Noise Analysis in Pre-Amplifier Circuits Associated to Highly Sensitive Optically-Pumped Magnetometers for Geomagnetic Applications
Abstract
:Featured Application
Abstract
1. Introduction
2. Principle of Mx Optically Pumped Cesium Magnetometer
3. Noise Analysis and Optimizations of Photoelectric Detection Circuit
3.1. Noise Analysis of Photoelectric Detection Circuit
3.2. Optimized Design of Photoelectric Detection Circuit
4. Experiment and Discussion
4.1. Test of Photoelectric Detection Circuit
4.2. Optimization of RF Power
4.3. Optimization of Incident Light Power
4.4. Optimization of Cell Temperature
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Parameters | Value |
---|---|
Sensitivity (@ λ=894 nm), η | 0.55 A/W |
Terminal capacitance, Ci | 4300 pF |
Shunt resistance, Rs | 10 GΩ |
Dark current, Id | 50 pA |
AD549 | AD822 | AD745 | LT1028 | |
---|---|---|---|---|
equivalent input noise voltage (nV/√Hz) | 35 | 13 | 2.9 | 0.85 |
equivalent input noise current (fA/√Hz) | 0.11 | 0.8 | 6.9 | 1000 |
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Liu, L.; Lu, Y.; Zhuang, X.; Zhang, Q.; Fang, G. Noise Analysis in Pre-Amplifier Circuits Associated to Highly Sensitive Optically-Pumped Magnetometers for Geomagnetic Applications. Appl. Sci. 2020, 10, 7172. https://doi.org/10.3390/app10207172
Liu L, Lu Y, Zhuang X, Zhang Q, Fang G. Noise Analysis in Pre-Amplifier Circuits Associated to Highly Sensitive Optically-Pumped Magnetometers for Geomagnetic Applications. Applied Sciences. 2020; 10(20):7172. https://doi.org/10.3390/app10207172
Chicago/Turabian StyleLiu, Leisong, Yuantian Lu, Xin Zhuang, Qunying Zhang, and Guangyou Fang. 2020. "Noise Analysis in Pre-Amplifier Circuits Associated to Highly Sensitive Optically-Pumped Magnetometers for Geomagnetic Applications" Applied Sciences 10, no. 20: 7172. https://doi.org/10.3390/app10207172
APA StyleLiu, L., Lu, Y., Zhuang, X., Zhang, Q., & Fang, G. (2020). Noise Analysis in Pre-Amplifier Circuits Associated to Highly Sensitive Optically-Pumped Magnetometers for Geomagnetic Applications. Applied Sciences, 10(20), 7172. https://doi.org/10.3390/app10207172