{"ID":2863546,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.24683","arxiv_id":"2509.24683","title":"Impedance Modeling of Magnetometers: A Path Toward Low-Noise Readout Circuits","abstract":"Optimizing sensor readout schemes and integrated circuit designs for both open-loop and closed-loop implementations requires precise modeling and simulation strategies. This study introduces a novel two-port impedance model to estimate the behavior of a converse Magnetoelectric (cME) sensor. This model provides a possible framework for calculating transfer functions and simulating magnetometer behavior in both continuous- and discrete-time simulation environments, and it is also possibly transferable to other magnetometer types. Common S-parameters were measured experimentally using an impedance analyzer and converted to Z-parameters to create a transfer function for system-level simulations. The model was validated through an analysis of output-related noise using MATLAB and LTSpice simulations to optimize the noise of the analog circuit parts of the system. The simulation results were compared with experimental measurements using a Zurich Instruments lock-in amplifier and the custom-designed low-noise printed circuit board (PCB) under model considerations. The proposed methodology derives noise considerations and the transfer function of a magnetometer. These are essential for readout schemes for mixed-signal circuit design. This allows low-noise electronics to be designed and extended to other sensor interface electronics, broadening their applicability in high-performance magnetic sensing.","short_abstract":"Optimizing sensor readout schemes and integrated circuit designs for both open-loop and closed-loop implementations requires precise modeling and simulation strategies. This study introduces a novel two-port impedance model to estimate the behavior of a converse Magnetoelectric (cME) sensor. This model provides a possi...","url_abs":"https://arxiv.org/abs/2509.24683","url_pdf":"https://arxiv.org/pdf/2509.24683v1","authors":"[\"Johan Arbustini\",\"Eric Elzenheimer\",\"Elizaveta Spetzler\",\"Pablo Mendoza\",\"Daniel Fernández\",\"Jordi Madrenas\",\"Jeffrey McCord\",\"Michael Höft\",\"Robert Rieger\",\"Andreas Bahr\"]","published":"2025-09-29T12:20:52Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}