Noise Field Research Articles

Effect of proton irradiation on the performance of fluxgate sensors

The fluxgate magnetometers have been used in many space missions due to their stability, low cost, low mass, and good measuring sensitivity and range. Space weather conditions around the Earth and solar system may be dangerous for the sensors of these crucially important devices. Proton irradiation was used to simulate space weather conditions near the Earth’s magnetosphere in Van Allen belts. The effect of proton irradiation on the structural, magnetic, and sensor performance of our fluxgate sensors was studied with irradiation doses up to 60 kRad. Sensor’s materials were prepared using a planar flow casting technique having two different compositions, namely Fe38Co38Mo8CuB15 (Fe38) and Fe42Co42CuB15 (Fe42). Structural investigation of the alloys was performed by X-ray diffraction patterns and SEM micrographs. A magnetic force microscope and vibrating sample magnetometer were used to investigate surface and bulk magnetic properties, respectively. The characterization of the sensors was done by determination of the working field range, transfer function, and noise at 1 Hz. The amorphous structure of the Fe38Co38Mo8CuB15 alloy did not change with irradiation, while some degree of crystallization was depicted in the Fe42Co42CuB15 alloy, probably due to the local heating of the ribbon. The formation of magnetic domains was clearly observed in Fe38Co38Mo8CuB15 alloy in MFM images after the irradiation. On the contrary, it was not observed in Fe42Co42CuB15 alloy due to excessive domain growth. The magnetic parameters, namely coercivity (Hc) and saturation magnetization (Ms) were affected by the proton irradiation in a different way. The former increases with irradiation dose, while the latter first decreases and then rises to its initial value or a little smaller. On the other hand, with increasing doses, for both alloys, the transfer functions of the sensors show a decrease while the noise increases substantially. The noise parameters of the sensors were raised 4–5 times after the maximum irradiation dose; similarly, sensitivities decreased more than 100 times.

Denoising and wavefield separation method for DAS VSP via deep learning

Distributed acoustic sensing (DAS) vertical seismic profiling (VSP) is, a new combined method of borehole seismic exploration, that has the advantages of low cost, high resistance to temperature and pressure, and high sampling rate. However, the collected data generally suffer from high noise, detracting from the potential high-precision imaging benefits and limiting the full application of the technique. The quality of wavefield separation is also crucial to VSP processing. To mitigate the various problems, a regularized residual channel attention network (RRCAN) is proposed for improved denoising and wavefield separation. Based on two prediction tasks, the networks are built (i.e., RRCAN_1 and RRCAN_2) by adding a regularization term to the loss function. To reduce the loss of effective signals during the denoising process, a wavefield separation method that includes secondary effective information extraction is adopted. The final separation results reflect the denoised and removed noise data, a total of 500 geological models are constructed using a random method and RRCAN_1 is trained with synthetic and field noise data. The conventional plane-wave destruction method is improved by using velocity information, and high-precision separation results for upgoing and downgoing waves are obtained for RRCAN_2 training. The test results obtained for the synthetic and field data show that the proposed network effectively suppresses DAS VSP noise while yielding excellent separation results for downgoing and upgoing waves. Therefore, denoising and wavefield separation methods based on RRCAN provide effective high-precision DAS VSP imaging.

Spatiochromatic and temporal natural image statistics modelling: Applications from display analysis to neural networks

Natural image statistics are well known to have a spatial frequency power spectra that has a 1/f^a behavior, with a typically stated as between 2 and 4. This indicates an invariance to scale. Further work has theorized how the visual system is tuned for such statistics in visual cortex (V1) [1]. Color image statistics also show an invariance to scale [2]. The luminance histogram is typically understood to be log normal with respect to luminance, although for HDR images, a subcomponent with skew toward much higher luminances is observed. Color statistics were initially described at the simplest level via the gray world hypothesis [3], but more details are now available, even at the hyperspectral [4]. The a power function for HDR was found to increase from the lower values of 2 to more typical values of 4 and 5 [5]. For temporal statistics, the data tends to be measured primarily for media, with a 1/f^a for scene cut statistics [6], and temporal frequency and temporal frequency for media with a focus on the motion statistics via optical flow [7]. Statistics for purely natural as well as human made environments (e.g., buildings and the resulting perspective geometry) have been studied, each having different orientation statistics [8]. The use of image statistics for standardized assessment of television power consumption was used to replace test targets, which were often detected and used to lower TV power consumption in well known cheating schemes. To prevent this, a short test video that had luminance statistics matching 48 hours of broadcast content was generated and used for TV power testing [9]. The highly adaptative nature of current TVs (power limiting, dual modulation, dynamic response) has motivated researchers to incorporate complex noise fields following natural image statistics into measurement targets [10,11]. One particular natural image statistic-based still image test target (dead leaves) is widely used in camera optics and sensor development. Algorithm development and testing for image and video processing has almost always been ad hoc, with a mixture of geometric test targets and hand selected test images, sometimes aiming to be corner cases, sometimes not. More recently, large data sets of images have been used to train various neural network models for tasks such as super resolution, bit rate compression, and dynamic range mapping. However, images are not ergodic, and possibly not even wide-sense stationary. We propose the use of imagery based on noise following the natural image statistics for spatio-chromatic (and temporal) to compactly probe the wide variety of image possibilities for algorithmic development, in addition to the existing uses for image capture and display analysis. While we don’t suggest replacing actual practical imagery, we believe such noise fields can augment image algorithm analysis. To address the problem of non-ergodicity, we allow the basic power term a in the natural image statistic model to vary over a large range in a video, such that it includes the extremes of white noise and low frequency gradients. We use color image statistic models that include decorrelated colors to generate the RGB video. We will present results for traditional adaptive data compression (with chromatic subsampling), as well as a more contemporary neural network approach (Neural Fields [12]) as applied to upscaling and denoising. We analyze the results both visually and through several recent color image quality models. Field DJ. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A, 1987; 4:2379-2394 C. Parraga, T. Troscianko, and D.J. Tolhurst (2002) spatiochromatic properties of natural images and human vision. Current Biology V 12 R. M. Evans, Method for correcting photographic color prints, US Patent 2,571,697 (1951) A. Chakrabarti and T. Zickler (2011) Statistics of real-world hyperspectral images CVPR R. Dror, A. Willsky, and E. Adelson (2004) statistical characterization of real-world illumination. JOV V4 J. Cutting (2019) Sequences in popular cinema generate inconsistent event segmentation. Attn. Percept. And Psycho. V 81. D. Lee, H. Ko, J. Kim, and A. Bovik (2021) On the space-time statistics of motion pictures. JOSA A V 38 #7 A. Torralba and A. Oliva (2003) Statistics of natural image categories, Network: Computational Neural Systems 14 391-412 International Electrotechnical Commission, IEC 62087:2008(E), “Methods of measurement for the power consumption of audio, video, and related Equipment. Kunkel T, Daly S. 57-1: Spatiotemporal Noise Targets Inspired by Natural Imagery Statistics. SID Symposium Digest of Technical Papers, 2020, 51:842-845. Kunkel, T, Friedrich, F. Utilizing advanced spatio-temporal backgrounds with dynamic test signals for high dynamic range display metrology. J Soc Inf Display. 2022; 30( 5): 423– 432. https://doi.org/10.1002/jsid.1125 Yiheng Xie1, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar1, "Neural Fields in Visual Computing and Beyond", Eurographics / CGF State-of-the-Art Report, 2022.

Assessment of the knowledge level of radiographers and CT technologists regarding computed tomography parameters in Iran

ObjectiveTo evaluate the knowledge of CT technologists and radiographers concerning CT parameters, in order to keep CT users be aware of all CT parameters and their impact on image quality and patient dose while keeping their knowledge up to date. MethodsThis cross-sectional descriptive-analytic study was conducted in Zanjan province, Iran, using a valid and reliable online questionnaire with 53 questions distributed to 153 radiology personnel. Each questionnaire included questions about demographic characteristics and CT parameters, including kVp, mAs, image noise, slice thickness, pitch and automatic tube current modulation (ATCM), and the effects of these parameters on image quality and radiation dose. ResultsA response rate of 61.0% (94/153) was achieved. This study enrolled 30 radiographers and 64 CT technologists. There was no significant difference in the mean scores of the two groups (52.16 ± 9.90 vs. 56.09 ± 12.00, t ​= ​−1.545, P ​= ​0.126). CT personnel had the highest and lowest knowledge scores in image reconstruction (t ​= ​−28.33, P ​= ​0.001) and mAs (t ​= ​4.27, P ​= ​0.590), respectively, whereas radiographers had the highest and lowest knowledge scores in the fields of image noise (t ​= ​9.85, P ​= ​0.015) and kVp (t ​= ​−12.73, P ​= ​0.007), respectively. ConclusionsThe total knowledge scores of CT technologists and radiographers for various scan parameters affecting image quality and dose were insufficient. Thus, it is recommended that regular retraining courses be held to enhance and update technologists’ knowledge.

A case study of the comparison between rubberized and polymer modified asphalt on heavy traffic pavement in wet and freeze environment

Ground tire rubber (GTR) usage in asphalt pavement with the dry process has gained more prominence in recent times. The objective of this work is to investigate the pavement performance of GTR-modified asphalt pavement and polymer-modified asphalt pavement on heavy volume of traffic conditions in Michigan's wet and freeze environment. A suite of laboratory tests was done to evaluate the pavement performance of GTR-modified and polymer-modified asphalt mixtures. To reveal the strain and stress relationship under different frequencies and temperatures, the dynamic modulus test was applied. The Hamburg wheel tracking device (HWTD) was used to assess the high-temperature deformation resistance. The disc-shaped compact tension (DCT) test was used to evaluate the low-temperature cracking characteristics. The characteristics of the asphalt binder were assessed by the dynamic shear rheometer (DSR) for high-temperature properties and the asphalt binder cracking device (ABCD) for low-temperature properties. After the construction, a field noise test was conducted. The experimental results stated that the polymer-modified asphalt mixture and GTR-modified asphalt mixture showed higher dynamic modulus and better ability to prevent cracking than the conventional asphalt mixture at low temperatures, as well as better permanent deformation and stripping resistance than the conventional asphalt mixture. The fracture energy of the GTR-modified hot mix asphalt (HMA) is 13–16 % larger than the polymer-modified HMA. The number of passes to the stripping point of GTR-modified was 510–518 % higher than the conventional HMA. When compared to the field core, the lab-compacted HMA offers superior pavement performance. The extracted asphalt binder test results show the GTR-modified asphalt has better rutting resistance and cracking resistance than polymer-modified asphalt, and the results in the noise test demonstrated that the rubber-modified asphalt pavement mitigated the noise level by 2–3 dB on the road at different vehicle speeds. Moreover, the pavement condition was noticeably enhanced after the reconstruction of the surface course. The total number of passenger tires to be used in this project is about 2270. To summarize, better rutting and cracking properties in asphalt pavement are shown by the project's utilization of rubber technology. And the GTR-modified HMA is comparable to polymer-modified HMA. Therefore, it may be appropriate to utilize rubber technology on high-traffic volume asphalt pavement in Michigan's wet and freeze climate.

常导高速磁浮与高速铁路近场噪声对比与分析

常导高速磁浮与高速铁路近场噪声对比与分析

The stochastic delayed Cucker-Smale system in a harmonic potential field

<p style='text-indent:20px;'>We propose a delayed Cucker-Smale system with multiplicative noise in a harmonic potential field and investigate its emergent dynamics. It exhibits a collective behavior "flocking and concentration" if the corresponding non-delay stochastic system admits the almost surely collective behavior and the delay is sufficiently small. We provide theoretical framework and numerical simulations.</p>

Investigation of the effect of adaptive characteristics on non-cavitating noise for flexible propeller in non-uniform flow via the fluid-structure interaction model

When constructing a low-noise submarine, it is crucial to consider the non-cavitating noise from the propeller. Non-cavitating noise reduction is crucial for submarine stealth and survivability. Recently, several studies have been conducted on the use of flexible propellers as a means of reducing non-cavitating noise. However, there are no studies on the use of flexible propellers with adaptive characteristics to reduce noise in wake fields. Thus, this study investigated the noise reduction effect of adaptive characteristics on non-cavitating noise for the flexible propeller in the wake field. Numerical investigations on the main propeller variables were conducted based on the proposed procedure using fluid-structure interaction and acoustic analysis models. The results were compared with those of rigid propellers to determine the possible reasons for noise reduction. Finally, the acoustic analysis results of the flexible propeller were compared with those of the rigid propeller to reveal the effectiveness of the adaptive characteristics.

Numerical simulation of structure-borne noise in a T-shaped tee considering fluid–structure interaction

In order to research the structure-borne noise characteristics of a T-shaped tee considering fluid–structure interaction (FSI), large eddy simulation and the acoustic finite element method were used to simulate the flow field and structure-borne noise related to T-shaped tees under different inlet and outlet combinations. The results show that the frequency domain sound pressure level (SPL) distribution under various inlet flow velocities is stable, the structure-borne noise of the T-shaped tee is a high-frequency noise, and the SPL curves provide a peak distribution. Meanwhile, the distribution characteristics of the structure-borne noise in the frequency domain follow similar trends under different inlet flow velocities. Additionally, the structure-borne noise does not produce the mechanical resonance of the system. When the inlet velocity increases from 1 to 3 m/s, the total sound pressure level (TSPL) increases from 83.71 to 98.18 dB, a relative increase of 17.3%. In addition, the frequency domain distributions of the SPL under various inlet and outlet combinations are basically similar. The TSPL of four inlet and outlet combinations for the structure-borne noise are III, IV, II, and I in descending order. When the inlet flow velocity is 1, 2, and 3 m/s, in the case of combination I, the TSPL of the structure-borne noise decreases by 6.28, 5.59, and 6.39 dB, in contrast to the case of combination III, respectively. This study provides the guidance for the noise control and structural optimization design of a T-shaped tee considering the FSI.

Numerical Simulation of 3D Flow Field and Flow-Induced Noise Characteristics in a T-Shaped Reducing Tee Junction

The so-called T-shaped reducing tees are typically used to divide, change and control (to a certain extent) the flow direction in pipe networks. In this study, the Ffowcs Williams–Hawkings (FW-H) equation and the Large Eddy Simulation (LES) methods are used to simulate the flow-induced noise related to T-shaped reducing tees under different inlet flow velocities and for different pipe diameter ratios. The results show that the maximum flow velocity, average flow velocity, and vorticity in the branch pipe increase gradually as the related diameter decreases. Strong vorticity and secondary flows are also observed in the branch pipe, and the associated violent pressure fluctuations are found to be the main sources of flow-induced noise. In particular, as the pipe diameter ratio decreases from 1 to 0.45, the Total Sound Pressure Level (TSPL) increases by 6.8, 6.26, and 7.43 dB for values of the inlet flow velocity of 1, 2, and 3 m/s, respectively. The distribution characteristics of the flow-induced noise in the frequency domain follow similar trends for different pipe diameter ratios.

Extended Milstein Approximation to the Stochastic Allen-Cahn Equation with Random Diffusion Coefficient Field and Multiplicative Noise

Extended Milstein Approximation to the Stochastic Allen-Cahn Equation with Random Diffusion Coefficient Field and Multiplicative Noise

Analysis of spin-orbit torque magnetic tunnel junction model without external magnetic field assistance based on antiferromagnetism

The effect of spin-orbit torque (SOT) provides a new method of implementing ultra-low power spintronic devices. The in-plane exchange bias (EB) field in antiferromagnetic material can effectively assist SOT magnetization switching. Meanwhile, the utilization of voltage-controlled magnetic anisotropy (VCMA) can effectively reduce the switching barrier. Taking advantage of the EB and VCMA effect, it is possible to realize SOT magnetic tunnel junctions without external field assistance. In this work, a spin-orbit torque magnetic tunnel junction model composed of antiferromagnetic/ferromagnetism/oxides without external magnetic field is developed by solving the modified Landau-Lifshitz-Gilbert (LLG) modular equation, and its magnetization dynamics is analyzed and studied. The effective fields in the model include the demagnetization field, thermal noise field, perpendicular magnetic anisotropy field with VCMA effect, and exchange bias field. Taking IrMn/CoFeB/MgO material system for example, the factors affecting the precession of magnetization are investigated, such as the effect of the exchange bias field, the VCMA effect and the mechanism of SOT field-like torque. Considering the practical applications, the effect of the deviation of the fabrication process of magnetic tunnel junctions is also analyzed. The simulation results demonstrate that the combined effect of <inline-formula><tex-math id="M5">\begin{document}$ {{\boldsymbol{H}}_{{\text{EB}}}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="19-20230901_M5.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="19-20230901_M5.png"/></alternatives></inline-formula> with VCMA effect can greatly reduce the critical <i>I</i><sub>SOT</sub>, thus assisting and realizing the complete field-free magnetization reversal; the SOT field-like torque plays a dominant role in realizing the magnetization reversal, and by adjusting the ratio of the SOT field-like torque to the damping-like torque, field free switching can be realized in the device at the ps grade ; and the MTJ can realize effective switching when the deviation of oxide thickness <inline-formula><tex-math id="M6">\begin{document}$ {\gamma _{{\text{tf}}}} \leqslant 10{\text{%}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="19-20230901_M6.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="19-20230901_M6.png"/></alternatives></inline-formula> or the deviation of free layer thickness <inline-formula><tex-math id="M7">\begin{document}$ {\gamma _{{\text{tox}}}} \leqslant 13{\text{%}}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="19-20230901_M7.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="19-20230901_M7.png"/></alternatives></inline-formula>. Spin-orbit torque devices based on the antiferromagnetic without external magnetic field will provide highly promising solutions for a new-generation ultra-low power, ultra-high speed, and ultra-high integration devices and circuits.

Precision Magnetic Field Sensing with Dual Multi-Wave Atom Interferometer.

Precision magnetic field measurement is widely used for practical applications, fundamental research, and medical purposes, etc. We propose a novel quantum magnetometer based on atoms' multi-wave (3-wave and 5-wave) Ramsey interference. Our design features high phase sensitivity and can be applied to in situ measurements of the magnetic field inside vacuum chambers. The final state detection is designed to be achieved by Raman's two-photon transition. The analytical solution for applicable interference fringe is presented. Fringe contrast decay due to atom temperature and magnetic field gradient is simulated to estimate reasonable experimental conditions. Sensitivity functions for phase noise and magnetic field noise in a multi-wave system are derived to estimate the noise level required to reach the expected resolution. The validity of the model, dual-channel features on bias estimation, and the quasi-non-destructive detection feature are discussed.

Research on Suppression of Airflow Secondary Noise in a Muffler Based on Large Eddy Simulation

Based on the Large Eddy Simulation (LES), the problem of the performance of a muffler being weakened by the airflow secondary noise in the expansion chamber was analyzed. Based on the different relative positions of the inlet and outlet, a single-chamber muffler is divided into four structures and a numerical simulation model of the flow field is developed. The LES was used to analyze the flow field and secondary noise in the expansion chamber. First, the LES is used to calculate the unsteady flow in the expansion chamber to obtain the turbulent intensity and the pressure pulsation distribution of the flow in the muffler chamber. Subsequently, a simulation model of the acoustic field was built separately to obtain the secondary noise distribution of the flow in the muffler by computing the flow field information. It is shown that the secondary noise properties in the muffler are related to its geometrical configuration. The turbulence intensity of the flow field in the chamber can be reduced by changing the airflow pattern in the chamber, to weaken the intensity of the airflow secondary noise. Finally, a structural modification of the two-chamber muffler was performed based on the findings of the study, and the improved muffler performance was evaluated through numerical simulations and field tests. Experimental results show that the improved muffler has better acoustic properties and increases the noise reduction capacity by about 18 percent. It further confirms that the intensity of secondary noise can be substantially suppressed by changing the internal structure of the muffler, which opens up new ideas for the future design and modification of exhaust mufflers.

Ambient noise autocorrelation scheme for imaging theP-wave reflectivity of the lithosphere

SUMMARYAmbient noise autocorrelations can be used to reconstruct the seismic reflection response of the Earth structure beneath single stations using continuous recordings without the need for either active sources or earthquakes. In the last decade, this technique has emerged as an inexpensive approach with the potential to provide similar information to that from the classical receiver function (RF) analysis. Previous studies have located and mapped discontinuities at different crustal depths with ambient noise autocorrelations by applying different processing techniques. An ambient noise autocorrelation function (ACF) provides the body-wave reflectivity of the local structure, assuming a homogeneous distribution of noise sources. However, an effective method design is required in order to determine a reliable reflection response. Here, we review the theory behind the ambient noise ACF method and design a workflow to obtain the P-wave reflectivity with a special focus on the Moho depth. In particular, we calculate a smooth function to fit and subtract the zero-lag component in the time domain, that is, the large-amplitude signal near 0 lag time in the ACF. The zero-lag component can interfere with the reflection component, so its removal allows us to increase the frequency band to use. We bandpass filter the ACFs between 1 and 6 s. We also derive and apply a phase shift correction in the ACFs due to the integration of a homogeneously distributed noise field dominated by distant sources from deep below, such as teleseismic sources. Both linear and nonlinear, phase-weighted stacks are used. Linear stacking is used to identify the main interfaces since it ensures the linearity of the processing steps; nevertheless, nonlinear, phase-weighted stacking help validate the coherent signals. We test and apply our method to continuous vertical recordings from three stations in Ireland and five stations in different cratons and obtain clear P-wave reflection from the Moho and other crustal and upper-mantle discontinuities in most cases. However, noise coming from local heterogeneities, non-homogeneous distribution of the ambient noise sources or instrumental noise is also expected. Therefore, additional, a priori information is desirable to help identify key phases in single ACFs. We compute synthetic ACFs using P-wave velocity (VP) models from controlled-source profiles in Ireland. The relatively complex ACF traces obtained at the stations in Ireland show a close data-synthetic match for the Moho and mid-crustal discontinuities. The ACF traces from the stations in different cratons are directly compared with receiver functions showing overall agreement and offering complementary information on the origin of the signal.

Moment Evolution Equations and Moment Matching for Stochastic Image EPDiff

Models of stochastic image deformation allow study of time-continuous stochastic effects transforming images by deforming the image domain. Applications include longitudinal medical image analysis with both population trends and random subject-specific variation. Focusing on a stochastic extension of the LDDMM models with evolutions governed by a stochastic EPDiff equation, we use moment approximations of the corresponding Itô diffusion to construct estimators for statistical inference in the full stochastic model. We show that this approach, when efficiently implemented with automatic differentiation tools, can successfully estimate parameters encoding the spatial correlation of the noise fields on the image.

Encoder-Decoder Architecture for 3D Seismic Inversion.

Inverting seismic data to build 3D geological structures is a challenging task due to the overwhelming amount of acquired seismic data, and the very-high computational load due to iterative numerical solutions of the wave equation, as required by industry-standard tools such as Full Waveform Inversion (FWI). For example, in an area with surface dimensions of 4.5 km × 4.5 km, hundreds of seismic shot-gather cubes are required for 3D model reconstruction, leading to Terabytes of recorded data. This paper presents a deep learning solution for the reconstruction of realistic 3D models in the presence of field noise recorded in seismic surveys. We implement and analyze a convolutional encoder-decoder architecture that efficiently processes the entire collection of hundreds of seismic shot-gather cubes. The proposed solution demonstrates that realistic 3D models can be reconstructed with a structural similarity index measure (SSIM) of 0.9143 (out of 1.0) in the presence of field noise at 10 dB signal-to-noise ratio.

Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient-Recalled Echo (qGRE) magnetic resonance imaging metrics associated with human brain neuronal structure and hemodynamic properties.

The purpose of the current study was to introduce a Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) method for reconstructing quantitative maps of biological tissue cellular-specific, R2t*, and hemodynamic-specific, R2', metrics of quantitative gradient-recalled echo (qGRE) MRI. The DANSE method adapts a supervised learning paradigm to train a convolutional neural network for robust estimation of R2t* and R2' maps with significantly reduced sensitivity to noise and the adverse effects of macroscopic (B0 ) magnetic field inhomogeneities directly from the gradient-recalled echo (GRE) magnitude images. The R2t* and R2' maps for training were generated by means of a voxel-by-voxel fitting of a previously developed biophysical quantitative qGRE model accounting for tissue, hemodynamic, and B0 -inhomogeneities contributions to multigradient-echo GRE signal using a nonlinear least squares (NLLS) algorithm. We show that the DANSE model efficiently estimates the aforementioned qGRE maps and preserves all the features of the NLLS approach with significant improvements including noise suppression and computation speed (from many hours to seconds). The noise-suppression feature of DANSE is especially prominent for data with low signal-to-noise ratio (SNR ~ 50-100), where DANSE-generated R2t* and R2' maps had up to three times smaller errors than that of the NLLS method. The DANSE method enables fast reconstruction of qGRE maps with significantly reduced sensitivity to noise and magnetic field inhomogeneities. The DANSE method does not require any information about field inhomogeneities during application. It exploits spatial and gradient echo time-dependent patterns in the GRE data and previously gained knowledge from the biophysical model, thus producing high quality qGRE maps, even in environments with high noise levels. These features along with fast computational speed can lead to broad qGRE clinical and research applications.

Surface roughness noise analysis and comprehensive noise effects on depth-dependent coherence time of NV centers in diamond

Noise is a detrimental issue for nitrogen-vacancy (NV) centers in diamond, causing line broadening and decreasing the coherence time (T2). Following our previous electric and magnetic field noise work, we investigate noise caused by the diamond surface roughness, which is a source for charge density fluctuations and incoherent photon scattering. We find that the varying surface charge density noise source is prevalent throughout the entire NV dynamical decoupling frequency range, while the photon scattering noise is almost negligible. Next, we combine the results from various noise sources to perform comprehensive analyses on T2 and how it varies with NV depth. At a given NV depth of 5 nm below a hydrogen- or fluorine-terminated surface, we find that these magnetic nuclei reduce the NV coherence time the most, followed by the surface electric field noise sources. The photon scattering and bulk magnetic field noise effects on T2 are weak compared to the varying charge density, electric dipole, and surface impurity noise. However, with oxygen surface termination, the surface electric field noise becomes comparable to the surface magnetic field noise. Our calculated values of T2,Hahn (few microseconds to ten microseconds) are in good agreement with the experimental values reported elsewhere. Finally, we calculate an anticipated signal-to-noise ratio (SNR) for NV AC magnetometry of external nuclear spins. In our simplified assessment, where some depth-dependent parameters (e.g. NV conversion efficiency) are held constant, we find that shallower NV layers should yield the best SNR, which is consistent with experimental findings.

Impact of the Surface Irregularities of NiFeMo Compacted Powder Particles on Irreversible Magnetization Processes.

One specific group of materials with excellent application potential are powder-compacted soft magnetic materials. These materials have been intensively studied by materials scientists to improve their magnetic properties. This work describes the influence of mechanical smoothing applied to Ni80Fe15Mo5 (wt.%) alloy particle surfaces before the process of compaction. The soft magnetic properties of compacted powders prepared from smoothed and non-smoothed particles were investigated using the following measurements: coercive field, permeability, excess loss, and Barkhausen noise analysis. We found that compactions prepared with smoothed powder particles exhibit a lower value of coercivity (4.80 A/m), higher initial (10,850) and maximum relative permeability (27,700), and low-frequency core losses (1.54 J/m3) in comparison with compactions prepared with non-smoothed particles.