Automatic Characterization of Random Nuclear Spin Baths

Abigail Poteshman, University of Chicago

Photo of Abigail Poteshman

Defects in semiconductors, such as nitrogen-vacancy centers in diamond or divacancies in silicon carbide (SiC), are candidates for qubits in quantum information processing devices due to their long coherence times. To implement a quantum algorithm, these optically controlled defects are initialized, manipulated, and read out via a sequence of laser pulses. All defects exist in materials with random spin baths due to naturally occurring isotopes, which can impact the coherence time of the central defect spin. For example, diamond contains a 1.1% isotopic frequency of carbon 13, and SiC hosts an additional 4.9% isotopic frequency of silicon 29. These nuclear spins interact with the central defect via the hyperfine interaction. If the hyperfine coupling constants are known, these bath spins can be further manipulated via laser pulses to act as local memory units. However, at present there are no methods to automatically and efficiently characterize the local random nuclear spin baths in materials containing defects. Determining the hyperfine coupling constants in random nuclear spin baths directly via experiment takes a significant amount of manual labor and time for a given sample. However, we can efficiently simulate dynamical decoupling experiments for given a bath spin configuration and hyperfine coupling strengths, and hence we can augment data from shorter dynamical decoupling experiments with simulated data. In this poster, we present fast, efficient numerical and data-driven methods to extract hyperfine components from short dynamical decoupling experiments.

Abstract Author(s): Abigail N. Poteshman, Mykyta Onizhuk, Giulia Galli