A hybridized MCMC framework performs trans-dimensional model selection and parameter estimation from sparse noisy data, recovering nuclear spin locations and couplings around spin defects with an order of magnitude less data than existing approaches.
Five-second coherence of a single spin with single-shot readout in silicon carbide
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Trans-dimensional Hamiltonian model selection and parameter estimation from sparse, noisy data
A hybridized MCMC framework performs trans-dimensional model selection and parameter estimation from sparse noisy data, recovering nuclear spin locations and couplings around spin defects with an order of magnitude less data than existing approaches.