A spin-mechanical quantum chip for exploring exotic interactions.

How to illuminate dark matter has become the foremost open question in fundamental science nowadays, which is of great significance in understanding the laws of nature. Exploring exotic interactions beyond the standard model is one of the essential approaches to searching for dark matter particles. Although it has been explored in a variety of lab-scale and tabletop-scale setups over the past years, no such interactions have been observed, and improving the sensitivity significantly becomes of paramount importance, but challenging. Here, we formulate the conception of a spin-mechanical quantum chip compatible with scalable on-chip detectors. Utilizing the prototype chip realized by the integration of a mechanical resonator and a diamond with single nitrogen vacancy at the microscale, the constraints of spin-velocity-dependent interactions have been improved by two orders of magnitude, where there is no evidence for new bosons in the force range below 100 nm, i.e., in the rest-mass window of 2-10 electronvolts. Based on the proof-of-principle experiment, this promising chip can be scaled up to meet the requirements of searching for exotic interactions at preeminent sensitivity. Low-cost and high-yield chip-scale setups will accelerate the process of dark matter exploration, providing a path toward on-chip fundamental physics experiments.

High-Verdet Constant and Low-Optical Loss Tb3+ Doped Magnetite Nanoparticles.

Magneto-optical (MO) polymer nanocomposites have emerged as alternatives to conventional MO crystals, particularly in nanophotonics applications, thanks to their better processing flexibility and superior Verdet constants. However, a higher Verdet constant commonly comes with excessive optical loss due to increased absorption and scattering, resulting in a constant or reduced figure-of-merit (FOM) defined as the Verdet constant over optical loss. By doping magnetite (Fe3O4) nanoparticles with Tb3+ ions, we report a new strategy to enhance the Verdet constant without increasing the optical loss. The Fe3O4:Tb3+ nanocomposite is one of a kind that simultaneously achieves a state-of-the-art Verdet constant of 5.6 × 105 °/T·m and a state-of-the-art FOM of 31°/T in the near-infrared region.

Adaptive multipole models of optically pumped magnetometer data.

Multipole expansions have been used extensively in the Magnetoencephalography (MEG) literature for mitigating environmental interference and modelling brain signal. However, their application to Optically Pumped Magnetometer (OPM) data is challenging due to the wide variety of existing OPM sensor and array designs. We therefore explore how such multipole models can be adapted to provide stable models of brain signal and interference across OPM systems. Firstly, we demonstrate how prolate spheroidal (rather than spherical) harmonics can provide a compact representation of brain signal when sampling on the scalp surface with as few as 100 channels. We then introduce a type of orthogonal projection incorporating this basis set. The Adaptive Multipole Models (AMM), which provides robust interference rejection across systems, even in the presence of spatially structured nonlinearity errors (shielding factor is the reciprocal of the maximum fractional nonlinearity error). Furthermore, this projection is always stable, as it is an orthogonal projection, and will only ever decrease the white noise in the data. However, for array designs that are suboptimal for spatially separating brain signal and interference, this method can remove brain signal components. We contrast these properties with the more typically used multipole expansion, Signal Space Separation (SSS), which never reduces brain signal amplitude but is less robust to the effect of sensor nonlinearity errors on interference rejection and can increase noise in the data if the system is sub-optimally designed (as it is an oblique projection). We conclude with an empirical example utilizing AMM to maximize signal to noise ratio (SNR) for the stimulus locked neuronal response to a flickering visual checkerboard in a 128-channel OPM system and demonstrate up to 40 dB software shielding in real data.

Measuring Human Auditory Evoked Fields with a Flexible Multi-Channel OPM-Based MEG System.

BACKGROUND: Magnetoencephalography (MEG) is a non-invasive imaging technique for directly measuring the external magnetic field generated from synchronously activated pyramidal neurons in the brain. The optically pumped magnetometer (OPM) is known for its less expensive, non-cryogenic, movable and user-friendly custom-design provides the potential for a change in functional neuroimaging based on MEG. METHODS: An array of OPMs covering the opposite sides of a subject's head is placed inside a magnetically shielded room (MSR) and responses evoked from the auditory cortices are measured. RESULTS: High signal-to-noise ratio auditory evoked response fields (AEFs) were detected by a wearable OPM-MEG system in a MSR, for which a flexible helmet was specially designed to minimize the sensor-to-head distance, along with a set of bi-planar coils developed for background field and gradient nulling. Neuronal current sources activated in AEF experiments were localized and the auditory cortices showed the highest activities. Performance of the hybrid optically pumped magnetometer-magnetoencephalography/electroencephalography (OPM-MEG/EEG) system was also assessed. CONCLUSIONS: The multi-channel OPM-MEG system performs well in a custom built MSR equipped with bi-planar coils and detects human AEFs with a flexible helmet. Moreover, the similarities and differences of auditory evoked potentials (AEPs) and AEFs are discussed, while the operation of OPM-MEG sensors in conjunction with EEG electrodes provides an encouraging combination for the exploration of hybrid OPM-MEG/EEG systems.

Three-Axis Vector Magnetometer with a Three-Dimensional Flux Concentrator.

This research proposes a magnetic field sensor with spatial orientation ability. Through the assistance of a magnetic flux concentrator, out-of-plane magnetic flux can be concentrated and guided into the planar magnetic cores of a fluxgate sensor. A printed circuit board is used to construct the basic planar structure, on which the proposed three-dimensional magnetic flux concentrator and magnetic cores are assembled. This reduces the alignment error of the coils and improves the reliability of the sensor. Three-axis sensing is achieved by using the second harmonic signals from selected sensing coil pairs. The magnetometer exhibits a linear range to 130 µT. At an excitation frequency of 50 kHz, the measured sensitivities are 257.1, 468.8, and 258.8 V/T for the X-, Y-, and Z-axis sensing modes, respectively. This sensor utilizes only one sensing mechanism for the vector field, making it suitable for IoT applications, especially for assessing mechanical posture or position.

Planar Hall Effect Magnetic Sensors with Extended Field Range.

The magnetic field range in which a magnetic sensor operates is an important consideration for many applications. Elliptical planar Hall effect (EPHE) sensors exhibit outstanding equivalent magnetic noise (EMN) on the order of pT/Hz, which makes them promising for many applications. Unfortunately, the current field range in which EPHE sensors with pT/Hz EMN can operate is sub-mT, which limits their potential use. Here, we fabricate EPHE sensors with an increased field range and measure their EMN. The larger field range is obtained by increasing the uniaxial shape-induced anisotropy parallel to the long axis of the ellipse. We present measurements of EPHE sensors with magnetic anisotropy which ranges between 12 Oe and 120 Oe and show that their EMN at 10 Hz changes from 800 pT/Hz to 56 nT/Hz. Furthermore, we show that the EPHE sensors behave effectively as single magnetic domains with negligible hysteresis. We discuss the potential use of EPHE sensors with extended field range and compare them with sensors that are widely used in such applications.

Superconducting Quantum Magnetometer Based on Flux Focusing Effect for High-Sensitivity Applications.

A superconducting quantum magnetometer for high-sensitivity applications has been developed by exploiting the flux focusing of the superconducting loop. Unlike conventional dc SQUID magnetometers that use a superconducting flux transformer or a multiloop design, in this case, a very simple design has been employed. It consists of a bare dc SQUID with a large washer-shaped superconducting ring in order to guarantee a magnetic field sensitivity BΦ less than one nT/Φ0. The degradation of the characteristics of the device due to an inevitable high value of the inductance parameter ßL was successfully compensated by damping the inductance of the dc SQUID. The size of the magnetometer, coinciding with that of the washer, is 5 × 5 mm2 and the spectral density of the magnetic field noise is 8 fT/√Hz with a low frequency noise knee of two Hz. The excellent performance of this simple magnetometer makes it usable for all high-sensitivity applications including magnetoencephalography.

Structural Design and Parameter Optimization of Magnetic Gradient Tensor Measurement System.

Magnetic anomaly detection (MAD) technology based on the magnetic gradient tensor (MGT) has broad application prospects in fields such as unexploded ordnance detection and mineral exploration. The difference approximation method currently employed in the MGT measurement system introduces measurement errors. Designing reasonable geometric structures and configuring optimal structural parameters can effectively reduce measurement errors. Based on research into differential MGT measurement, this paper proposes three simplified planar MGT measurement structures and provides the differential measurement matrix. The factors that affect the design of the baseline distance of the MGT measurement system are also theoretically analyzed. Then, using the magnetic dipole model, the error analysis of the MGT measurement structures is carried out. The results demonstrate that the planar cross-shaped structure is optimal, with the smallest measurement error, only 3.15 × 10-10 T/m. Furthermore, employing the control variable method, the impact of sensor resolution constraints, noise level, target magnetic moment, and detection distance on the design of the optimal baseline distance of the MGT measurement system is simulated and verified. The results indicate that the smaller the target magnetic moment, the farther the detection distance, the lower the magnetometer resolution, the greater the noise, and the greater the baseline distance required. These conclusions provide reference and guidance for the construction of the MGT measurement system based on triaxial magnetometers.

A Compensation Method for the Geomagnetic Measurement Error of an Underwater Ship-Borne Magnetometer Based on Constrained Total Least Squares.

When magnetic matching aided navigation is applied to an underwater vehicle, the magnetometer must be installed inside the vehicle, considering the navigation safety and concealment of the underwater vehicle. Then, the interference magnetic field will seriously affect the accuracy of geomagnetic field measurement, which directly affects the accuracy of geomagnetic matching aided navigation. Therefore, improving the accuracy of geomagnetic measurements inside the vehicle through error compensation has become one of the most difficult problems that requires an urgent solution in geomagnetic matching aided navigation. In order to solve this problem, this paper establishes the calculation model of the internal magnetic field of the underwater vehicle and the geomagnetic measurement error model of the ship-borne magnetometer. Then, a compensation method for the geomagnetic measurement error of the ship-borne magnetometer, based on the constrained total least square method, is proposed. To verify the effectiveness of the method proposed in this paper, a simulation experiment of geomagnetic measurement and compensation of a ship-borne three-axis magnetometer was constructed. Among them, to be closer to the real situation, a combination of the geomagnetism model, the elliptic shell model and the magnetic dipole model was used to simulate the internal magnetic field of the underwater vehicle. The experimental results indicated that the root mean square error of geomagnetic measurement in an underwater vehicle was less than 5 nT after compensation, and the accuracy of geomagnetic measurement met the requirements of geomagnetic matching aided navigation.

Sensor array design of optically pumped magnetometers for accurately estimating source currents.

An optically pumped magnetometer (OPM) is a new generation of magnetoencephalography (MEG) devices that is small, light, and works at room temperature. Due to these characteristics, OPMs enable flexible and wearable MEG systems. On the other hand, if we have a limited number of OPM sensors, we need to carefully design their sensor arrays depending on our purposes and regions of interests (ROIs). In this study, we propose a method that designs OPM sensor arrays for accurately estimating the cortical currents at the ROIs. Based on the resolution matrix of minimum norm estimate (MNE), our method sequentially determines the position of each sensor to optimize its inverse filter pointing to the ROIs and suppressing the signal leakage from the other areas. We call this method the Sensor array Optimization based on Resolution Matrix (SORM). We conducted simple and realistic simulation tests to evaluate its characteristics and efficacy for real OPM-MEG data. SORM designed the sensor arrays so that their leadfield matrices had high effective ranks as well as high sensitivities to ROIs. Although SORM is based on MNE, the sensor arrays designed by SORM were effective not only when we estimated the cortical currents by MNE but also when we did so by other methods. With real OPM-MEG data we confirmed its validity for real data. These analyses suggest that SORM is especially useful when we want to accurately estimate ROIs' activities with a limited number of OPM sensors, such as brain-machine interfaces and diagnosing brain diseases.

Real-time, model-based magnetic field correction for moving, wearable MEG.

Most neuroimaging techniques require the participant to remain still for reliable recordings to be made. Optically pumped magnetometer (OPM) based magnetoencephalography (OP-MEG) however, is a neuroimaging technique which can be used to measure neural signals during large participant movement (approximately 1 m) within a magnetically shielded room (MSR) (Boto et al., 2018; Seymour et al., 2021). Nevertheless, environmental magnetic fields vary both spatially and temporally and OPMs can only operate within a limited magnetic field range, which constrains participant movement. Here we implement real-time updates to electromagnetic coils mounted on-board of the OPMs, to cancel out the changing background magnetic fields. The coil currents were chosen based on a continually updating harmonic model of the background magnetic field, effectively implementing homogeneous field correction (HFC) in real-time (Tierney et al., 2021). During a stationary, empty room recording, we show an improvement in very low frequency noise of 24 dB. In an auditory paradigm, during participant movement of up to 2 m within a magnetically shielded room, introduction of the real-time correction more than doubled the proportion of trials in which no sensor saturated recorded outside of a 50 cm radius from the optimally-shielded centre of the room. The main advantage of such model-based (rather than direct) feedback is that it could allow one to correct field components along unmeasured OPM axes, potentially mitigating sensor gain and calibration issues (Borna et al., 2022).

Magnetic field sensors using VO2/Fe3O4nanoparticle devices.

We combined the metal-insulator transition (MIT) properties of VO2and the magnetic properties of Fe3O4to realize a magnetometer with very large nonlinearity and switching characteristics. VO2, Fe3O4nanoparticles, and a conductive binder (silver paint) were mixed and drop-casted onto two-terminal gap junction devices. The device's current-voltage characteristics exhibited current-switching behavior related to MIT in VO2which changed with the external magnetic field. The magnetoresistance and magnetostriction in Fe3O4both contributed to the field sensitivity of the sensor. Sensitivities as high as 1 A nT-1(or 50.8 V T-1with a current bias) were observed near the MIT voltage. The resulting minimum detectable signal was 20 pT/SQRT(Hz).

Optimization of Signal Space Separation for Optically Pumped Magnetometer in Magnetoencephalography.

Magnetoencephalography (MEG) is a noninvasive functional neuroimaging modality but highly susceptible to environmental interference. Signal space separation (SSS) is a method for improving the SNR to separate the MEG signals from external interference. The origin and truncation values of SSS significantly affect the SSS performance. The origin value fluctuates with respect to the helmet array, and determining the truncation values using the traversal method is time-consuming; thus, this method is inappropriate for optically pumped magnetometer (OPM) systems with flexible array designs. Herein, an automatic optimization method for the SSS parameters is proposed. Virtual sources are set inside and outside the brain to simulate the signals of interest and interference, respectively, via forward model, with the sensor array as prior information. The objective function is determined as the error between the signals from simulated sources inside the brain and the SSS reconstructed signals; thus, the optimized parameters are solved inversely by minimizing the objective function. To validate the proposed method, a simulation analysis and MEG auditory-evoked experiments were conducted. For an OPM sensor array, this method can precisely determine the optimized origin and truncation values of the SSS simultaneously, and the auditory-evoked component, for example, N100, can be accurately located in the temporal cortex. The proposed optimization procedure outperforms the traditional method with regard to the computation time and accuracy, simplifying the SSS process in signal preprocessing and enhancing the performance of SSS denoising.

Sensitive magnetometry reveals inhomogeneities in charge storage and weak transient internal currents in Li-ion cells.

The ever-increasing demand for high-capacity rechargeable batteries highlights the need for sensitive and accurate diagnostic technology for determining the state of a cell, for identifying and localizing defects, and for sensing capacity loss mechanisms. Here, we leverage atomic magnetometry to map the weak induced magnetic fields around Li-ion battery cells in a magnetically shielded environment. The ability to rapidly measure cells nondestructively allows testing even commercial cells in their actual operating conditions, as a function of state of charge. These measurements provide maps of the magnetic susceptibility of the cell, which follow trends characteristic for the battery materials under study upon discharge. In particular, hot spots of charge storage are identified. In addition, the measurements reveal the capability to measure transient internal current effects, at a level of µA, which are shown to be dependent upon the state of charge. These effects highlight noncontact battery characterization opportunities. The diagnostic power of this technique could be used for the assessment of cells in research, quality control, or during operation, and could help uncover details of charge storage and failure processes in cells.

Improving Reliability of Magnetic Localization Using Input Space Transformation.

Body motion tracking for medical applications has the potential to improve quality of life for people with physical or speech motor disorders. Current solutions available in the market are either inaccurate, not affordable, or are impractical for a medical setting or at home. Magnetic localization can address these issues thanks to its high accuracy, simplicity of use, wearability, and use of inexpensive sensors such as magnetometers. However, sources of unreliability affect magnetometers to such an extent that the localization model trained in a controlled environment might exhibit poor tracking accuracy when deployed to end users. Traditional magnetic calibration methods, such as ellipsoid fit (EF), do not sufficiently attenuate the effect of these sources of unreliability to reach a positional accuracy that is both consistent and satisfactory for our target applications. To improve reliability, we developed a calibration method called post-deployment input space transformation (PDIST) that reduces the distribution shift in the magnetic measurements between model training and deployment. In this paper, we focused on change in magnetization or magnetometer as sources of unreliability. Our results show that PDIST performs better than EF in decreasing positional errors by a factor of ~3 when magnetization is distorted, and up to ~7 when our localization model is tested on a different magnetometer than the one it was trained with. Furthermore, PDIST is shown to perform reliably by providing consistent results across all our data collection that tested various combinations of the sources of unreliability.

Biomagnetism: The First Sixty Years.

Biomagnetism is the measurement of the weak magnetic fields produced by nerves and muscle. The magnetic field of the heart-the magnetocardiogram (MCG)-is the largest biomagnetic signal generated by the body and was the first measured. Magnetic fields have been detected from isolated tissue, such as a peripheral nerve or cardiac muscle, and these studies have provided insights into the fundamental properties of biomagnetism. The magnetic field of the brain-the magnetoencephalogram (MEG)-has generated much interest and has potential clinical applications to epilepsy, migraine, and psychiatric disorders. The biomagnetic inverse problem, calculating the electrical sources inside the brain from magnetic field recordings made outside the head, is difficult, but several techniques have been introduced to solve it. Traditionally, biomagnetic fields are recorded using superconducting quantum interference device (SQUID) magnetometers, but recently, new sensors have been developed that allow magnetic measurements without the cryogenic technology required for SQUIDs.

An Integrated Single-Beam Three-Axis High-Sensitivity Magnetometer.

Three-axis atomic magnetometers have great advantages for interpreting information conveyed by magnetic fields. Here, we demonstrate a compact construction of a three-axis vector atomic magnetometer. The magnetometer is operated with a single laser beam and with a specially designed triangular 87Rb vapor cell (side length is 5 mm). The ability of three-axis measurement is realized by reflecting the light beam in the cell chamber under high pressure, so that the atoms before and after reflection are polarized along two different directions. It achieves a sensitivity of 40 fT/Hz in x-axis, 20 fT/Hz in y-axis, and 30 fT/Hz in z-axis under spin-exchange relaxation-free regime. The crosstalk effect between different axes is proven to be little in this configuration. The sensor configuration here is expected to form further values, especially for vector biomagnetism measurement, clinical diagnosis, and field source reconstruction.

Multi-Parameter Optimization of Rubidium Laser Optically Pumped Magnetometers with Geomagnetic Field Intensity.

Rubidium laser optically pumped magnetometers (OPMs) are widely used magnetic sensors based on the Zeeman effect, laser pumping, and magnetic resonance principles. They measure the magnetic field by measuring the magnetic resonance signal passing through a rubidium atomic gas cell. The quality of the magnetic resonance signal is a necessary condition for a magnetometer to achieve high sensitivity. In this research, to obtain the best magnetic resonance signal of rubidium laser OPMs in the Earth's magnetic field intensity, the experiment system of rubidium laser OPMs is built with a rubidium atomic gas cell as the core component. The linewidth and amplitude ratio (LAR) of magnetic resonance signals is utilized as the optimization objective function. The magnetic resonance signals of the magnetometer experiment system are experimentally measured for different laser frequencies, radio frequency (RF) intensities, laser powers, and atomic gas cell temperatures in a background magnetic field of 50,765 nT. The experimental results indicate that optimizing these parameters can reduce the LAR by one order of magnitude. This shows that the optimal parameter combination can effectively improve the sensitivity of the magnetometer. The sensitivity defined using the noise spectral density measured under optimal experimental parameters is 1.5 pT/Hz1/2@1 Hz. This work will provide key technical support for rubidium laser OPMs' product development.

An Iterative Implementation of the Signal Space Separation Method for Magnetoencephalography Systems with Low Channel Counts.

The signal space separation (SSS) method is routinely employed in the analysis of multichannel magnetic field recordings (such as magnetoencephalography (MEG) data). In the SSS method, signal vectors are posed as a multipole expansion of the magnetic field, allowing contributions from sources internal and external to a sensor array to be separated via computation of the pseudo-inverse of a matrix of the basis vectors. Although powerful, the standard implementation of the SSS method on MEG systems based on optically pumped magnetometers (OPMs) is unstable due to the approximate parity of the required number of dimensions of the SSS basis and the number of channels in the data. Here we exploit the hierarchical nature of the multipole expansion to perform a stable, iterative implementation of the SSS method. We describe the method and investigate its performance via a simulation study on a 192-channel OPM-MEG helmet. We assess performance for different levels of truncation of the SSS basis and a varying number of iterations. Results show that the iterative method provides stable performance, with a clear separation of internal and external sources.

Atomic Magnetometer Achieves Visual Salience Analysis in Drosophila.

An atomic magnetometer (AM) was used to non-invasively detect the tiny magnetic field generated by the brain of a single Drosophila. Combined with a visual stimulus system, the AM was used to study the relationship between visual salience and oscillatory activity of the Drosophila brain by analyzing changes in the magnetic field. Oscillatory activity of Drosophila in the 1-20 Hz frequency band was measured with a sensitivity of 20 fT/Hz. The field in the 20-30 Hz band under periodic light stimulation was used to explore the correlation between short-term memory and visual salience. Our method opens a new path to a more flexible method for the investigation of brain activity in Drosophila and other small insects.