Modeling of nonlinear and nonstationary stochasticity for atomic ensembles

Bodong Qin; Zhuo Wang; Ruigang Wang; Feng Li; Zehua Liu; Chi Fang

doi:10.1016/j.isatra.2023.09.019

Modeling of nonlinear and nonstationary stochasticity for atomic ensembles

ISA Trans. 2023 Dec:143:557-571. doi: 10.1016/j.isatra.2023.09.019. Epub 2023 Sep 26.

Authors

Bodong Qin¹, Zhuo Wang², Ruigang Wang³, Feng Li⁴, Zehua Liu⁴, Chi Fang⁴

Affiliations

¹ School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Institute of Large-scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, Beijing 100191, China; National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou 310023, China. Electronic address: bodongqin@buaa.edu.cn.
² School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Institute of Large-scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, Beijing 100191, China. Electronic address: zhuowang@buaa.edu.cn.
³ School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China. Electronic address: ruigangwang@buaa.edu.cn.
⁴ School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Institute of Large-scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, Beijing 100191, China; National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou 310023, China.

PMID: 37806820
DOI: 10.1016/j.isatra.2023.09.019

Abstract

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 5.36×10^-6degs^-1Hz^-1/2.

Keywords: Allan variance analysis; Atomic ensembles; Itô’s lemma; Parameter identification; Stochastic system modeling.