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A Quasi Absolute Optically Pumped Magnetometer for the Permanent Recording of the Earth's Magnetic Field Vector (OPC)

Authors:

E Pulz ,

Helmholtz-Zentrum Potsdam, Deutsches GeoForschungsZentrum GFZ, D-14473 Potsdam, Telegrafenberg, Germany
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K -H Jäckel,

Helmholtz-Zentrum Potsdam, Deutsches GeoForschungsZentrum GFZ, D-14473 Potsdam, Telegrafenberg, Germany
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O Bronkalla

Helmholtz-Zentrum Potsdam, Deutsches GeoForschungsZentrum GFZ, D-14473 Potsdam, Telegrafenberg, Germany
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Abstract

Despite the advance of technology, the fully automatic recording of absolute magnetic field vector variation at observatories remains an elusive goal. Primary difficulties are the long term stability of sensor orientation and the stable operation of the sensor system. In standard practice, definitive data are produced through the combination of continuous operation of a variometer and the occasional absolute measurements that are used for calibration of the variometer data. A single, automatic instrument that can continuously acquire absolute vector measurements with 1-second resolution is desired. We introduce a device that will fulfil these requirements. Data are acquired using Serson's method: the ambient magnetic field is modulated by superposed fields. This method has been applied, mostly in connection with Proton magnetometers, for many years. In general it requires that the applied fields have a strength on the order of the Earth's magnetic field. But the sampling rate is limited for most xisting systems. In contrast, our system only requires applied fields of about 5000nT, and the switching rate of polarities is 5Hz. This is possible because we use a fast self oscillating Cs-magnetometer. The self oscillating Cs-magnetometer is calibrated by a Cs-He cell during times without additional fields (tandem-magnetometer).
DOI: http://doi.org/10.2481/dsj.IAGA-18
How to Cite: Pulz, E., Jäckel, K.-H. & Bronkalla, O., (2011). A Quasi Absolute Optically Pumped Magnetometer for the Permanent Recording of the Earth's Magnetic Field Vector (OPC). Data Science Journal. 10, pp.IAGA109–IAGA116. DOI: http://doi.org/10.2481/dsj.IAGA-18
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Published on 20 Jul 2011.
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