System Noise Level Research Articles

Optimal demodulation domain for microwave SQUID multiplexers in presence of readout system noise

The Microwave SQUID Multiplexer (μMUX) is the device of choice for the readout of a large number of low-temperature detectors in a wide variety of experiments within the fields of astronomy and particle physics. While it offers large multiplexing factors, the system noise performance is highly dependent on the cold- and warm-readout electronic systems used to read it out, as well as the demodulation domain and parameters chosen. In order to understand the impact of the readout systems in the overall detection system noise performance, first, we extended the available μMUX simulation frameworks, including additive and multiplicative noise sources in the probing tones (i.e., phase and amplitude noise), along with the capability of demodulating the scientific data, either in the resonator’s phase or the scattering amplitude. Then, considering the additive noise as a dominant noise source, the optimum readout parameters to achieve minimum system noise were found for both open-loop and flux-ramp demodulation schemes in the aforementioned domains. Later, we evaluated the system noise sensitivity to multiplicative noise sources under the optimum readout parameters. Finally, as a case study, we evaluated the optimal demodulation domain and the expected system noise level for a typical software-defined radio readout system. This work leads to an improved system performance prediction and noise engineering based on the available readout electronics and the selected demodulation domain.

A Room‐Temperature Operational Alignment Magnetometer Utilizing Free‐Spin Precession

AbstractAn alignment magnetometer based on free‐spin precession (FSP) has been deployed in the geomagnetic range. A linearly polarized probe beam is utilized to create alignment in a buffer‐gas‐free paraffin‐coated natural abundance rubidium vapor cell at room temperature exposed to a pulsed radio frequency field. Furthermore, the utilization of hyperfine‐selective optical repumping employing linearly polarized beams amplifies the proportion of responsive atoms. As a consequence, this leads to a remarkable enhancement in the optical rotation signal. This paper reports measurements with a minor static magnetic field of about 1 inside a four‐layer ‐metal shield, achieving a system noise level of 0.16 ). With a static magnetic field amplitude of 48.5 (in proximity to Earth's magnetic field), the noise level is ).

Quality control in clinical raster-scan optoacoustic mesoscopy

Optoacoustic (photoacoustic) mesoscopy bridges the gap between optoacoustic microscopy and macroscopy and enables high-resolution visualization deeper than optical microscopy. Nevertheless, as images may be affected by motion and noise, it is critical to develop methodologies that offer standardization and quality control to ensure that high-quality datasets are reproducibly obtained from patient scans. Such development is particularly important for ensuring reliability in applying machine learning methods or for reliably measuring disease biomarkers. We propose herein a quality control scheme to assess the quality of data collected. A reference scan of a suture phantom is performed to characterize the system noise level before each raster-scan optoacoustic mesoscopy (RSOM) measurement. Using the recorded RSOM data, we develop a method that estimates the amount of motion in the raw data. These motion metrics are employed to classify the quality of raw data collected and derive a quality assessment index (QASIN) for each raw measurement. Using simulations, we propose a selection criterion of images with sufficient QASIN, leading to the compilation of RSOM datasets with consistent quality. Using 160 RSOM measurements from healthy volunteers, we show that RSOM images that were selected using QASIN were of higher quality and fidelity compared to non-selected images. We discuss how this quality control scheme can enable the standardization of RSOM images for clinical and biomedical applications.

A design of a high‐resolution frequency modulated continuous wave radar for drone detection based on spurious phase noise and discrete clutter reduction

AbstractThe authors deal with the problem of the design and manufacture of a high‐resolution FMCW radar for drone detection and classification. The difficulties of the problem are discrete clutter reduction and spurious phase noise mitigation. The discrete clutter is due to the reflected signals from land vehicles, birds etc., while the spurious phase noise is inherent in the radar signal due to the phase‐locked loop component and leakage between the transmitting and receiving paths. Both spurious phase noise and clutter will increase the system noise level and hence reduce the probability of detection of small targets such as drones and induce false alarms on the radar screen. In order to reduce discrete clutter, the authors propose a method to separate a drone from discrete clutter based on the design of the radar system parameters for a drone and its propeller detection, target's Doppler dispersion and moving characteristics. For spur mitigation, a method that focuses on the design of the isolation coefficient between transmitting and receiving paths to decrease the power of spurs below the minimum power requirement at the input of the analogue‐to‐digital converter is introduced. The results were applied by the authors to the development and manufacture of a radar with the given specifications for drone detection and classification. Different laboratory and field tests show that the spurs are mitigated and the drones are separated from discrete clutter with a range and accuracy better than the one recently published.

Study on Friction Characteristics of ADC12-POM Gear Pair

In a transmission system, the cooperative utilization of metal small gears and plastic large gears not only significantly reduced the system weight and noise levels, but also harmonized strength and longevity between the gears of varying sizes. Nevertheless, the existing research on metal-plastic friction remains insufficient. This study focused on the ADC12-POM gear pair, conducted sliding friction tests between polyoxymethylene (POM) plastic balls of different diameters and ADC12 metal plates using a self-made reciprocating friction and wear testing machine. The friction coefficients between the ADC12-POM sliding pairs were evaluated under different load and velocity conditions, and subsequent nonlinear regression analysis using the IBM SPSS software yielded an initial calculation model for the friction coefficients at the contact surfaces of the ADC12-POM gear pair. By analyzing the Engagement characteristics of gears, we calculated the variations in curvature radius, relative sliding velocity, and load distribution coefficient during the Engagement process. This enabled us to establish a computational model for determining the tooth surface friction coefficient of the ADC12-POM gear pair. Furthermore, we derived the relationship between Engagement efficiency and the friction coefficient and conducted experimental investigations to assess the efficiency of gear Engagement. The deviation between the theoretically calculated Engagement efficiency and the experimental results was approximately 2%, thereby confirming the feasibility of the friction coefficient calculation model.

Comparing Phantom and Animal Metrics Applied in the Determination of Focused Ultrasound Stable and Inertial Cavitation Levels.

The opening of the blood-brain barrier (BBB) to allow therapeutic drug passage can be achieved by inducing microbubble cavitation using focused ultrasound (FUS). This approach can be monitored through analysis of the received signal to distinguish between stable cavitation associated with safe BBB opening and inertial cavitation associated with blood vessel damage. In this study, FUS phantom and animal studies were used to evaluate the experimental conditions that generate several cross-consistent metrics having the potential to be combined for the reliable, automatic control of cavitation levels. Typical metrics for cavitation monitoring involve observing changes in the spectrum generated by applying the discrete Fourier transform (DFT) to the time domain signal detected using a hydrophone during FUS. A confocal hydrophone was used to capture emissions during a 10 ms FUS burst, sampled at 32 ns intervals, to produce 321,500 points and a high-resolution spectrum when transformed. The FUS spectra were analyzed to show the impact that equipment-transients and well-known DFT-related distortions had on the metrics used for cavitation control. A new approach, physical sparsification (PH-SP), was introduced to sharpen FUS spectral peaks and minimize the effect of these distortions. It was demonstrated that the general spectral signal-to-noise ratio (SNR) could be improved by removing the initial noisy phantom hydrophone signal transient. Minor changes in the transient length digitally removed from the sampled values significantly changed the spectral bandwidths of all the harmonically related FUS signals. We evaluated signal processing techniques to minimize the impact these DFT-related distortions on area-under-the-curve (AUC) metric calculations, and we identified the advantages of using PH-SP and proposed new metrics when characterizing FUS spectral properties. The results show many second, third and sub-harmonic metrics provide cross-consistent evidence of changes between stable and inertial cavitation levels. Removing the first harmonic signal component with a hardware low-pass filter allowed the hydrophone gain to be boosted without introducing distortion, leading to an improved analysis of the sub-harmonic signal orders of magnitude smaller in intensity. Metrics that optimized the energy in the real component of the complex-valued PH-SP spectra provided a 32% increase in the sub-harmonic sensitivity compared to standard metrics. A preliminary investigation of existing and proposed metrics showed that system noise could be large enough to mask the transition between stable and inertial cavitation. Strong narrowing of sub-harmonic peak shapes on applying physical sparsification (PH-SP) were seen in both phantom and animal studies. However, validating equivalent trends of the metrics with pressure were limited by the increased system noise level in the animal study combined with the natural variability between subjects studied. The combined use of hardware low-pass filters and physical sparsification to selectively removing distortions in the spectrum allowed the optimization of metrics for cavitation monitoring by improving the sub-harmonic sensitivity.

Data selection method for restoring a tsunami source form

The reconstruction of a tsunami source as a solution to the inverse problem in mathematical physics relies on the use of the truncated singular value decomposition method (a variant of the least squares method) for inverting remote records of the tsunami wave. The proposed method allows one to overcome the inevitable instability of the numerical solution. The result of inversion depends on the choice of the observation system, actual bathymetry and data noise level. Within the developed approach, a methodology for choosing key inversion options and an optimal dataset which provide the best accuracy of a tsunami source recovery is discussed. It is based on analyzing the distribution of the specific energy generated by all spatial modes at the locations of the active sensors. The peculiarity of the algorithm is that the use of the most informative data allows one without re-computation of the direct problem to obtain wave amplitudes at the points of interest (let us call them as “fictitious” stations) where there were no observations, but those that were considered in preliminary calculations. Three real-life events, the Chilean Illapel tsunami on September 16, 2015, the tsunami near the Solomon Islands on February 6, 2013, and the Shikotan tsunami on October 5, 1994, are used as examples of the proposed approach. The results obtained allow one hope for using of this approach in practice.

Improving the measurement range of FFPI strain sensing using second-order control PDH technology.

A novel demodulation method is presented to expand the measurement dynamic range for fiber optic strain sensors using PDH technology. The new control algorithm uses two integrators to form a 2nd order control, and the FFPI strain sensor can have a dynamic range of 20 dB/octave larger than the PID control method when the input signal frequency decreases a magnitude. A strain resolution of 4.7 pɛ Hz-1/2@10Hz, a 118 dB@10Hz dynamic range without consecution, and 158 dB with consecution is obtained. The experiment results show that the new control method can improve the sensing system's dynamic range with the corner frequency unchanged and without the system noise level degradation.

OBD-Data-Assisted Cost-Based Map-Matching Algorithm for Low-Sampled Telematics Data in Urban Environments

A myriad of connected vehicles collects large-scale telematics data throughout cities, enabling data-based infrastructure planning. To truly benefit from this emerging technology, it is important to integrate pervasive telematics data with map data to produce more tractable and readable information for traffic flows and safety. Map-matching algorithms enable the projection of noisy trajectory data onto map data as a means of integrating telematics data. However, map-matching poses challenges due to higher levels of positioning errors and complex road networks. The authors propose a novel map-matching algorithm that can fuse in-vehicle data with trajectory data to improve the efficiency and accuracy of the algorithm. The proposed algorithm combines the probabilistic and weight-based map-matching frameworks. The novelty of the proposed algorithm includes (i) an adaptive segment candidate search mechanism based on in-vehicle speed information, (ii) adaptive matching parameters to reflect the variations in the Global Positioning System (GPS) noise levels, (iii) a novel transition probability that uses in-vehicle speed data, and (iv) a backend data query system for the shortest routes. Map-matching results were validated based on ground-truth data collected using an in-vehicle sensing device developed by the authors, as well as comparing with a commonly-used off-the-shelf map-matching platform. The proposed algorithm is proven to be robust, with an accuracy of 97.45%, particularly where map data are denser and GPS noise is high.

Distributed Acoustic Sensor Using a Double Sagnac Interferometer Based on Wavelength Division Multiplexing

We demonstrated a fiber optic distributed acoustic sensor based on a double Sagnac interferometer, using two wavelengths separated by CWDM modules. A mathematical model of signal formation principle, based on a shift in two signals analysis, was described and substantiated mathematically. The dependence of the sensor sensitivity on a disturbance coordinate and frequency was found and simulated, and helped determine a low sensitivity zone length and provided sensor scheme optimization. A data processing algorithm without filtering, appropriate even in case of a high system noise level, was described. An experimental study of the distributed fiber optic sensor based on a Sagnac interferometer with two wavelengths divided countering loops was carried out. An accuracy of 24 m was achieved for 25.4 km SMF sensing fiber without phase unwrapping.

Research into Changes in the Level of System Noise in High-Performance Clusters

Research into Changes in the Level of System Noise in High-Performance Clusters

Keeping or reversing social norms promote cooperation by enhancing indirect reciprocity

Indirect reciprocity facilitates cooperation in social dilemmas by assessing the behaviors of agents through social norms. In this paper, we introduce two new types of second-order social norms with keeping rule and reversing rule, respectively. Besides, this paper also considers two different reputation scenarios, namely, public and private reputation scenarios. To verify the impact of social norms with keeping or reversing rules on cooperation, we develop an evolutionary theoretical model. Through numerical multi-agent simulations, we find that social norms with keeping or reversing are conducive to cooperation. Specifically, for the low benefit-cost ratio, the keeping rule can encourage cooperation, while for the high benefit-cost ratio, the reversing rule can promote cooperation. In addition, simulation results also suggest that the influences of the two reputation scenarios on the evolution of cooperation are different. The public reputation scenario provides a more favorable environment for cooperation than the private reputation scenario. Moreover, we observe that the increase of system noise level, whether action error or mutation rate, will have negative impacts on the emergence of cooperation.

Effects of bounded noise and time delay on signal transmission in excitable neural networks

The influence of bounded noise and time delay on the sub–threshold signal transmission in FitzHugh–Nagumo neuronal networks is studied in this paper. It is found that the signal transmission performance can be enhanced by moderate noise levels in neuronal systems. There is an optimal cross–correlation time where the noise enhances signal transmission best. Moreover, the positively correlated bounded noise–induced stochastic anti–resonance phenomenon monotonically enhances with the increasing cross–correlated intensity. Interestingly, the stochastic anti–resonance phenomenon disappears when the noise is negatively correlated. With the fine–tuning of the time delay, the resonance peaks occur at each half–integer multiples of the signal period, implying delay–induced multiple stochastic resonances. The sub–harmonic stochastic resonance and stochastic anti–resonance alternatively appear at the appropriate coupling strength. These results may provide a novel perspective on sub–threshold signal transmission in the nervous system.

Operational Requirements Analysis for Electric Vertical Takeoff and Landing Vehicle in the Brazilian Regulatory Framework

Air passenger transport is expected to change, in the next years, the urban air mobility (UAM) environment. New technologies are enabling the introduction of a new concept of aircraft, referred to as electric vertical takeoff and landing vehicle (eVTOL), with vertical take-off and landing capability, distributed electric propulsion system and low noise level compared to helicopters. This article presents an analysis of the Brazilian Civil Aviation Regulations (RBAC) No. 91 and 135, which address the minimum requirements for commercial operations of commuter and on-demand public passenger transport with airplanes with up to 19 seats. The objective of this article is to identify the technical and regulatory barriers to initiating the eVTOL operation in Brazil and to validate the current operational air traffic rules. After the analysis of the operational requirements and the current Air Traffic Management (ATM) infrastructure for helicopter operation, the minimum required and recommended navigation, communication and surveillance equipment are identified, as well as the main operational limitations for the operation of this type of aircraft in transporting passengers. This analysis is just the beginning of a broader study and there are many challenges to support an increased eVTOL operations.

VRF noise: From data sheets to field measurements

In the last 20 years, Variable Refrigerant Flow (VRF) systems have gained prominence in many sectors of U.S. construction. These devices move conditioned refrigerant from outdoor units through pipes to indoor units, serving areas that require heating or cooling. Advantages of a VRF system include eliminating the need to carry conditioned air through long runs of ductwork, allowing more environmental control in each space or zone served, and offering quieter operation levels. Indoor VRF system noise levels provided by manufacturers are often measured in anechoic conditions close to the unit, which is in contrast to the installed conditions in many buildings using VRF systems. We seek to explore the existing literature documenting VRF sound levels, while we compare and contrast these sound levels to field-installed VRF system measurements.

Optimization of the Weak Measurement System by Determining the Optimal Total Phase Difference

In this study, a method to improve the detection accuracy of a “weak measurement” system of optical rotation was proposed by determining the optimal total phase difference of the system. Analysis of the characteristics of weak measurement regime of the system under different total phase differences provided the total phase difference corresponding to the regime with the smallest ratio of system noise level to sensitivity (that is, the highest system resolution). In this regime, an optical rotation resolution of 5.522 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> ° was obtained, which is nearly an order of magnitude higher than the original system.

New, improved analysis of correlation ECE data to accurately determine turbulent electron temperature spectra and magnitudes (invited).

Turbulent electron temperature fluctuation measurement using a correlation electron cyclotron emission (CECE) radiometer has become an important diagnostic for studying energy transport in fusion plasmas, and its use is widespread in tokamaks (DIII-D, ASDEX Upgrade, Alcator C-Mod, Tore Supra, EAST, TCV, HL-2A, etc.). The CECE diagnostic typically performs correlation analysis between two closely spaced (within the turbulent correlation length) ECE channels that are dominated by uncorrelated thermal noise emission. This allows electron temperature fluctuations embedded in the thermal noise to be revealed and fluctuation level and spectra determined. We have demonstrated a new, improved CECE coherency-based analysis for calculating the temperature fluctuation frequency spectrum and level, which has been verified both numerically through the simulation of synthetic ECE radiometer data and through analysis of experimental data from the CECE system on DIII-D. The new formulation places coherency-based analysis on a firm foundational footing and corrects some currently published methodologies. This new method accurately accounts for bias error in the coherence function and correctly calculates noise levels for a fixed data record length. It provides excellent accuracy in determining temperature fluctuation level (e.g., <10% error) even for a small realization number in the ensemble average. The method also has a smaller uncertainty (i.e., error bar) in the power spectrum when compared to the more standard cross-power method when evaluated at low coherency. Direct calculation of system noise level using correlation between randomized intermediate frequency signals is recommended.

Light extinction spectroscopy applied to polystyrene colloids: Sensitivity to complex refractive index uncertainties and to noise

The measurement of particle size distribution (PSD) in colloids and nanofluids presents many challenges, especially when it requires to be conducted in-situ and real-time. Our work aims to assess the capabilities of Light Extinction Spectroscopy (LES) technique to determine concentration and volumetric PSD (vPSD) of colloids and nanofluids. Numerical simulations are performed to verify robustness of LES data inversion algorithm and to identify the most relevant uncertainty sources. Experiments are carried out on well-dispersed water based colloids containing Polystyrene particles with median diameters at 120 nm and 300 nm. LES results are compared with supplier’s data, 3D-DLS measurements, and SEM images. Via sensitivity analyses, LES sensitivity to particle complex refractive index spectrum and to system noise level are examined. To improve accuracy, we limit LES data inversion at shorter wavelengths where high SNR is acquired. The noise is experimentally characterized and embedded into numerical simulations to better mimic the real conditions. We show that while noise level affects mostly vPSDs’ peak height, small inaccuracies in complex refractive index spectrum deteriorate the stability of the inversion, especially for smaller vPSDs. To overcome the latter, we carry out a preliminary in-situ calibration on particle complex refractive index spectrum. Accordingly, results are substantially improved with maximal discrepancies smaller than 3% for median and volume mean diameters, and lower than 13% for number concentrations. Besides, the retrieval of bi-modal distribution is promising. In conclusion, our methodology can be considered as a guideline to evaluate the applicability and accuracy of the LES technique in colloids.

Solving optimization problems with Rydberg analog quantum computers: Realistic requirements for quantum advantage using noisy simulation and classical benchmarks

Platforms of Rydberg atoms have been proposed as promising candidates to solve some combinatorial optimization problems. Here, we compute quantitative requirements on the system sizes and noise levels that these platforms must fulfill to reach quantum advantage in approximately solving the Unit-Disk Maximum Independent Set problem. Using noisy simulations of Rydberg platforms of up to 26 atoms interacting through realistic van der Waals interactions, we compute the average approximation ratio that can be attained with a simple quantum annealing-based heuristic within a fixed temporal computational budget. Based on estimates of the correlation lengths measured in the engineered quantum state, we extrapolate the results to large atom numbers and compare them to a simple classical approximation heuristic. We find that approximation ratios of at least $\approx 0.84$ are within reach for near-future noise levels. Not taking into account further classical and quantum algorithmic improvements, we estimate that quantum advantage could be reached by attaining a number of controlled atoms of $\sim8,000$ for a time budget of 2 seconds, and $\sim 1,000-1,200$ for a time budget of 0.2 seconds, provided the coherence levels of the system can be improved by a factor 10 while maintaining a constant repetition rate.

PolSAR additive noise estimation based on shadow regions

ABSTRACT Additive noise results from the thermal noise of the radar receiver or antenna, and often has an adverse effect on the subsequent applications. To weaken the influence of additive noise, it is crucial to know the actual additive noise level. However, the system noise level is not always provided in some single- or full-polarimetric synthetic aperture radar (PolSAR) products. As one of the typical low backscattering objects (LBOs) in PolSAR images, shadow occurs as soon as the depression angle of the synthetic aperture radar (SAR) system reaches a more value than the slope away from the radar illumination, and thus provides a feasible way to measure additive noise. This paper proposes a framework to automatically extract shadow regions by a trained model using the bag of words (BoW) model with data from different scenes. The additive noise can then be estimated across a large area based on the extracted shadow. The experiments based on single- and full-polarimetric Radarsat-2 data suggest that the shadow-based framework is an effective way to estimate additive noise.