Image and sample geometry effects in SQUID magnetometers

Zięba, Andrzej

doi:10.1063/1.1144306

Cited by 30 publications

(12 citation statements)

References 72 publications

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“…The sensor response function of an SRM is primarily determined by the geometry of the sensing coils, while “image effects” produced by the superconducting shield (used to maximize the sensitivity and minimize the noise of the SQUID system) may complicate the actual response [e.g., Zięba , ]. Shibuya and Michikawa [] performed theoretical calculations of sensor response for the first generation SRM onboard R/V JOIDES Resolution with superconducting shield, and obtained results comparable to the empirical measurement along z axis [ Oda and Shibuya , ].…”

Section: Response Function Determinationmentioning

confidence: 99%

Deconvolution of continuous paleomagnetic data from pass-through magnetometer: A new algorithm to restore geomagnetic and environmental information based on realistic optimization

Oda

Xuan

2014

Geochem. Geophys. Geosyst.

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The development of pass-through superconducting rock magnetometers (SRM) has greatly promoted collection of paleomagnetic data from continuous long-core samples. The output of passthrough measurement is smoothed and distorted due to convolution of magnetization with the magnetometer sensor response. Although several studies could restore high-resolution paleomagnetic signal through deconvolution of pass-through measurement, difficulties in accurately measuring the magnetometer sensor response have hindered the application of deconvolution. We acquired reliable sensor response of an SRM at the Oregon State University based on repeated measurements of a precisely fabricated magnetic point source. In addition, we present an improved deconvolution algorithm based on Akaike's Bayesian Information Criterion (ABIC) minimization, incorporating new parameters to account for errors in sample measurement position and length. The new algorithm was tested using synthetic data constructed by convolving ''true'' paleomagnetic signal containing an ''excursion'' with the sensor response. Realistic noise was added to the synthetic measurement using Monte Carlo method based on measurement noise distribution acquired from 200 repeated measurements of a u-channel sample. Deconvolution of 1000 synthetic measurements with realistic noise closely resembles the ''true'' magnetization, and successfully restored finescale magnetization variations including the ''excursion.'' Our analyses show that inaccuracy in sample measurement position and length significantly affects deconvolution estimation, and can be resolved using the new deconvolution algorithm. Optimized deconvolution of 20 repeated measurements of a u-channel sample yielded highly consistent deconvolution results and estimates of error in sample measurement position and length, demonstrating the reliability of the new deconvolution algorithm for real pass-through measurements.

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Section: Response Function Determinationmentioning

confidence: 99%

Deconvolution of continuous paleomagnetic data from pass-through magnetometer: A new algorithm to restore geomagnetic and environmental information based on realistic optimization

Oda

Xuan

2014

Geochem. Geophys. Geosyst.

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“…This geometry is intermediate between the “high homogeneity” arrangement (Δ = 40 mm, L ∼ 100 mm) optimized for discrete‐sample measurements and the “high‐resolution” geometry (Δ = 10 mm, L ∼ 40 mm) designed for maximum resolution of downcore variations. Although the coil geometry is accurately known, calculation of the instrument response function from first principles is strongly complicated by “image effects” related to the superconducting shield [ Zięba , 1993; Shibuya and Michikawa , 2000; Parker and Gee , 2002]. Our magnetometer uses pulse‐tube cryocooling rather than a liquid helium reservoir.…”

Section: Response Function Determination and Noise Characterizationmentioning

confidence: 99%

Deconvolution of u channel magnetometer data: Experimental study of accuracy, resolution, and stability of different inversion methods

Jackson

Bowles

Lascu

et al. 2010

Geochem Geophys Geosyst

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[1] We explore the effects of sampling density, signal/noise ratios, and position-dependent measurement errors on deconvolution calculations for u channel magnetometer data, using a combination of experimental and numerical approaches. Experiments involve a synthetic sample set made by setting hydraulic cement in a 30-cm u channel and slicing the hardened material into ∼2-cm lengths, and a natural lake sediment u channel sample. The cement segments can be magnetized and measured individually, and reassembled for continuous u channel measurement and deconvolution; the lake sediment channel was first measured continuously and then sliced into discrete samples for individual measurement. Each continuous data set was deconvolved using the ABIC minimization code of Oda and Shibuya (1996) and two new approaches that we have developed, using singular-value decomposition and regularized least squares. These involve somewhat different methods to stabilize the inverse calculations and different criteria for identifying the optimum solution, but we find in all of our experiments that the three methods converge to essentially identical solutions. Repeat scans in several experiments show that measurement errors are not distributed with position-independent variance; errors in setting/determining the u channel position (standard deviation ∼0.2 mm) translate in regions of strong gradients into measurement uncertainties much larger than those due to instrument noise and drift. When we incorporate these depth-dependent measurement uncertainties into the deconvolution calculations, the resulting models show decreased stability and accuracy compared to inversions assuming depth-independent measurement errors. The cement experiments involved varying directions and uniform intensities downcore, and very good accuracy was obtained using all of the methods when the signal/noise ratio was greater than a few hundred and the sampling interval no larger than half the length scale of magnetization changes. Addition of synthetic noise or reduction of sampling density decreased the resolution and accuracy of all the methods equally. The sediment-core experiment involved uniform (axial) magnetization direction and strongly varying intensities downcore. Intensity variations are well resolved and directions are accurate to within about 5 degrees, with errors attributable to omission and/or inaccurate calibration of cross terms in the instrument response function.

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“…x v , value of À(9.81 6 0.02) Â 10 À6 . The experimental uncertainties of the susceptibility values are dominated by the variation observed in the value of k. The differences in the value for k for water and polyethylene may be attributed to subtle variations of the geometric shape of samples (18)(19)(20), which had cylindrical and rectangular shapes, respectively.…”

Section: Methodsmentioning

confidence: 99%