Cross-correlated Noises Research Articles

Low-frequency resistance fluctuations in an ionic-liquid-gated channel probed by cross-correlation noise spectroscopy

Low-frequency resistance fluctuations in an ionic-liquid-gated channel probed by cross-correlation noise spectroscopy

IFNet: Data-driven multisensor estimate fusion with unknown correlation in sensor measurement noises

In recent years, multisensor fusion for state estimation has gained considerable attention. The effectiveness of the optimal fusion estimation method heavily relies on the correlation among sensor measurement noises. To enhance estimate fusion performance by mining unknown correlation in the data, this paper introduces a novel multisensor fusion approach using an information filtering neural network (IFNet) for discrete-time nonlinear state space models with cross-correlated measurement noises. The method presents three notable advantages: First, it offers a data-driven perspective to tackle uncertain correlation in multisensor estimate fusion while preserving the interpretability of the information filtering. Second, by harnessing the RNN’s capability to manage data streams, it can dynamically update the fusion weights between sensors to improve fusion accuracy. Third, this method has a lower complexity than the state-of-the-art KalmanNet measurement fusion method when dealing with the fusion problem involving a large number of sensors. Numerical simulations demonstrate that IFNet exhibits better fusion accuracy than traditional filtering methods and KalmanNet fusion filtering when correlation among measurement noises is unknown.

Analysis of Channel Current Noise in Small Nanoscale Metal Oxide Semiconductor Field Effect Transistors.

The shrinkage of metal oxide semiconductor field effect transistor (MOSFET) to the small size of the nanoscale results in changes in their channel current noise composition. This paper determines the channel current noise composition of 90nm MOSFET through experiments, and according to the device material and noise characteristics analysis, the channel current noise of 90nm and below is obtained, which not only contains thermal noise and suppressed channel shot noise, but also adds suppressed gate tunneling shot noise and cross-correlation noise. Then, Monte Carlo simulation of 10nm MOSFET noise is further used to determine the channel current composition of small size nanoscale devices. Subsequently, based on the device structure and fundamental characteristics of channel current noise, the channel current noise model is established. Finally, this model is employed to analyze the relationship between thermal noise, suppressed shot noise, cross-correlation noise, and channel current noise in relation to bias parameters and device characteristics. The theoretical results are basically consistent with the experimental and the simulated results, and the channel noise increases with the increase of bias voltage. This achievement holds promise for enhancing the operational efficiency, reliability, and lifetime of nanoscale small-sized MOSFET devices.

Semiconductor laser systems excited by multiplicative Ornstein-Uhlenbeck noise and additive sine-Wiener noise in relation to real and imaginary parts.

In this paper we study a semiconductor laser system excited by multiplicative Ornstein-Uhlenbeck (OU) noise and additive sine-Wiener (SW) noise with a related real part and imaginary part. The two-dimensional Langevin equation(LE) with cross-correlating complex OU noise and complex SW noise is equivalent to the six-dimensional LE. Based on functional methods and spatial dimension extension methods, the six-dimensional Fokker-Planck equation(FPE) is achieved. Through Taylor expansion approximation and linear transformation, the dimensionality of FPE is reduced, and the exact expression of the probability distribution (SPD) in steady state is obtained. The impacts of noise parameters on laser intensity on SPD are further analyzed. Moreover, based on the reduced FPE, the information entropy of the system is obtained. This calculation is useful for us to understand further the influence of system parameters and noise correlation coefficient on the system. The main work lies in obtaining an alternative method for deriving a FPE corresponding to the two-dimensional stochastic semiconductor laser model, which is more applicable than methods in previous literature. An equivalent expression for cross-correlated OU noise and cross-correlated SW noise as well as a method for approximate solutions of a high-dimensional FPE are also provided.

Protecting Quantum Information via Destructive Interference of Correlated Noise.

Decoherence and imperfect control are crucial challenges for quantum technologies. Common protection strategies rely on noise temporal autocorrelation, which is not optimal if other correlations are present. We develop and demonstrate experimentally a strategy that uses the cross-correlation of two noise sources. Utilizing destructive interference of cross-correlated noise extends the coherence time tenfold, improves control fidelity, and surpasses the state-of-the-art sensitivity for high frequency quantum sensing, significantly expanding the applicability of noise protection strategies.

Different Fractional Charges from Auto- and Cross-Correlation Noise in Quantum Hall States without Upstream Modes.

Fractional charges of anyons can be extracted from shot noise in two ways. One can use either the autocorrelation noise of the current in one drain or the cross-correlation noise between two drains on the two sides of the device. The former approach typically overestimates the charge. This may happen due to upstream edge modes. We propose a mechanism for the excess autocorrelation noise without upstream modes. It applies to systems with multiple copropagating edge modes and assumes that the noise is measured at a low but nonzero frequency.

Impact of Double Time Delays on Regime Shift and Stochastic Resonance for a Species Population System Driven by Colored Correlated Multiplicative and Additive Noises

In this paper, the characteristics for the state transition between the boom state and the extinction one, varius stochastic resonance (SR) phenomena for a species population system induced by double time delays and colored cross-correlated Gaussian noises are investigated. The control of the species population system has an important effect on ecological balance and the development of human living environment. By means of the numerical calculation of the mean extinction time and the stationary probability density function (SPDF), we can figure out some fact: both external and internal noises, the noise correlation strength and its correlation time, one time delay can all reduce the ecological stability and shorten the survival time of the system; while the other time delay can enhance significantly the biological stability and postpone the extinction of the population. For the mean extinction time (MET) of the species population, it is found that noise correlation strength, time delay, the noise correlation time can all reduce the peak value of the MET, which leads to the reduction of the life cycle. Inversely, the other time delay will not change the maximum of the MET, and induce the peak value to shift to the left. With respect to the SNR, it is discovered that in the noise correlation strength and its correlation time, one-time delay mainly plays a prominent role in inhibiting the SR effect. On the contrary, the multiplicative noise can result in the enhancement of the resonant peak. In particular, the other time delay and the additive noise can stimulate the SR effect for the SNR during the initial period. However, the further increase of them will bring about the reduction of the resonant phenomenon.

Tumor state transitions driven by Gaussian and non-Gaussian noises

Tumor state transitions between the excited (high-concentration) and nonexcited (low-concentration) basins under the Gaussian white noise and non-Gaussian colored noise are investigated via the most probable steady states (MPSS) and the first escape probability (FEP)-based stochastic basin of attraction (SBA), respectively. Reducing the non-Gaussian colored noise and then utilizing the unified colored noise approximation (UCNA), the Markov system is derived. The extremal controlling equation of stationary probability density function (SPDF) is derived to analyze the impacts of noise on transitions in terms of MPSS. The existence of the ‘color’ of the non-Gaussian colored noise induces the reappearance of the uncorrelated additive white noise parameter that had vanished from the extremal controlling equation, completely reversing the inability of the uncorrelated additive Gaussian white noise to operate on transitions. The FEP-dependent SBA characterizing the excited basin stability is performed to further analyze the role of noise on the likelihood of escaping to the nonexcited state. Results show that the cross-correlated noises play a dual role in regulating SBA. The increased SBA indicating more difficulty to escape to the nonexcited state reflects a worse therapeutic effect. Therefore, enhancing the negatively correlated noise intensities and augmenting the non-Gaussian noise correlation time is essential for destabilizing the excited basin and achieving optimal therapeutic efficacy.

Influence of colored cross-correlated noise on stochastic resonance for an underdamped bistable system subjected to multiplicative and additive noises

The stochastic resonance (SR) behavior for an underdamped bistable system with colored cross-correlated noise between multiplicative and additive noise is investigated. The stationary probability density is obtained under the condition of the detailed balance. The expressions for the signal-to-noise ratios (SNRs) for two initial states is deduced by applying two-state theory under the adiabatic condition. The analysis result indicates that the SR phenomenon takes place when the SNRs vary with the coupling strength and the correlation time of the cross-correlated noise. Double SR phenomenon occurs on SNRs’ curves with the increase of the strength of the additive noise. One resonance peak exists when the SNRs change with the damping coefficient and with the intensity of the multiplicative noise.

Sequential Fusion Filter for State Estimation of Nonlinear Multi-Sensor Systems with Cross-Correlated Noise and Packet Dropout Compensation

This paper is concerned with the problem of state estimation for nonlinear multi-sensor systems with cross-correlated noise and packet loss compensation. In this case, the cross-correlated noise is modeled by the synchronous correlation of the observation noise of each sensor, and the observation noise of each sensor is correlated with the process noise at the previous moment. Meanwhile, in the process of state estimation, since the measurement data may be transmitted in an unreliable network, data packet dropout will inevitably occur, leading to a reduction in estimation accuracy. To address this undesirable situation, this paper proposes a state estimation method for nonlinear multi-sensor systems with cross-correlated noise and packet dropout compensation based on a sequential fusion framework. Firstly, a prediction compensation mechanism and a strategy based on observation noise estimation are used to update the measurement data while avoiding the noise decorrelation step. Secondly, a design step for a sequential fusion state estimation filter is derived based on an innovation analysis method. Then, a numerical implementation of the sequential fusion state estimator is given based on the third-degree spherical-radial cubature rule. Finally, the univariate nonstationary growth model (UNGM) is combined with simulation to verify the effectiveness and feasibility of the proposed algorithm.

Convolutional neural network to distinguish glitches from minute-long gravitational wave transients

Gravitational wave bursts are transient signals distinct from compact binary mergers that arise from a wide variety of astrophysical phenomena. Because most of these phenomena are poorly modeled, the use of traditional search methods such as matched filtering is excluded. Bursts include short ($<$10 seconds) and long (from 10 to a few hundreds of seconds) duration signals for which the detection is constrained by environmental and instrumental transient noises called glitches. Glitches contaminate burst searches, reducing the amount of useful data and limiting the sensitivity of current algorithms. It is therefore of primordial importance to locate and distinguish them from potential burst signals. In this paper, we propose to train a convolutional neural network to detect glitches in the time-frequency space of the cross-correlated LIGO noise. We show that our network is retrieving more than 95$\%$ of the glitches while being trained only on a subset of the existing glitch classes highlighting the sensitivity of the network to completely new glitch classes.

Cooper pair splitting controlled by a temperature gradient.

Electrons in two different normal metallic electrodes attached to a sufficiently thin superconducting island may become entangled due to the effect of Cooper pair splitting. This phenomenon is of fundamental importance and may also have serious implications for developing quantum communication technologies. One way to identify Cooper pair splitting is to analyze long-range cross correlations of fluctuating currents in three-terminal hybrid normal-superconducting-normal nanostructures. Here, we theoretically investigate non-trivial behavior of cross-correlated non-local shot noise in the presence of a temperature gradient. We suggest that applying a temperature gradient may serve as an extra tool to control the phenomenon of Cooper pair splitting.

Effect of color cross-correlated noise on the growth characteristics of tumor cells under immune surveillance.

Based on the Michaelis-Menten reaction model with catalytic effects, a more comprehensive one-dimensional stochastic Langevin equation with immune surveillance for a tumor cell growth system is obtained by considering the fluctuations in growth rate and mortality rate. To explore the impact of environmental fluctuations on the growth of tumor cells, the analytical solution of the steady-state probability distribution function of the system is derived using the Liouville equation and Novikov theory, and the influence of noise intensity and correlation intensity on the steady-state probability distributional function are discussed. The results show that the three extreme values of the steady-state probability distribution function exhibit a structure of two peaks and one valley. Variations of the noise intensity, cross-correlation intensity and correlation time can modulate the probability distribution of the number of tumor cells, which provides theoretical guidance for determining treatment plans in clinical treatment. Furthermore, the increase of noise intensity will inhibit the growth of tumor cells when the number of tumor cells is relatively small, while the increase in noise intensity will further promote the growth of tumor cells when the number of tumor cells is relatively large. The color cross-correlated strength and cross-correlated time between noise also have a certain impact on tumor cell proliferation. The results help people understand the growth kinetics of tumor cells, which can a provide theoretical basis for clinical research on tumor cell growth.

Impact of self-heating on thermal noise in In1−xGaxAs GAA MOSFETs

Self-heating in nanoscale gate-all-around (GAA) MOSFETs can be attributed to the low thermal conductivity of channel material, gate dielectric material, and large thermal resistance of the source and drain contacts. Self-heating can severely increase the thermal noise level in nanoscale gate-all-around (GAA) MOSFETs as the peak lattice temperature increases several degrees above the ambient temperature. This work presents a detailed analysis of thermal noise in InGaAs based nanowire (NW)/nanosheet (NS) GAA metal-oxide-semiconductor field-effect transistors (MOSFETs). Calibrated electro-thermal simulation results are used to analyze the influence of interfacial thermal resistance (ITR), the number of nanowires/nanosheets (N) and mole fraction of Gallium on drain noise power spectral density (SID), induced gate noise power spectral density (SIG), and cross-correlation noise power spectral density (SIC). The impact of engineered source/drain contacts and thermal conductivity of buried oxide (BOX) materials on SID, SIG, and SIC parameters is also investigated in this work. It is observed that Si3N4 outperforms SiO2 as a BOX material. The noise power spectral densities such as SID, SIG, and SIC decrease by 8%, 27%, and 22%, respectively, in NW GAA MOSFETs and 16%, 26%, and 18%, respectively, in NS GAA MOSFETs, when Si3N4 replaces SiO2 as a BOX layer.

Stochastic Resonance in a Fractional Oscillator with Cross-Correlation Noise

Stochastic Resonance in a Fractional Oscillator with Cross-Correlation Noise

Noise enhanced stability of an active particle in a spatial metastable potential driven by cross-correlated noises

We investigate the escape dynamics of an active Brownian particle (ABP) in a spatial cubic potential subject to the cross-correlated multiplicative noise and additive noise. Based on the Schweitzer–Ebeling–Tilch model, the effects of noise strength, cross-correlation intensity between noises, damping coefficient and potential amplitude on the mean escape time (MET) from a metastable potential state are analyzed. The results indicate that the MET exhibits a non-monotonic behavior with a maximum as a function of the intensities of the multiplicative and additive noises, identifying the occurrence of the noise enhanced stability (NES) effects induced by the multiplicative noise and by the additive noise. The increase of the cross-correlation strength always enhances the NES effect induced by the additive noise, regardless of the cross-correlation between noises is positive or negative. However, the positive and negative cross-correlation play an opposite role on the NES effect induced by the multiplicative noise. Moreover, the NES effects induced by the additive and multiplicative noises can be enhanced by the increase of the damping coefficient and the potential amplitude. A physical mechanism for the NES effect of the ABP can be understood as the fact that a certain amount of noise can stabilize the sojourn of the ABP in a limit cycle. Our results demonstrate that the cross-correlation between noises may provide a possible strategy for controlling the stability of active particle systems.

Global state estimation under sequential measurement fusion for clustered sensor networks with cross-correlated measurement noises

In practical multi-sensor fusion estimation, both the expensive communication burden of long-distance connection sensor networks and cross-correlated noises are usually inevitable, and need to be taken into account. To adequately address these difficulties, a global fusion estimation problem is studied for clustered sensor networks with cross-correlated measurement noises. To begin, we derive direct and indirect sequential measurement fusion (SMF) schemes as fusion rules, relying on whether a weighted least square method is used directly for the arriving measurements. We discover that the direct SMF has lower computational complexity than the indirect SMF, but the estimation accuracy of the latter is higher when the number of sensors exceeds three. Then, a globally indirect sequential measurement fusion estimation (GISMF) algorithm is proposed by using the indirect SMF, which is more computationally efficient and suitable for asynchronous fusion than that of batch fusion estimation. Accuracy relations among the GISMF, the batch state fusion estimation, and the centralized Kalman fuser (CKF) are proved. Moreover, the equality of the estimation accuracy between the GISMF and the CKF is also performed if all the measurement noises are mutually independent or if the measurement noises are only cross-correlated within the same cluster. Finally, several simulation results are implemented to show the effectiveness of the presented algorithm.

Ratchet effect of interacting active particles induced by cross-correlated noises

Ratchet effect of interacting active particles induced by cross-correlated noises

The analysis of channel noise properties and its correlation in nanoscale metal–oxide–semiconductor field-effect transistors

During the traditional channel noise modeling of nanoscale MOSFETs, neither the suppression of shot noise by Fermi and Coulomb effects nor the cross correlation noise between the source current noise and gate current noise is considered. However, they should not be ignored. In this study, the channel noise of a 22 nm MOSFET is tested experimentally, and the results show that the suppressed shot noise, the thermal noise, and the cross correlation noise are the main types of channel noises in nano-MOSFETs. Furthermore, according to the physical structure and characteristics of the MOSFET, a noise model, including the elements of shot noise, thermal noise, and cross correlation noise, is derived, which considers the influence of the shot noise suppressed by either the Fermi or Coulomb effects. Based on the model, the variation of noise with the channel length, temperature, source–drain voltage, and gate voltage is analyzed. The results are consistent with the experiments and theories in the literature.

Optimal Kalman-like filter for a class of nonlinear stochastic systems

This paper deals with an optimal Kalman-like filter for nonlinear discrete-time systems aided with auto and cross-correlated noises and stochastic parameter matrices involved in state and measurement equations, and random nonlinearity. The random variables are proposed by their statistical characteristics while the inquiry is focused on stochastic multivariate analysis and calculation. For the nonlinear system with the auto and cross-correlated noises and stochastic parameter matrices, an equivalent system is first reconstructed by decomposing stochastic parameter matrices and introducing uncorrelated pseudo-noises. Then a recursive filter that ensures unbiasedness and minimizes the error variance is designed for the newly transformed equivalent system. Finally, the filter is verified by applying it to some numerical simulations.