Modeling of nonlinear and nonstationary stochasticity for atomic ensembles.

This paper addresses the problem of stochastic modeling of atomic ensembles under multi-source noise and makes the model interpretable. First, based on Itô's lemma and Allan variance analysis (ITÔ-AVAR), an approach is proposed to model nonstationary stochastic submodels of atomic ensembles. On this basis, the variance decomposition and nonlinear optimization algorithms are utilized to hybridize modeling atomic ensembles with nonlinear and nonstationary properties. Second, an Itô's lemma dynamic allan variance analysis (ITÔ-DAVAR) approach is developed for online modeling of atomic ensembles. Further, an atomic ensembles sensitivity enhancement scheme based on the proposed approach is given, which effectively promotes the progress of quantum instrument engineering. Finally, the proposed scheme are deployed in the optical pumping magnetometer and spin-exchange relaxation-free comagnetometer, respectively, while experimentally verifying the sensitivity of the spin-exchange relaxation-free comagnetometer reaches 5. 36 × 1 0 − 6 deg s − 1 Hz − 1 / 2 . • An approach is proposed for modeling nonstationary stochastic submodels of atomic ensembles using Itô's lemma and Allan variance analysis. • Combining the variance decomposition and the nonlinear optimization algorithm to hybrid model the atomic ensembles. • A sliding-window technique is employed to realize real-time online modeling of the atomic ensembles, ensuring adaptability and practicality. • An atomic ensembles sensitivity improvement scheme is proposed to promote its engineering progress. • The effectiveness of the proposed approach is verified through numerical simulations and practical experiments. [ABSTRACT FROM AUTHOR]