Noise Reduction Factor Research Articles

Photon number distribution of squeezed light from a silicon nitride microresonator measured without photon number resolving detectors

The measurement of the photon number distribution (PND) allows one to extract metrics of non-classicality of fundamental and technological relevance, but in principle it requires the use of detectors with photon number resolving (PNR) capabilities. In this work we reconstruct the PND of two-mode pulsed squeezed light generated from a silicon nitride microresonator using threshold detectors and variable optical attenuations. The PNDs are characterized up to ∼1.2 photons per pulse, through which we extracted an on-chip squeezing level of 6.2(2) dB and a noise reduction factor of −3.8(2) dB. The PNDs are successfully reconstructed up to a Hilbert space dimension of 6 × 6. The analysis performed on the photon number basis allows us to characterize the influence of a spurious thermal background field that spoils the photon number correlations. We evaluate the impact of self- and cross-phase modulation on the generation efficiency in case of a pulsed pump, and validate the results through numerical simulations of the master equation of the system.

Oxidative Stress Assessment of Noise Exposure in the Workers Using Hearing Protection in a Pressing Industry.

Exposure to noise by generation of free radicals causes oxidative stress in body. The aim of this study was the evaluation of oxidative stress in workers who have used hearing protection devices during working time. Pressing workers (n=24) of a home appliance industry were studied using hearing protection devices to reduce noise exposure. Twenty two office staff (without exposure to noise) were considered as a control group. Two groups were matched for age, work experience and smoking. Exposure to noise was measured by dosimeter method at workstations. By obtaining 3 ml blood sample, Malondialdehyde levels, Thiol groups and total antioxidant capacity were evaluated in all subjects. Exposure to sound pressure level in pressing workers by considering the noise reduction factor of the earplug was observed in 77.65 dB with minimum 75.1 dB and Maximum 81.22 dB. Plasma thiol groups (0.076 (0.041-0.119) vs (0.110 (0.076-0.197), mmol/l P =0.0001) and total antioxidant capacity (361.33± 54.65 vs 414.14± 96.82, µmol/ml P = 0.026) in pressing workers significantly decreased than control group. Pearson correlation showed significant results between exposure to noise and oxidative stress parameters. Exposure to noise wave cause oxidative stress in different site of body. Oxidative stress is an intermediate way for different disease due to noise exposure. Reducing of noise exposure by earplug in pressing workers is not efficient protection for oxidative stress generation. Therefore, hearing protection devices are not a barrier to the harmful effects of noise in occupational exposure.

Evaluation of Different Filtering Methods Devoted to Magnetometer Data Denoising

In this article, we describe a performance comparison conducted between several digital filters intended to mitigate the intrinsic noise observed in magnetometers. The considered filters were used to smooth the control signals derived from the magnetometers, which were present in an autonomous forestry machine. Three moving average FIR filters, based on rectangular Bartlett and Hanning windows, and an exponential moving average IIR filter were selected and analyzed. The trade-off between the noise reduction factor and the latency of the proposed filters was also investigated, taking into account the crucial importance of latency on real-time applications and control algorithms. Thus, a maximum latency value was used in the filter design procedure instead of the usual filter order. The experimental results and simulations show that the linear decay moving average (LDMA) and the raised cosine moving average (RCMA) filters outperformed the simple moving average (SMA) and the exponential moving average (EMA) in terms of noise reduction, for a fixed latency value, allowing a more accurate heading angle calculation and position control mechanism for autonomous and unmanned ground vehicles (UGVs).

Thermal and superthermal noise signals as resources for underwater quantum communication

Quantum technologies have opened new perspectives for enhancing communication speed and security, particularly in challenging underwater environments, where conventional protocols rely on acoustic wave propagation. In this study, we introduce an innovative communication protocol built upon the utilization of mesoscopic twin-beam (TWB) states, entangled in the number of photons, and photon-number-resolving detectors. Our approach involves transmitting information by mixing the part of TWB that propagates through water with two signals having identical mean values but different statistical distributions. Specifically, we explore the advantages and limitations associated with employing pseudothermal states and two distinct types of superthermal states in our communication protocol. Through both theoretical analysis and experimental investigation, we assess the feasibility of accurately discriminating which state has been superimposed onto the TWB by evaluating the noise reduction factor. Our findings demonstrate promising outcomes, suggesting the practical implementation of this protocol in real-world underwater communication scenarios.

Adaptive IMM-UKF for Airborne Tracking

In this paper, we propose a nonlinear tracking solution for maneuvering aerial targets based on an adaptive interacting multiple model (IMM) framework and unscented Kalman filters (UKFs), termed as AIMM-UKF. The purpose is to obtain more accurate estimates, better consistency of the tracker, and more robust prediction during sensor outages. The AIMM-UKF framework provides quick switching between two UKFs by adapting the transition probabilities between modes based on a distance function. Two modes are implemented: a uniform motion model and a maneuvering model. The experimental validation is performed with Monte Carlo simulations of three scenarios with ACAS Xa tracking logic as a benchmark, which is the next generation of airborne collision avoidance systems. The two algorithms are compared using hypothesis testing of the root mean square errors. In addition, we determine the normalized estimation error squared (NEES), a new proposed noise reduction factor to compare the estimation errors against the measurement errors, and an estimated maximum error of the tracker during sensor dropouts. The experimental results illustrate the superior performance of the proposed solution with respect to the tracking accuracy, consistency, and expected maximum error.

A CO2 and H2O Gas Analyzer with Reduced Error due to Platform Motion

Abstract One long-standing technical problem affecting the accuracy of eddy correlation air–sea CO2 flux estimates has been motion contamination of the CO2 mixing-ratio measurement. This sensor-related problem is well known but its source remains unresolved. This report details an attempt to identify and reduce motion-induced error and to improve the infrared gas analyzer (IRGA) design. The key finding is that a large fraction of the motion sensitivity is associated with the detection approach common to most closed- and open-path IRGA employed today for CO2 and H2O measurements. A new prototype sensor was developed to both investigate and remedy the issue. Results in laboratory and deep-water tank tests show marked improvement. The prototype shows a factor of 4–10 reduction in CO2 error under typical at-sea buoy pitch and roll tilts in comparison with an off-the-shelf IRGA system. A similar noise reduction factor of 2–8 is observed in water vapor measurements. The range of platform tilt motion testing also helps to document motion-induced error characteristics of standard analyzers. Study implications are discussed including findings relevant to past field measurements and the promise for improved future flux measurements using similarly modified IRGA on moving ocean observing and aircraft platforms.

A Feasibility Study on Deep Learning Reconstruction to Improve Image Quality With PROPELLER Acquisition in the Setting of T2-Weighted Gynecologic Pelvic Magnetic Resonance Imaging.

Evaluate deep learning (DL) to improve the image quality of the PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction technique) for 3 T magnetic resonance imaging of the female pelvis. Three radiologists prospectively and independently compared non-DL and DL PROPELLER sequences from 20 patients with a history of gynecologic malignancy. Sequences with different noise reduction factors (DL 25%, DL 50%, and DL 75%) were blindly reviewed and scored based on artifacts, noise, relative sharpness, and overall image quality. The generalized estimating equation method was used to assess the effect of methods on the Likert scales. Quantitatively, the contrast-to-noise ratio and signal-to-noise ratio (SNR) of the iliac muscle were calculated, and pairwise comparisons were performed based on a linear mixed model. P values were adjusted using the Dunnett method. Interobserver agreement was assessed using the κ statistic. P value was considered statistically significant at less than 0.05. Qualitatively, DL 50 and DL 75 were ranked as the best sequences in 86% of cases. Images generated by the DL method were significantly better than non-DL images (P < 0.0001). Iliacus muscle SNR on DL 50 and DL 75 was significantly better than non-DL images (P < 0.0001). There was no difference in contrast-to-noise ratio between the DL and non-DL techniques in the iliac muscle. There was a high percent agreement (97.1%) in terms of DL sequences' superior image quality (97.1%) and sharpness (100%) relative to non-DL images. The utilization of DL reconstruction improves the image quality of PROPELLER sequences with improved SNR quantitatively.

Technology and Tool Development for BACPAC: Qualitative and Quantitative Analysis of Accelerated Lumbar Spine MRI with Deep-Learning Based Image Reconstruction at 3T.

To evaluate whether combining fast acquisitions with deep-learning reconstruction can provide diagnostically useful images and quantitative assessment comparable to standard-of-care acquisitions for lumbar spine magnetic resonance imaging (MRI). Eighteen patients were imaged with both standard protocol and fast protocol using reduced signal averages, each protocol including sagittal fat-suppressed T2-weighted, sagittal T1-weighted, and axial T2-weighted 2D fast spin-echo sequences. Fast-acquisition data was additionally reconstructed using vendor-supplied deep-learning reconstruction with three different noise reduction factors. For qualitative analysis, standard images as well as fast images with and without deep-learning reconstruction were graded by three radiologists on five different categories. For quantitative analysis, convolutional neural networks were applied to sagittal T1-weighted images to segment intervertebral discs and vertebral bodies, and disc heights and vertebral body volumes were derived. Based on noninferiority testing on qualitative scores, fast images without deep-learning reconstruction were inferior to standard images for most categories. However, deep-learning reconstruction improved the average scores, and noninferiority was observed over 24 out of 45 comparisons (all with sagittal T2-weighted images while 4/5 comparisons with sagittal T1-weighted and axial T2-weighted images). Interobserver variability increased with 50 and 75% noise reduction factors. Deep-learning reconstructed fast images with 50% and 75% noise reduction factors had comparable disc heights and vertebral body volumes to standard images (r2≥ 0.86 for disc heights and r2≥ 0.98 for vertebral body volumes). This study demonstrated that deep-learning-reconstructed fast-acquisition images have the potential to provide noninferior image quality and comparable quantitative assessment to standard clinical images.

Mesoscopic States of Light for the Detection of Weakly Absorbing Objects

Over the past twenty years, different imaging techniques have been proposed and implemented in order to reconstruct the images of different kinds of objects, including faint ones. In this work, we exploit the mesoscopic intensity domain to prove that the determination of the transmittance efficiency of an object can be obtained by considering the calculation of the noise reduction factor in the case of a multi-mode pseudothermal state divided at a balanced beam splitter and detected by photon-number-resolving detectors. The good quality of the experimental results suggests that this strategy can be extended to the determination of a matrix of different transmittance values by means of arrays of photon-number-resolving detectors.

Deep learning-based imaging reconstruction for MRI after neoadjuvant chemoradiotherapy for rectal cancer: effects on image quality and assessment of treatment response.

To investigate the effects of deep learning-based imaging reconstruction (DLR) on the image quality of MRI of rectal cancer after chemoradiotherapy (CRT), and its accuracy in diagnosing pathological complete responses (pCR). We included 39 patients (men: women, 21:18; mean age ± standard deviation, 59.1 ± 9.7years) with mid-to-lower rectal cancer who underwent a long-course of CRT and high-resolution rectal MRIs between January 2020 and April 2021. Axial T2WI was reconstructed using the conventional method (MRIconv) and DLR with two different noise reduction factors (MRIDLR30 and MRIDLR50). The signal-to-noise ratio (SNR) of the tumor was measured. Two experienced radiologists independently made a blind assessment of the complete response on MRI. The sensitivity and specificity for pCR were analyzed using a multivariable logistic regression analysis with generalized estimating equations. Thirty-four patients did not have a pCR whereas five (12.8%) had pCR. Compared with the SNR of MRIconv (mean ± SD, 7.94 ± 1.92), MRIDLR30 and MRIDLR50 showed higher SNR (9.44 ± 2.31 and 11.83 ± 3.07, respectively) (p < 0.001). Compared to MRIconv, MRIDLR30 and MRIDLR50 showed significantly higher specificity values (p < 0.036) while the sensitivity values were not significantly different (p > 0.301). The sensitivity and specificity for pCR were 48.9% and 80.8% for MRIconv; 48.9% and 88.2% for MRIDLR30; and 38.8% and 86.7% for MRIDLR50, respectively. DLR produced MR images with higher resolution and SNR. The specificity of MRI for identification of pCR was significantly higher with DLR than with conventional MRI.

Novel scheme for secure data transmission based on mesoscopic twin beams and photon-number-resolving detectors

Quantum resources can improve the quality and security of data transmission. A novel communication protocol based on the use of mesoscopic twin-beam (TWB) states of light is proposed and discussed. The message sent by Alice to Bob is encoded in binary single-mode thermal states having two possible mean values, both smaller than the mean value of the TWB. Such thermal states are alternately superimposed to the portion of TWB sent to Bob. We demonstrate that in the presence of an eavesdropping attack that intercepts and substitutes part of the signal with a thermal noise, Bob can still successfully decrypt the message by evaluating the noise reduction factor for detected photons. The protocol opens new perspectives in the exploitation of quantum states of light for applications to Quantum Communication.

Measurement of the Quantum Efficiency of Analog Detectors in the Parametric Down-Conversion Field

Approaches to the standard-free calibration of the quantum efficiency of a wide class of analog detectors based on the measurement of statistical characteristics of fields generated by parametric down-conversion are analyzed. General expressions are obtained for the noise reduction factor of the difference photocurrent and for the covariance of photocurrents in the signal and idler channels that take into account the possibility of strong fluctuations in the amplitudes of single-photon response functions of the detectors used. It is shown that the measurement of the noise reduction factor of the difference photocurrent using detectors that cannot operate in the photon counting mode is on its own insufficient to directly characterize the level of two-mode squeezing in the down-conversion field and to determine the quantum efficiency of photosensitive elements without additional calibration procedures. A method to determine the quantum efficiency of such detectors based on measuring the dependence of the normalized covariance of photocurrents on the parametric gain is proposed.

Slow light frequency reference cavities—proof of concept for reducing the frequency sensitivity due to length fluctuations

Length changes due to thermo-mechanical noise originating from, for example, Brownian motion are a key limiting factor of present day state-of-the-art laser frequency stabilization using Fabry–Pérot cavities. We present a laser-frequency stabilization concept using an optical cavity with a strong slow-light effect to reduce the impact of cavity length changes on the frequency stability. The resulting noise-reduction factor is proportional to the ratio between the light phase and group velocities in the highly dispersive cavity spacer. We experimentally demonstrate a proof-of-principle implementation of this laser-frequency stabilization technique using a rare-earth doped crystalline cavity spacer in conjunction with semi-permanent spectral tailoring to achieve precise control of the dispersive properties of the cavity. Compared to the same setup in the absence of the slow-light effect a reduction in frequency sensitivity of four orders of magnitude was achieved.

Extending quantum probabilistic error cancellation by noise scaling

We propose a general framework for quantum error mitigation that combines and generalizes two techniques: probabilistic error cancellation (PEC) and zero-noise extrapolation (ZNE). Similar to PEC, the proposed method represents ideal operations as linear combinations of noisy operations that are implementable on hardware. However, instead of assuming a fixed level of hardware noise, we extend the set of implementable operations by noise scaling. By construction, this method encompasses both PEC and ZNE as particular cases and allows us to investigate a larger set of hybrid techniques. For example, gate extrapolation can be used to implement PEC without requiring knowledge of the device's noise model, e.g., avoiding gate-set tomography. Alternatively, probabilistic error reduction can be used to estimate expectation values at intermediate virtual noise strengths (below the hardware level), leading to partially mitigated results at a lower sampling cost. Moreover, multiple results obtained with different noise-reduction factors can be further postprocessed with ZNE to better approximate the zero-noise limit.

Suppression of Shot Noise During the Soft Reset by Cascaded Transitions on a Potential Ladder With Single-Carrier Charging Steps

A shot noise suppression process of the emission-limited or the “soft” reset in an image sensor is investigated by analytically solving a master (Kolmogorov-Bateman) equation for a continuous-time Markov chain with correlated carrier emission rates. An explicit form of the probability distribution function, the hypoexponential type, is derived. An analytical form of the soft-reset (SR) noise is derived as the second-order moment, that is, variance, of the distribution function. It describes all the main characteristics of the SR noise previously reported; time-dependent shot noise suppression approaching an asymptotic limit of the half amount of noise charges as those of the fast or “hard” reset. The noise suppression mechanism is attributed to cascaded transitions of the storage node potential on a potential ladder giving the variance composed of a uniformly decreasing convergent series. The noise reduction factor is shown to be determined by the ladder spacing of a single-carrier charging potential. From the first-order moment analysis, an average time or lifetime dependence identical to that of the deterministic diode-decay equation is derived. Thus, the SR noise can be characterized by the governing probability law and its moments.

A practical model of twin-beam experiments for sub-shot-noise absorption measurements

Quantum-intensity-correlated twin beams of light can be used to measure absorption with precision beyond the classical shot-noise limit. The degree to which this can be achieved with a given estimator is defined by the quality of the twin-beam intensity correlations, which is quantified by the noise reduction factor. We derive an analytical model of twin-beam experiments, incorporating experimental parameters such as the relative detection efficiency of the beams, uncorrelated optical noise, and uncorrelated detector noise. We show that for twin beams without excessive noise, measured correlations can be improved by increasing the detection efficiency of each beam; notwithstanding, this may unbalance detection efficiency. However, for beams with excess intensity or other experimental noise, one should balance detection efficiency, even at the cost of reducing detection efficiency—we specifically define these noise conditions and verify our results with statistical simulation. This has application in design and optimization of absorption spectroscopy and imaging experiments.

Newtonian-noise reassessment for the Virgo gravitational-wave observatory including local recess structures

The LIGO and Virgo Scientific Collaborations have cataloged ten confident detections from binary black holes and one from binary neutron stars in their first two observing runs, which has already brought up an immense desire among the scientists to study the Universe and to extend the knowledge of astrophysics from these compact objects. One of the fundamental noise sources limiting the achievable detector bandwidth is given by Newtonian noise arising from terrestrial gravity fluctuations. It is important to model Newtonian noise spectra very accurately as it cannot be monitored directly using current technology. In this article, we show the reduction in the Newtonian noise curve obtained by more accurately modelling the current configuration of the Virgo observatory. In Virgo, there are clean rooms or recess like structures underneath each test mirror forming the main two Fabry–Perot arm cavities of the detector. We compute the displacements originating from an isotropic Rayleigh field including the recess structure. We find an overall strain noise reduction factor of 2 in the frequency band from 12 to about 15 Hz relative to previous models. The reduction factor depends on frequency and also varies between individual test masses.

Identification of noise level and indication of its impact on residential barrier design in street edge

Pengaruh kebisingan terhadap fisik manusia tidak saja mengganggu organ pendengaran, tetapi juga dapat menimbulkan gangguan pada organ-organ tubuh yang lain serta penurunan efektivitas kerja dan kinerja. Penelitian ini bertujuan untuk mengkaji tingkat kebisingan di hunian di tepi jalan raya Kota Yogyakarta serta menemukan indikasi dampak pada desain bangunan dan barrier oleh pemilik rumah untuk mengurangi kebisingan. Penelitian ini bersifat kuantitatif asosiatif. Data diperoleh dari pengukuran dan pengamatan lapangan. Hasil penelitian menunjukan bahwa tingkat kebisingan di hunian di tepi jalan raya, kelas jalan II, jalan lokal, di Kota Yogyakarta belum memenuhi standar nilai LTNI dan LNP. Desain bangunan serta barrier sebagai faktor pereduksi kebisingan jalan raya ditemukan dengan persentase sebesar 100% pada ruas Jalan Bung Tarjo, 85,7% pada ruas Jalan Ki Penjawi, 20,83% pada ruas Jalan Juminahan, 52,08% pada ruas Jalan Bausasran, 13,37% pada ruas Jalan Suryodiningratan, dan 10,7% pada ruas Jalan Mangkuyudan. Dengan demikian masyarakat belum sepenuhnya sadar terhadap tingginya tingkat kebisingan jalan raya.

Nonclassical noise features in a correlation plenoptic imaging setup

Sub-shot-noise imaging and correlation plenoptic imaging are two quantum imaging techniques that enable to overcome different problems of classical imaging systems. Combining the two techniques is not trivial, since the former is based on the detection of identical corresponding modes to subtract noise, while the latter requires the detection of different modes to perform directional reconstruction. In this paper, we experimentally show the possibility to obtain a noise-reduction factor smaller than one, a necessary condition to perform sub-shot-noise imaging, in a setup that can be adapted to correlation plenoptic imaging.

Analysis of Correlation in MEMS Gyroscope Array and its Influence on Accuracy Improvement for the Combined Angular Rate Signal.

Obtaining a correlation factor is a prerequisite for fusing multiple outputs of a mircoelectromechanical system (MEMS) gyroscope array and evaluating accuracy improvement. In this paper, a mathematical statistics method is established to analyze and obtain the practical correlation factor of a MEMS gyroscope array, which solves the problem of determining the Kalman filter (KF) covariance matrix Q and fusing the multiple gyroscope signals. The working principle and mathematical model of the sensor array fusion is briefly described, and then an optimal estimate of input rate signal is achieved by using of a steady-state KF gain in an off-line estimation approach. Both theoretical analysis and simulation show that the negative correlation factor has a favorable influence on accuracy improvement. Additionally, a four-gyro array system composed of four discrete individual gyroscopes was developed to test the correlation factor and its influence on KF accuracy improvement. The result showed that correlation factors have both positive and negative values; in particular, there exist differences for correlation factor between the different units in the array. The test results also indicated that the Angular Random Walk (ARW) of 1.57°/h0.5 and bias drift of 224.2°/h for a single gyroscope were reduced to 0.33°/h0.5 and 47.8°/h with some negative correlation factors existing in the gyroscope array, making a noise reduction factor of about 4.7, which is higher than that of a uncorrelated four-gyro array. The overall accuracy of the combined angular rate signal can be further improved if the negative correlation factors in the gyroscope array become larger.