Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell

Addressing the constraint of magnetic field gradients in the vapor cell on enhancing the sensitivity of atomic magnetometers, this paper proposed a dual-layer heater design based on genetic algorithms, effectively reduced the magnetic field gradients within the vapor cell. The study analyzed the inf...

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Main Authors: Zhicheng Tan, Jing Zhu, Yanyan Liu, Siyang Lu, Lianqing Zhu
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:e-Prime: Advances in Electrical Engineering, Electronics and Energy
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Online Access:http://www.sciencedirect.com/science/article/pii/S2772671124003462
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author Zhicheng Tan
Jing Zhu
Yanyan Liu
Siyang Lu
Lianqing Zhu
author_facet Zhicheng Tan
Jing Zhu
Yanyan Liu
Siyang Lu
Lianqing Zhu
author_sort Zhicheng Tan
collection DOAJ
description Addressing the constraint of magnetic field gradients in the vapor cell on enhancing the sensitivity of atomic magnetometers, this paper proposed a dual-layer heater design based on genetic algorithms, effectively reduced the magnetic field gradients within the vapor cell. The study analyzed the influence of key parameters of the resistive wire, such as wire width, thickness, and spacing, on magnetic noise generation in the three-dimensional model of the heater. The parameter combinations were then optimized synchronously using genetic algorithms to reduce the magnetic field gradient in the vapor cell region and enhance the magnetic noise self-suppression capability of the heater. The simulation results confirmed that the magnetic field strength in most areas remains below 40 pT, and the magnetic field gradient was well-managed. Additionally, further magnetic field experiments demonstrated that the heater's current-generated magnetic field had a strong self-suppression effect on magnetic noise, as evidenced by the index k value of -0.05. This paper provides convincing technical support and experimental evidence for improving the performance of the SERF atomic magnetometer.
format Article
id doaj-art-808bd584472041f898b13da77d1271cf
institution Kabale University
issn 2772-6711
language English
publishDate 2024-12-01
publisher Elsevier
record_format Article
series e-Prime: Advances in Electrical Engineering, Electronics and Energy
spelling doaj-art-808bd584472041f898b13da77d1271cf2024-12-16T05:38:41ZengElseviere-Prime: Advances in Electrical Engineering, Electronics and Energy2772-67112024-12-0110100766Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cellZhicheng Tan0Jing Zhu1Yanyan Liu2Siyang Lu3Lianqing Zhu4Key Laboratory of the Ministry of Education for Optoelectronics Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing, 100192, China; Guangzhou Nansha Intelligent Photonic Sensing Research Institute, Guangzhou, 511462, ChinaKey Laboratory of the Ministry of Education for Optoelectronics Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing, 100192, China; Guangzhou Nansha Intelligent Photonic Sensing Research Institute, Guangzhou, 511462, China; Corresponding author.Key Laboratory of the Ministry of Education for Optoelectronics Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing, 100192, China; Guangzhou Nansha Intelligent Photonic Sensing Research Institute, Guangzhou, 511462, ChinaKey Laboratory of the Ministry of Education for Optoelectronics Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing, 100192, China; Guangzhou Nansha Intelligent Photonic Sensing Research Institute, Guangzhou, 511462, ChinaKey Laboratory of the Ministry of Education for Optoelectronics Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing, 100192, China; Guangzhou Nansha Intelligent Photonic Sensing Research Institute, Guangzhou, 511462, ChinaAddressing the constraint of magnetic field gradients in the vapor cell on enhancing the sensitivity of atomic magnetometers, this paper proposed a dual-layer heater design based on genetic algorithms, effectively reduced the magnetic field gradients within the vapor cell. The study analyzed the influence of key parameters of the resistive wire, such as wire width, thickness, and spacing, on magnetic noise generation in the three-dimensional model of the heater. The parameter combinations were then optimized synchronously using genetic algorithms to reduce the magnetic field gradient in the vapor cell region and enhance the magnetic noise self-suppression capability of the heater. The simulation results confirmed that the magnetic field strength in most areas remains below 40 pT, and the magnetic field gradient was well-managed. Additionally, further magnetic field experiments demonstrated that the heater's current-generated magnetic field had a strong self-suppression effect on magnetic noise, as evidenced by the index k value of -0.05. This paper provides convincing technical support and experimental evidence for improving the performance of the SERF atomic magnetometer.http://www.sciencedirect.com/science/article/pii/S2772671124003462HeaterMagnetic field self-suppressionMagnetic field gradientGenetic algorithm
spellingShingle Zhicheng Tan
Jing Zhu
Yanyan Liu
Siyang Lu
Lianqing Zhu
Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell
e-Prime: Advances in Electrical Engineering, Electronics and Energy
Heater
Magnetic field self-suppression
Magnetic field gradient
Genetic algorithm
title Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell
title_full Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell
title_fullStr Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell
title_full_unstemmed Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell
title_short Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell
title_sort design of dual layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell
topic Heater
Magnetic field self-suppression
Magnetic field gradient
Genetic algorithm
url http://www.sciencedirect.com/science/article/pii/S2772671124003462
work_keys_str_mv AT zhichengtan designofduallayerheaterbasedongeneticalgorithmtooptimizemagneticfieldgradientinvaporcell
AT jingzhu designofduallayerheaterbasedongeneticalgorithmtooptimizemagneticfieldgradientinvaporcell
AT yanyanliu designofduallayerheaterbasedongeneticalgorithmtooptimizemagneticfieldgradientinvaporcell
AT siyanglu designofduallayerheaterbasedongeneticalgorithmtooptimizemagneticfieldgradientinvaporcell
AT lianqingzhu designofduallayerheaterbasedongeneticalgorithmtooptimizemagneticfieldgradientinvaporcell