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At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Stochastic Perturbations of Stable Dynamical Systems: Trajectory-Wise Approach

We study stochastic perturbations of a dynamical system with a locally stable fixed point. The perturbed system has the form of Ito stochastic differential equations. We assume that perturbations do not vanish at the equilibrium of the deterministic system. Using the approach based on consideration of trajectories to the analysis of stochastic differential equations, we find restrictions for perturbations under which the stability of the equilibrium is preserved with probability 1.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Performance study of LMS based adaptive algorithms for unknown system identification

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Discriminating chaotic and stochastic dynamics through the permutation spectrum test

In this paper, we propose a new heuristic symbolic tool for unveiling chaotic and stochastic dynamics: the permutation spectrum test. Several numerical examples allow us to confirm the usefulness of the introduced methodology. Indeed, we show that it is robust in situations in which other techniques fail (intermittent chaos, hyperchaotic dynamics, stochastic linear and nonlinear correlated dynamics, and deterministic non-chaotic noise-driven dynamics). We illustrate the applicability and reliability of this pragmatic method by examining real complex time series from diverse scientific fields. Taking into account that the proposed test has the advantages of being conceptually simple and computationally fast, we think that it can be of practical utility as an alternative test for determinism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Entropic stochastic resonance without external force in oscillatory confined space

We have studied the dynamics of Brownian particles in a confined geometry of dumbbell-shape with periodically oscillating walls. Entropic stochastic resonance (ESR) behavior, characterizing by a maximum value of the coherent factor Q at some optimal level of noise, is observed even without external periodic force in the horizontal direction, which is necessary for conventional ESR where the wall is static and the particle is subjected to the force. Interestingly, the ESR can be remarkably enhanced by the particle gravity G, in contrast to the conventional case. In addition, Q decreases (increases) with G in the small (large) noise limit, respectively, while it non-monotonically changes with G for moderate noise levels. We have applied an effective 1D coarsening description to illustrate such a nontrivial dependence on G, by investigating the property of the 1D effective potential of entropic nature and paying special attention to the excess part resulting from the boundary oscillation. Dependences of the ESR strength with other related parameters are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Ratcheted electrophoresis of Brownian particles

The realization of nanoscale machines requires efficient methods by which to rectify unbiased perturbations to perform useful functions in the presence of significant thermal noise. The performance of such Brownian motors often depends sensitively on their operating conditions—in particular, on the relative rates of diffusive and deterministic motions. In this letter, we present a type of Brownian motor that uses contact charge electrophoresis of a colloidal particle within a ratcheted channel to achieve directed transport or perform useful work against an applied load. We analyze the stochastic dynamics of this model ratchet to show that it functions under any operating condition—even in the limit of strong thermal noise and in contrast to existing ratchets. The theoretical results presented here suggest that ratcheted electrophoresis could provide a basis for electrochemically powered, nanoscale machines capable of transport and actuation of nanoscale components.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Response analysis of a class of quasi-linear systems with fractional derivative excited by Poisson white noise

The Poisson white noise, as a typical non-Gaussian excitation, has attracted much attention recently. However, little work was referred to the study of stochastic systems with fractional derivative under Poisson white noise excitation. This paper investigates the stationary response of a class of quasi-linear systems with fractional derivative excited by Poisson white noise. The equivalent stochastic system of the original stochastic system is obtained. Then, approximate stationary solutions are obtained with the help of the perturbation method. Finally, two typical examples are discussed in detail to demonstrate the effectiveness of the proposed method. The analysis also shows that the fractional order and the fractional coefficient significantly affect the responses of the stochastic systems with fractional derivative.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

A combined phase contrast imaging and heterodyne interferometer system for multiscale fluctuation measurements (invited)

In this work, a novel combined diagnostic capable of measuring multiscale density fluctuations that extend from magnetohydrodynamic (MHD) to the lower range of electron temperature gradient turbulence has been designed, installed, and operated at DIII-D. The combined diagnostic was constructed by adding a heterodyne interferometer to the pre-existing phase contrast imaging (PCI) system, both of which measure line-integrated electron density fluctuations. The port-space footprint is minimized via use of a single 10.6 μm probe beam. With temporal bandwidths in excess of 1 MHz, the PCI measures high-k (1.5 cm -1 < |k R | ≤ 25 cm -1 ) fluctuations with sensitivity 3×10 13 m -2 /$\sqrt{kHz}$, while the interferometer simultaneously measures low-k (|k R | < 5 cm -1 ) fluctuations with sensitivity 3×10 14 m -2 /$\sqrt{kHz}$. The intentional mid-k overlap has been empirically verified with sound-wave calibrations and allows quantitative investigation of multiscale effects that are predicted to be significant in the reactor-relevant T e ~ T i regime. Lastly, via correlation with the primary DIII-D interferometer, the toroidal mode numbers of core-localized MHD can be measured.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

On the possibility of a significant improvement in the quality of a quantum ghost image by registering an additional image in the object channel

A modification of the classical scheme of the quantum ghost image formation is considered, in which an image of the object under study is formed and recorded in the object channel. This image is used together with the ghost image to construct an estimate of the transparency distribution of the object. It is shown that this technique reduces the image quality worsening associated with the non-unit quantum efficiency of the sensors, even when the quantum image obtained in the object channel is additionally distorted by noise due to photons that did not interact with the object. (image processing)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

THE IMPACT OF THE IONOSPHERE ON GROUND-BASED DETECTION OF THE GLOBAL EPOCH OF REIONIZATION SIGNAL

The redshifted 21 cm line of neutral hydrogen (H i), potentially observable at low radio frequencies (∼50–200 MHz), is a promising probe of the physical conditions of the intergalactic medium during Cosmic Dawn and the Epoch of Reionization (EoR). The sky-averaged H i signal is expected to be extremely weak (∼100 mK) in comparison to the Galactic foreground emission (∼10{sup 4} K). Moreover, the sky-averaged spectra measured by ground-based instruments are affected by chromatic propagation effects (∼tens of kelvin) originating in the ionosphere. We analyze data collected with the upgraded Broadband Instrument for Global Hydrogen Reionization Signal system deployed at the Murchison Radio-astronomy Observatory to assess the significance of ionospheric effects on the detection of the global EoR signal. The ionospheric effects identified in these data are, particularly during nighttime, dominated by absorption and emission. We measure some properties of the ionosphere, such as the electron temperature (T{sub e} ≈ 470 K at nighttime), magnitude, and variability of optical depth (τ{sub 100} {sub MHz} ≈ 0.01 and δτ ≈ 0.005 at nighttime). According to the results of a statistical test applied on a large data sample, very long integrations (∼100 hr collected over approximately 2 months) lead to increased signal-to-noise ratio even in the presence of ionospheric variability. This is further supported by the structure of the power spectrum of the sky temperature fluctuations, which has flicker noise characteristics at frequencies ≳10{sup −5} Hz, but becomes flat below ≈10{sup −5} Hz. Hence, we conclude that the stochastic error introduced by the chromatic ionospheric effects tends to zero in an average. Therefore, the ionospheric effects and fluctuations are not fundamental impediments preventing ground-based instruments from integrating down to the precision required by global EoR experiments, provided that the ionospheric contribution is properly accounted for in the data analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The adhesion model as a field theory for cosmological clustering

The adhesion model has been proposed in the past as an improvement of the Zel'dovich approximation, providing a good description of the formation of the cosmic web. We recast the model as a field theory for cosmological large scale structure, adding a stochastic force to account for power generated from very short, highly non-linear scales that is uncorrelated with the initial power spectrum. The dynamics of this Stochastic Adhesion Model (SAM) is reminiscent of the well known Kardar-Parisi-Zhang equation with the difference that the viscosity and the noise spectrum are time dependent. Choosing the viscosity proportional to the growth factor D restricts the form of noise spectrum through a 1-loop renormalization argument. For this choice, the SAM field theory is renormalizable to one loop. We comment on the suitability of this model for describing the non-linear regime of the CDM power spectrum and its utility as a relatively simple approach to cosmological clustering.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Consistency testing for robust phase estimation

In this work, we present an extension to the robust phase estimation protocol, which can identify incorrect results that would otherwise lie outside the expected statistical range. Robust phase estimation is increasingly a method of choice for applications such as estimating the effective process parameters of noisy hardware, but its robustness is dependent on the noise satisfying certain threshold assumptions. We provide consistency checks that can indicate when those thresholds have been violated, which can be difficult or impossible to test directly. We test these consistency checks for several common noise models, and identify two possible checks with high accuracy in locating the point in a robust phase estimation run at which further estimates should not be trusted. One of these checks may be chosen based on resource availability, or they can be used together in order to provide additional verification.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Capturing high‐resolution digital images for use in forensic document examination

Abstract In the past, pattern disciplines within forensic science have periodically faced criticism due to their subjective and qualitative nature and the perceived absence of research evaluating and supporting the foundations of their practices. Recently, however, forensic scientists and researchers in the field of pattern evidence analysis have developed and published approaches that are more quantitative, objective, and data driven. This effort includes automation, algorithms, and measurement sciences, with the end goal of enabling conclusions to be informed by quantitative models. Before employing these tools, forensic evidence must be digitized in a way that adequately balances high‐quality detail and content capture with minimal background noise imparted by the selected technique. While the current work describes the process of optimizing a method to digitize physical documentary evidence for use in semi‐automated trash mark examinations, it could be applied to assist other disciplines where the digitization of physical items of evidence is prevalent. For trash mark examinations specifically, it was found that high‐resolution photography provided optimal digital versions of evidentiary items when compared to high‐resolution scanning.

Riley, Paige↗
DOE OSTI2025

WaveDenoiser

We developed a robust deep learning model to effectively reduce background noise in the time domain from seismic waveforms. The deep learning model processes a 57-second three-component seismogram to predict and generate a denoised seismogram. The training was conducted using the benchmark STEAD dataset, which comprises globally distributed earthquake signals recorded at local distances ranging from 0 to 350 kilometers.

Chai, Chengping [Oak Ridge National Laboratory (OR↗
DOE OSTI2020

Mode locking in an optomechanical cavity

Here, we experimentally study a fiber-based optical ring cavity integrated with a mechanical resonator mirror and an optical amplifier. The device exhibits a variety of intriguing nonlinear effects including synchronization and self-excited oscillation. Passively generated optical pulses are observed when the frequency of the optical ring cavity is tuned very close to the mechanical frequency of the suspended mirror. The optical power at the threshold of this process of mechanical mode locking is found to be related to quantum noise of the optical amplifier.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Utah FORGE: Seismic Event Catalogue from the April, 2022 Stimulation of Well 16A(78)-32

This dataset includes earthquake catalogues for the three stages of the 2022 well 16A(78)-32 stimulation provided by Geo Energie Suisse. Events in these catalogues have been visually inspected. There are additional events of lower signal to noise that were automatically detected. Those events will require additional analysis and processing. Times are recorded in UTC (Coordinate Universal Time), and the coordinate reference system is UTM Zone 12N, NAD83.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Testing Paired Neural Network Models for Aftershock Identification

Aftershock sequences are a burden to real-time seismic monitoring. Cross-correlation can be used because aftershocks exhibit similar waveforms, but the method is computationally expensive. Deep learning may be an alternative, as it is computationally efficient, but great attention to training and testing is required in order to trust that the model can generalize to new aftershock sequences. This is problematic for aftershock sequences, because large-magnitude earthquakes are unpredictable and are globally widespread. Here, we test several paired neural network (PNN) models trained on a augmented (noise-added) earthquake dataset, to determine whether they can be generalized to process real aftershock sequences. Two aftershock datasets that were originally detected by cross-correlation and subsequently validated by an expert analyst were used. We found that current PNN models struggle to generalize to aftershock sequences. However, we identify approaches to improve training future PNN models and believe that improvements may be achieved by transfer learning.

58 GEOSCIENCES↗
DOE OSTI2025

AWAKEN Site A1 - NREL Scanning Lidar (Halo XR+ #235) / Processed Data

These data include raw scanning Doppler lidar measurements from the deployment of the NREL HALO XR+ (s/n 235) at the A1 site. The processed measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.

17 WIND ENERGY↗