Time-dependent Noise Research Articles

Noise monitoring in primary schools: comparisons between different time-dependent parameters for acoustic performance evaluation

The A-weighted equivalent sound level is commonly used to describe or regulate environmental noise over a defined time interval. Although it is very convenient and easy to compare noise limits or requirements, it does not provide summary information on how noise evolves. On the other hand, the detailed analysis of the history of the measurements over time is too burdensome in the case of long-term monitoring. As part of a large study that aims to investigate the effects of noise on the cognitive abilities of primary school children, long-term unattended monitoring was carried out using low-cost instrumentation based on smartphone apps and calibrated external microphones. From the data obtained, acoustic indices and parameters were calculated, which allowed the assessment of the time-dependent noise exposure of the students based on the type of activity carried out in class. This analysis can be useful for validating the acoustic design requirements in schools.

Entanglement buffering with two quantum memories

Quantum networks crucially rely on the availability of high-quality entangled pairs of qubits, known as entangled links, distributed across distant nodes. Maintaining the quality of these links is a challenging task due to the presence of time-dependent noise, also known as decoherence. Entanglement purification protocols offer a solution by converting multiple low-quality entangled states into a smaller number of higher-quality ones. In this work, we introduce a framework to analyse the performance of entanglement buffering setups that combine entanglement consumption, decoherence, and entanglement purification. We propose two key metrics: the availability, which is the steady-state probability that an entangled link is present, and the average consumed fidelity, which quantifies the steady-state quality of consumed links. We then investigate a two-node system, where each node possesses two quantum memories: one for long-term entanglement storage, and another for entanglement generation. We model this setup as a continuous-time stochastic process and derive analytical expressions for the performance metrics. Our findings unveil a trade-off between the availability and the average consumed fidelity. We also bound these performance metrics for a buffering system that employs the well-known bilocal Clifford purification protocols. Importantly, our analysis demonstrates that, in the presence of noise, consistently purifying the buffered entanglement increases the average consumed fidelity, even when some buffered entanglement is discarded due to purification failures.

Lévy noise-induced effects in a long Josephson junction in the presence of two different spatial noise distributions

We analyze the impact of Lévy-distributed stochastic fluctuations on the average switching time and voltage drop across a current-biased long Josephson tunnel junction. We compare the system’s response for two spatial configurations of time-dependent noise, i.e., homogeneous and distributed along the junction length. The response of the Josephson junction is explored by varying the characteristic parameter of the Lévy source, i.e., the α stability index and the noise intensity. These findings offer an effective tool to characterize a Lévy component possibly embedded in an unknown noise signal.

Quantum control for time-dependent noise by inverse geometric optimization

Quantum control for time-dependent noise by inverse geometric optimization

Aerodynamic noise analysis of tilting rotor in edgewise flow conditions

This paper presents a comprehensive experimental analysis of the noise characteristics of an isolated tilt-rotor system under edgewise flight conditions. The investigation explores the effect of rotor tilt on noise and aerodynamics using flow velocity, thrust, and far-field noise measurements. Flow field results show that as the tilting angles vary, there is a change in speed over the rotor blade surface, which influences vortex formation and wake attributes. The far-field noise spectra revealed a significant decrease in sound pressure level with increasing tilt angle, predominantly evident in both the high-amplitude tonal peaks and the broadband signal within the low-to-mid frequency range. The directivity patterns of the overall sound pressure level also demonstrated a reduction in magnitude with the tilting of the rotor. This reduction was observed consistently across all top-plane observation points, with a monopole directivity trend. Meanwhile, in the side plane array, the decrease was primarily evident above the plane of rotation with a dipole directivity pattern. The radiation direction at which the minimum sound pressure level occurs was identified near the rotation plane, irrespective of the tilt angle. Furthermore, the time-dependent noise analyses revealed dominant and persistent signal characteristics at the blade passing frequency, whereas the mid-frequency range exhibited more intermittent behaviour, and the high-frequency range indicated transient characteristics.

Noise-Suppressing Newton Algorithm for Kinematic Control of Robots

In this paper, armed with the integral control method, a new noise-suppressing Newton (NSN) algorithm is proposed for the redundancy resolution of redundant robot manipulators efficiently. For practical hardware implementation, the discrete-time noise-suppressing Newton (abbreviated as DTNSN) algorithm is discretized from the continues NSN algorithm. Specifically, the distinguishing feature of the proposed DTNSN algorithm is that it can rigorously converge with inherent tolerance to noises induced by communication jamming and computational systematical errors. In contrast, considerable traditional algorithms often dispose of noises with the high-degree filter from the viewpoint of signal processing, which requires a complex system structure and further results in a heavy computational burden. Note that theoretical analyses are provided to elaborate the convergent property of the DTNSN algorithm polluted with constant bias, time-dependent linear noises and bounded random noises. Besides, by the proposed DTNSN algorithm, the end effector of both serial and parallel redundant robot manipulators complete the allocated motion planning and are impervious to the noisy simulated environment.

Adaptive quantum error mitigation using pulse-based inverse evolutions

AbstractQuantum Error Mitigation (QEM) enables the extraction of high-quality results from the presently-available noisy quantum computers. In this approach, the effect of the noise on observables of interest can be mitigated using multiple measurements without additional hardware overhead. Unfortunately, current QEM techniques are limited to weak noise or lack scalability. In this work, we introduce a QEM method termed ‘Adaptive KIK’ that adapts to the noise level of the target device, and therefore, can handle moderate-to-strong noise. The implementation of the method is experimentally simple — it does not involve any tomographic information or machine-learning stage, and the number of different quantum circuits to be implemented is independent of the size of the system. Furthermore, we have shown that it can be successfully integrated with randomized compiling for handling both incoherent as well as coherent noise. Our method handles spatially correlated and time-dependent noise which enables us to run shots over the scale of days or more despite the fact that noise and calibrations change in time. Finally, we discuss and demonstrate why our results suggest that gate calibration protocols should be revised when using QEM. We demonstrate our findings in the IBM quantum computers and through numerical simulations.

FEMFFUSION and its verification using the C5G7 benchmark

FEMFFUSION is an open source code that solves the multigroup neutron transport equation using the diffusion and the SPN approximations. This code uses the continuous Galerkin finite element method to be able to deal with any type of geometry, structured or unstructured, and problem dimension. To verify the program, a research study of the two-dimensional C5G7 benchmark has been performed, including the static, time-dependent and neutron noise computations. Numerical results include the effective multiplication factor, keff, the spatial neutron fluxes, and neutron power distributions for the static computations. The total neutron power evolution of a given transient and the neutron flux distribution evolution for the different energy groups. In addition, neutron noise frequency domain calculation were completed for perturbations of some cross-section in the reactor core. All computation have been performed using different SPN approximations. FEMFFUSION results are verified against the official OECD/NEA benchmark results.

Requirements for a processing-node quantum repeater on a real-world fiber grid

We numerically study the distribution of entanglement between the Dutch cities of Delft and Eindhoven realized with a processing-node quantum repeater and determine minimal hardware requirements for verifiable blind quantum computation using color centers and trapped ions. Our results are obtained considering restrictions imposed by a real-world fiber grid and using detailed hardware-specific models. By comparing our results to those we would obtain in idealized settings, we show that simplifications lead to a distorted picture of hardware demands, particularly on memory coherence and photon collection. We develop general machinery suitable for studying arbitrary processing-node repeater chains using NetSquid, a discrete-event simulator for quantum networks. This enables us to include time-dependent noise models and simulate repeater protocols with cut-offs, including the required classical control communication. We find minimal hardware requirements by solving an optimization problem using genetic algorithms on a high-performance-computing cluster. Our work provides guidance for further experimental progress, and showcases limitations of studying quantum-repeater requirements in idealized situations.

Characterizing High Rate GNSS Velocity Noise for Synthesizing a GNSS Strong Motion Learning Catalog

Data-driven approaches to identify geophysical signals have proven beneficial in high dimensional environments where model-driven methods fall short. GNSS offers a source of unsaturated ground motion observations that are the data currency of ground motion forecasting and rapid seismic hazard assessment and alerting. However, these GNSS-sourced signals are superposed onto hardware-, location- and time-dependent noise signatures influenced by the Earth’s atmosphere, low-cost or spaceborne oscillators, and complex radio frequency environments. Eschewing heuristic or physics based models for a data-driven approach in this context is a step forward in autonomous signal discrimination. However, the performance of a data-driven approach depends upon substantial representative samples with accurate classifications, and more complex algorithm architectures for deeper scientific insights compound this need. The existing catalogs of high-rate (≥1Hz) GNSS ground motions are relatively limited. In this work, we model and evaluate the probabilistic noise of GNSS velocity measurements over a hemispheric network. We generate stochastic noise time series to augment transferred low-noise strong motion signals from within 70 kilometers of strong events (≥ MW 5.0) from an existing inertial catalog. We leverage known signal and noise information to assess feature extraction strategies and quantify augmentation benefits. We find a classifier model trained on this expanded pseudo-synthetic catalog improves generalization compared to a model trained solely on a real-GNSS velocity catalog, and offers a framework for future enhanced data driven approaches.

Rate of Convergence in the Smoluchowski-Kramers Approximation for Mean-field Stochastic Differential Equations

In this paper we study a second-order mean-field stochastic differential systems describing the movement of a particle under the influence of a time-dependent force, a friction, a mean-field interaction and a space and time-dependent stochastic noise. Using techniques from Malliavin calculus, we establish explicit rates of convergence in the zero-mass limit (Smoluchowski-Kramers approximation) in the Lp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^p$$\\end{document}-distances and in the total variation distance for the position process, the velocity process and a re-scaled velocity process to their corresponding limiting processes.

Noise footprint assessment at a vertiport for different approach and departure procedures of a tilt-wing air-taxi

Community noise at vertiports is one of the most important questions related to upcoming urban air mobility (UAM) operations. While fixed-wing and/or fixed-rotor aircraft can mainly be treated by their changing operational parameters, such as rotor or propeller rpm, tilt-wing or tilt-engine configurations are more difficult to simulate because of their constantly changing noise emission and spatial radiation characteristics. The work presented in this paper is providing an overview of the noise situation at a virtual vertiport which is being approached and departed by a tilt-wing air-taxi in different ways. Several different departure procedures are simulated with the same generic air-taxi. For the noise emission semi-empiric methods were used. During the air-taxi's descent and climb, different tilt configurations are included, mainly defined by the time dependent engine's tilt-angle, but also related to different approach paths. Each approach or departure procedure is generating individually time dependent changing noise emission characteristics which are used for noise footprint mapping around the touch-down or lift-off point. Different noise metrics are computed, including some which are representative to indicate noise annoyance among the vertiport's neighborhood. It is expected that each procedure will generate its own specific community noise situation in the vicinity of the vertiport, and thus may provide an early recommenddation for later operations. The results are compared towards each other. Additionally, a simulated certification flyover according to ICAO Chapter 13 - which is about the noise certification of tilt-rotor aircraft - is set into relation to the vertiport's community noise.

Asymptotic stability of evolution systems of probability measures for nonautonomous stochastic systems: Theoretical results and applications

The limiting stability of invariant probability measures of time homogeneous transition semigroups for autonomous stochastic systems has been extensively discussed in the literature. In this paper we initially initiate a program to study the asymptotic stability of evolution systems of probability measures of time inhomogeneous transition operators for nonautonomous stochastic systems. Two general theoretical results on this topic are established in a Polish space by establishing some sufficient conditions which can be verified in applications. Our abstract results are applied to a stochastic lattice reaction-diffusion equation driven by a time-dependent nonlinear noise. A time-average argument and an extended Krylov-Bogolyubov method due to Da Prato and Röckner [Seminar on stochastic analysis, random fields and applications V, Birkhäuser, Basel, 2008] are employed to prove the existence of evolution systems of probability measures. A mild condition on the time-dependent diffusion function is used to prove that the limit of every evolution system of probability measures must be an evolution system of probability measures of the limiting equation. The theoretical results are expected to be applied to various stochastic lattice systems/ODEs/PDEs in the future.

Blade-Tip Vortex Noise Mitigation Traded-Off against Aerodynamic Design for Propellers of Future Electric Aircraft

We study noise generation at the blade tips of propellers designed for future electric aircraft propulsion and, furthermore, analyze the interrelationship between noise mitigation and aerodynamics improvement in terms of propeller geometric designs. Classical propellers with three or six blades and a conceptual propeller with three joined dual-blades are compared to understand the effects of blade tip vortices on the noise generation and aerodynamics. The dual blade of the conceptual propeller is constructed by joining the tips of two sub-blades. These propellers are designed to operate under the same freestream flow conditions and similar electric power consumption. The Improved Delayed Detached Eddy Simulation (IDDES) is adopted for the flow simulation to identify high-resolution time-dependent noise sources around the blade tips. The acoustic computations use a time-domain method based on the convective Ffowcs Williams–Hawkings (FW-H) equation. The thrust of the 3-blade conceptual propeller is 4% larger than the 3-blade classical propeller and 8% more than the 6-blade one, given that they have similar efficiencies. Blade tip vortices are found emitting broadband noise. Since the classical and conceptual 3-blade propellers have different geometries, especially at the blade tips, they introduce deviations in the vortex development. However, the differences are small regarding the broadband noise generation. As compared to the 6-blade classical propeller, both 3-blade propellers produce much larger noise. The reason is that the increased number of blades leads to the reduced strength of tip vortices. The findings indicate that the noise mitigation through the modification of the blade design and number can be traded-off by the changed aerodynamic performance.

Threshold theorem in isolated quantum dynamics with stochastic control errors.

We investigate the effect of stochastic control errors in the time-dependent Hamiltonian on isolated quantum dynamics. The control errors are formulated as time-dependent stochastic noise in the Schrödinger equation. For a class of stochastic control errors, we establish a threshold theorem that provides a sufficient condition to obtain the target state, which should be determined in noiseless isolated quantum dynamics, as a relation between the number of measurements and noise strength. The theorem guarantees that if the sum of the noise strengths is less than the inverse of computational time, the target state can be obtained through a constant-order number of measurements. If the opposite is true, the number of measurements to guarantee obtaining the target state increases exponentially with computational time. Our threshold theorem can be applied to any isolated quantum dynamics such as quantum annealing and adiabatic quantum computation. This article is part of the theme issue 'Quantum annealing and computation: challenges and perspectives'.

Anderson and many-body localization in the presence of spatially correlated classical noise

We study the effect of spatially correlated classical noise on both Anderson and many-body localization of a disordered fermionic chain. By analyzing the evolution of the particle density imbalance following a quench from an initial charge density wave state, we find prominent signatures of localization also in the presence of the time-dependent noise, even though the system eventually relaxes to the infinite temperature state. In particular, for sufficiently strong static disorder we observe the onset of metastability, which becomes more prominent the stronger the spatial correlations of the noise. In this regime we find that the imbalance decays as a stretched-exponential - a behavior characteristic of glassy systems. We identify a simple scaling behavior of the relevant relaxation times in terms of the static disorder and of the noise correlation length. We discuss how our results could be exploited to extract information about the localization length in experimental setups.

Abundant analytic solutions of the stochastic KdV equation with time-dependent additive white Gaussian noise via Darboux transformation method

Abundant analytic solutions of the stochastic KdV equation with time-dependent additive white Gaussian noise via Darboux transformation method

Oscillating gravity, non-singularity and mass quantization from Moffat stochastic gravity arguments

In Moffat stochastic gravity arguments, the spacetime geometry is assumed to be a fluctuating background and the gravitational constant is a control parameter due to the presence of a time-dependent Gaussian white noise In such a surrounding, both the singularities of gravitational collapse and the Big Bang have a zero probability of occurring. In this communication, we generalize Moffat’s arguments by adding a random temporal tiny variable for a smoothing purpose and creating a white Gaussian noise process with a short correlation time. The Universe accordingly is found to be non-singular and is dominated by an oscillating gravity. A connection with a quantum oscillator was established and analyzed. Surprisingly, the Hubble mass which emerges in extended supergravity may be quantized.

Estimating rainfall–runoff modeling using the rainfall prognostic model-based artificial framework with a well-ordered selective genetic algorithm

Abstract Rainfall–runoff modeling is one of the most well-known applications of hydrology. The goal of rainfall–runoff modeling is to simulate the peak river flow caused by an actual or hypothetical rainfall force. In existing methods, the rainfall–runoff relationships are quantified to predict the daily streamflow of each catchment from its landscape attributes to measure the daily rainfall. However, the structural model error, infiltration rate, and the steep slopes of the hill affect the prediction process. To tackle these issues, this paper proposed a novel rainfall prognostic model-based artificial framework, which predicts day-to-day rainfall to prevent environmental disasters. The day-to-day predictions minimize the risks to life and property and also manage the agricultural farms in a better way because the possibility of rainfall has been estimated earlier. Furthermore, the posterior fire-breathing network is utilized to estimate model errors in the computational runoff by using time-dependent and random noise to the model's internal storage to solve the uncertainty problem. Since the model errors are estimated, there are limits to the infiltration rate and thus a prophetic multilayer network is utilized which relies on the soil runoff levels. Moreover, the network measures the dynamics of soil moisture to regulate the infiltration rate according to the rural or urban section. Moreover, to measure the surface water from the steep slopes, the system offered a well-ordered selective genetic algorithm to calculate the velocity of runoff in different bend areas to overcome the numerical problem. Thus, the model results showed that the work effectively predicts the rainfall from the investigation of model errors, infiltration rates, and velocity to achieve a better prediction range in the rainfall.

Anomalous ballistic scaling in the tensionless or inviscid Kardar-Parisi-Zhang equation

The one-dimensional Kardar-Parisi-Zhang (KPZ) equationis becoming an overarching paradigm for the scaling of nonequilibrium, spatially extended, classical and quantum systems with strong correlations. Recent analytical solutions have uncovered a rich structure regarding its scaling exponents and fluctuation statistics. However, the zero surface tension or zero viscosity case eludes such analytical solutions and has remained ill-understood. Using numerical simulations, we elucidate a well-defined universality class for this case that differs from that of the viscous case, featuring intrinsically anomalous kinetic roughening (despite previous expectations for systems with local interactions and time-dependent noise) and ballistic dynamics. The latter may be relevant to recent quantum spin chain experiments which measure KPZ and ballistic relaxation under different conditions. We identify the ensuing set of scaling exponents in previous discrete interface growth models related with isotropic percolation, and show it to describe the fluctuations of additional continuum systems related with the noisy Korteweg-de Vries equation. Along this process, we additionally elucidate the universality class of the related inviscid stochastic Burgers equation.