A modular, extendible and field-tolerant multichannel vector magnetometer based on current sensor SQUIDs
Jan-Hendrik Storm, Dietmar Drung, Martin Burghoff, Rainer, K\"orber

TL;DR
This paper introduces a modular, extendible multichannel SQUID magnetometer system designed for high-precision biomagnetic and spin precession measurements, demonstrating low noise levels and robustness in practical applications like ULF NMR and MEG.
Contribution
The paper presents a novel, field-tolerant multichannel SQUID magnetometer system with modular design, capable of high sensitivity and multi-application use, including biomagnetism and nuclear magnetic resonance.
Findings
Measured noise levels between 0.6 and 1.5 fT/Hz$^{1/2}$ for small magnetometers
Achieved a minimum noise level of 0.54 fT/Hz$^{1/2}$ using software gradiometry
Successfully performed ULF NMR and MEG experiments demonstrating system robustness
Abstract
We present the prototype module of our extendible and robust multichannel SQUID magnetometer system. A multi-module arrangement can be implemented by using up to 7 modules. It is intended for high-precision measurements of biomagnetism and spin precession. Further demanding applications are magnetorelaxometry and ultra-low-field nuclear magnetic resonance (ULF NMR), where pulsed fields of up to 100 mT are typically applied. The system is operated inside the Berlin Magnetically Shielded Room and equipped with 18 magnetometers consisting of niobium (Nb) wire-wound pick-up coils. A total of 16 small pick-up coils with 17.1 mm diameter form a regular grid with individual channels arranged to ensure system sensitivity covers all three orthogonal spatial directions. Two large hexagonal pick-up coils with an equivalent diameter of 74.5 mm sensitive in z-direction surround the grid at two…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
