New method predicts spin dynamics of materials

Researchers at UC Santa Cruz have developed a theoretical foundation and new computational tools for predicting a material’s spin dynamics, a key property for building solid-state quantum computing platforms and other applications of spintronics.

Spin can be used as the basis for qubits and single-photon emitters in applications of quantum information science, including quantum computation, communication, and sensing.

Lifetime of the spin states, known as the spin relaxation and decoherence time, are the key property for quantum computing which needs materials with long spin relaxation times.

The researchers established methods for determining spin dynamics from first principles, meaning that no empirical parameters from experimental measurements are needed to do the calculations. They also showed that their approach is generalizable to different types of materials with vastly different crystal symmetries and electronic structures.

For example, they predicted accurately the spin relaxation time of centrosymmetric materials such as silicon, ferromagnetic iron, and graphene, as well as non-centrosymmetric materials such as molybdenum disulfide and gallium nitride, highlighting the predictive power of their method for a broad range of quantum materials.

By enabling the rational design of materials, instead of searching blindly and testing a wide range of materials experimentally, these new methods could enable rapid advances in the field of quantum information technologies. (Phys.org)

The paper has been published in Nature Communications.

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