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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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| 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 |
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