent study uses advanced atomic-level computer simulations to predict the formation process of spin defects useful for quantum technologies.

Researchers at the University of Chicago’s Pritzker School of Molecular Engineering, led by Julia Galli, performed a computational study predicting the conditions needed to create specific spin defects in silicon carbide. These findings are detailed in the published article Communications of natureis a significant step toward establishing spin defect production parameters that hold the potential for advances in quantum technologies.

Quantum Mechanisms and Current Challenges

Disadvantages of electronic rotation semiconductors and insulators are rich platforms for quantum information, sensing, and communication applications. Defects are impurities and/or misplaced atoms in a solid, and the electrons associated with these atomic defects carry a spin. This quantum mechanical property can be used to provide a controllable qubit, the basic operating unit of quantum technology.

However, the synthesis of these spin defects, commonly achieved by experimental implantation and annealing processes, is still not well understood and, importantly, cannot yet be fully optimized. In silicon carbide, an attractive host material for spin qubits due to its industrial availability, different experiments have so far yielded different recommendations and results for creating the desired spin defects.

Computational Travel and Discovery

There has not yet been a clear strategy to shape spin defects to the exact specifications we want, a possibility that will be very beneficial for advancing quantum technologies, says Galli, the Family Professor of Molecular Engineering and Chemistry, who is an expert on the subject. author of a new work. So we embarked on a long computational journey to ask the following question: Can we understand how these defects form by performing full-atom simulations?

Gallis’ team, including Kunzhi Zhang, a postdoctoral researcher in the Gallis group, and François Guigi, a computer science professor at the University of California, Davis, combined multiple computational techniques and algorithms to predict the formation of specific rotational defects in silicon carbide, known as dislocations.

Divacations are created by removing silicon and carbon atom in the solid state of silicon carbide sitting close together. We know from previous experiments that these types of defects are promising platforms for sensing applications, Zhang says.

Quantum sensors can detect magnetic and electric fields and also reveal how complex chemical reactions occur, beyond what is possible with today’s technology. To unlock the possibilities of quantum sensing in the solid state, we first need to be able to create defects of the right spin, or qubits, in the right place, Galli says.

To find a recipe for predicting the formation of a particular spin defect, Galli and his team combined several techniques that helped them observe the motions of atoms and charges as the defect forms as a function of temperature.

Usually, when a spin defect is created, other defects also appear, and these can negatively interfere with the spin defect’s target sensing capabilities, said Gygi, the principal developer of the first-principles molecular dynamics code Qbox used in the teams’ quantum simulations. The ability to fully understand the complex mechanism of defect formation is critical.

Techniques and predictions

The team combined the Qbox code with other advanced sampling techniques developed at the Midwest Integrated Center for Computational Materials (MICCoM), a computational materials science center headquartered at Argonne National Laboratory and funded by the Department of Energy, from which Galli and Giji are seniors. investigators.

Our combined technique and multiple simulations revealed to us the special conditions under which demonic spin defects can form efficiently and controllably in silicon carbide, Galli says. In our calculations, we let the fundamental equations of physics tell us what happens inside the crystal structure when defects form.

Future directions and collaborations

The team expects that experimentalists will be interested in using their computational tools to model a variety of spin defects in silicon carbide and other semiconductors as well, but cautions that generalizing their tool to predict a wider range of defect formation processes and defect masses will require more work. . But the proof-of-principle we’ve provided is important, we’ve shown that we can computationally determine some of the conditions needed to create the desired spin defects, Galli says.

Next, his team will continue to work to expand their computational studies and accelerate their algorithms. They also want to expand their investigation to include a variety of more realistic conditions. Here, the samples were considered only in their bulk form, but there are surfaces, stresses, as well as macroscopic defects in the experimental samples. We would like to include their presence in our future simulations, and in particular understand how surfaces affect the formation of a spin defect, Galli says.

While his teams’ advances are based on computational studies, Galli says all of their predictions are based on years of collaboration with experimenters. Without the ecosystem in which we work, constantly talk and collaborate with experimenters, this would not happen.

Reference. Engineering spin-defect formation from first principles by Kunzhi Zhang, François Guigi, and Julia Galli, 26 September 2023.Communications of nature.
DOI: 10.1038/s41467-023-41632-9

The work is funded by the Department of Energy through the MICoM and Q-NEXT centers.