Stochastic resonance and coherence resonance in groundwater-dependent plant ecosystems.

Science.gov (United States)

Borgogno, Fabio; D'Odorico, Paolo; Laio, Francesco; Ridolfi, Luca

2012-01-21

Several studies have shown that non-linear deterministic dynamical systems forced by external random components can give rise to unexpectedly regular temporal behaviors. Stochastic resonance and coherence resonance, the two best known processes of this type, have been studied in a number of physical and chemical systems. Here, we explore their possible occurrence in the dynamics of groundwater-dependent plant ecosystems. To this end, we develop two eco-hydrological models, which allow us to demonstrate that stochastic and coherence resonance may emerge in the dynamics of phreatophyte vegetation, depending on their deterministic properties and the intensity of external stochastic drivers. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

Energy Technology Data Exchange (ETDEWEB)

Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn; Deng, Bin; Wei, Xile [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

2014-09-01

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

International Nuclear Information System (INIS)

Yu, Haitao; Guo, Xinmeng; Wang, Jiang; Deng, Bin; Wei, Xile

2014-01-01

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks

Equilibrium and stochastic resonance in finite chains of noisy bistable elements

International Nuclear Information System (INIS)

Morillo, Manuel; Gomez-Ordonez, Jose; Casado, Jose Manuel

2010-01-01

Graphical abstract: We analyze the dependence of the equilibrium distribution of a collective variable of a chain on relevant parameters including the chain size and its connectivity. We also analyze the stochastic resonance effect of the same variable. - Abstract: Using numerical simulations, we analyze equilibrium properties of finite chains of coupled noisy bistable units and their response to weak time periodic forces. Finite chains with global as well as local (nearest neighbors) coupling are considered. We focus on the study of a collective variable defined as the arithmetic mean of the variables characterizing each element of the chain. By contrast with the case of infinite size chains, where the coexistence of several equilibrium distributions for the same values of parameters is possible, for finite chains just a single equilibrium distribution exists for given values of the parameters. We demonstrate that, regardless of the chain connectivity, there exist transition lines separating regions in parameter space where the equilibrium distribution function is either monomodal or multimodal. The location of the transition line depends on the chain connectivity and the size of the system. For driven chains, the response of the system shows stochastic resonant effects. For the two types of chains considered, both the power spectral amplification and the signal-to-noise ratio of the collective variable are analyzed as the noise strength, the coupling parameter and the number of bistable units in the system are varied. Compared with the effects observed in single unit systems, the collective variable shows a strong enhancement of the stochastic resonance effects.

Stochastic resonance driven by time-modulated correlated coloured noise sources in a single-mode laser

International Nuclear Information System (INIS)

De-Yi, Chen; Li, Zhang

2009-01-01

This paper investigates the phenomenon of stochastic resonance in a single-mode laser driven by time-modulated correlated coloured noise sources. The power spectrum and signal-to-noise ratio R of the laser intensity are calculated by the linear approximation. The effects caused by noise self-correlation time τ 1 , τ 2 and cross-correlated time τ 3 for stochastic resonance are analysed in two ways: τ 1 , τ 2 and τ 3 are taken to be the independent variables and the parameters respectively. The effects of the gain coefficient Γ and loss coefficient K on the stochastic resonance are also discussed. It is found that besides the presence of the standard form and the broad sense of stochastic resonance, the number of extrema in the curve of R versus K is reduced with the increase of the gain coefficient Γ

A simple parameter can switch between different weak-noise-induced phenomena in a simple neuron model

Science.gov (United States)

Yamakou, Marius E.; Jost, Jürgen

2017-10-01

In recent years, several, apparently quite different, weak-noise-induced resonance phenomena have been discovered. Here, we show that at least two of them, self-induced stochastic resonance (SISR) and inverse stochastic resonance (ISR), can be related by a simple parameter switch in one of the simplest models, the FitzHugh-Nagumo (FHN) neuron model. We consider a FHN model with a unique fixed point perturbed by synaptic noise. Depending on the stability of this fixed point and whether it is located to either the left or right of the fold point of the critical manifold, two distinct weak-noise-induced phenomena, either SISR or ISR, may emerge. SISR is more robust to parametric perturbations than ISR, and the coherent spike train generated by SISR is more robust than that generated deterministically. ISR also depends on the location of initial conditions and on the time-scale separation parameter of the model equation. Our results could also explain why real biological neurons having similar physiological features and synaptic inputs may encode very different information.

Stochastic Resonance in a System of Coupled Chaotic Oscillators

International Nuclear Information System (INIS)

Krawiecki, A.

1999-01-01

Noise-free stochastic resonance is investigated numerically in a system of two coupled chaotic Roessler oscillators. Periodic signal is applied either additively or multiplicatively to the coupling term. When the coupling constant is varied the oscillators lose synchronization via attractor bubbling or on-off intermittency. Properly chosen signals are analyzed which reflect the sequence of synchronized (laminar) phases and non-synchronized bursts in the time evolution of the oscillators. Maximum of the signal-to-noise ratio as a function of the coupling constant is observed. Dependence of the signal-to-noise ratio on the frequency of the periodic signal and parameter mismatch between the oscillators is investigated. Possible applications of stochastic resonance in the recovery of signals in secure communication systems based on chaotic synchronization are briefly discussed. (author)

Improved stochastic resonance algorithm for enhancement of signal-to-noise ratio of high-performance liquid chromatographic signal

International Nuclear Information System (INIS)

Xie Shaofei; Xiang Bingren; Deng Haishan; Xiang Suyun; Lu Jun

2007-01-01

Based on the theory of stochastic resonance, an improved stochastic resonance algorithm with a new criterion for optimizing system parameters to enhance signal-to-noise ratio (SNR) of HPLC/UV chromatographic signal for trace analysis was presented in this study. Compared with the conventional criterion in stochastic resonance, the proposed one can ensure satisfactory SNR as well as good peak shape of chromatographic peak in output signal. Application of the criterion to experimental weak signals of HPLC/UV was investigated and the results showed an excellent quantitative relationship between different concentrations and responses

Stochastic resonance in bistable systems driven by harmonic noise

International Nuclear Information System (INIS)

Neiman, A.; Schimansky-Geier, L.

1994-01-01

We study stochastic resonance in a bistable system which is excited simultaneously by white and harmonic noise which we understand as the signal. In our case the spectral line of the signal has a finite width as it occurs in many real situations. Using techniques of cumulant analysis as well as computer simulations we find that the effect of stochastic resonance is preserved in the case of harmonic noise excitation. Moreover we show that the width of the spectral line of the signal at the output can be decreased via stochastic resonance. The last could be of importance in the practical using of the stochastic resonance

Decoding suprathreshold stochastic resonance with optimal weights

International Nuclear Information System (INIS)

Xu, Liyan; Vladusich, Tony; Duan, Fabing; Gunn, Lachlan J.; Abbott, Derek; McDonnell, Mark D.

2015-01-01

We investigate an array of stochastic quantizers for converting an analog input signal into a discrete output in the context of suprathreshold stochastic resonance. A new optimal weighted decoding is considered for different threshold level distributions. We show that for particular noise levels and choices of the threshold levels optimally weighting the quantizer responses provides a reduced mean square error in comparison with the original unweighted array. However, there are also many parameter regions where the original array provides near optimal performance, and when this occurs, it offers a much simpler approach than optimally weighting each quantizer's response. - Highlights: • A weighted summing array of independently noisy binary comparators is investigated. • We present an optimal linearly weighted decoding scheme for combining the comparator responses. • We solve for the optimal weights by applying least squares regression to simulated data. • We find that the MSE distortion of weighting before summation is superior to unweighted summation of comparator responses. • For some parameter regions, the decrease in MSE distortion due to weighting is negligible

A study on stochastic resonance of one-dimensional bistable system in the neighborhood of bifurcation point with the moment method

Energy Technology Data Exchange (ETDEWEB)

Zhang Guangjun [State Key Laboratory of Mechanical Structural Strength and Vibration, School of Architectural Engineering and Mechanics, Xi' an Jiaotong University, Xi' an, Shaanxi (China); Xu Jianxue [State Key Laboratory of Mechanical Structural Strength and Vibration, School of Architectural Engineering and Mechanics, Xi' an Jiaotong University, Xi' an, Shaanxi (China)] e-mail: jxxu@mail.xjtu.edu.cn

2006-02-01

This paper analyzes the stochastic resonance induced by a novel transition of one-dimensional bistable system in the neighborhood of bifurcation point with the method of moment, which refer to the transition of system motion among a potential well of stable fixed point before bifurcation of original system and double-well potential of two coexisting stable fixed points after original system bifurcation at the presence of internal noise. The results show: the semi-analytical result of stochastic resonance of one-dimensional bistable system in the neighborhood of bifurcation point may be obtained, and the semi-analytical result is in accord with the one of Monte Carlo simulation qualitatively, the occurrence of stochastic resonance is related to the bifurcation of noisy nonlinear dynamical system moment equations, which induce the transfer of energy of ensemble average (Ex) of system response in each frequency component and make the energy of ensemble average of system response concentrate on the frequency of input signal, stochastic resonance occurs.

A study on stochastic resonance of one-dimensional bistable system in the neighborhood of bifurcation point with the moment method

International Nuclear Information System (INIS)

Zhang Guangjun; Xu Jianxue

2006-01-01

This paper analyzes the stochastic resonance induced by a novel transition of one-dimensional bistable system in the neighborhood of bifurcation point with the method of moment, which refer to the transition of system motion among a potential well of stable fixed point before bifurcation of original system and double-well potential of two coexisting stable fixed points after original system bifurcation at the presence of internal noise. The results show: the semi-analytical result of stochastic resonance of one-dimensional bistable system in the neighborhood of bifurcation point may be obtained, and the semi-analytical result is in accord with the one of Monte Carlo simulation qualitatively, the occurrence of stochastic resonance is related to the bifurcation of noisy nonlinear dynamical system moment equations, which induce the transfer of energy of ensemble average (Ex) of system response in each frequency component and make the energy of ensemble average of system response concentrate on the frequency of input signal, stochastic resonance occurs

Behavioral Stochastic Resonance

Science.gov (United States)

Freund, Jan A.; Schimansky-Geier, Lutz; Beisner, Beatrix; Neiman, Alexander; Russell, David F.; Yakusheva, Tatyana; Moss, Frank

2001-03-01

Zooplankton emit weak electric fields into the surrounding water that originate from their own muscular activities associated with swimming and feeding. Juvenile paddlefish prey upon single zooplankton by detecting and tracking these weak electric signatures. The passive electric sense in the fish is provided by an elaborate array of electroreceptors, Ampullae Lorenzini, spread over the surface of an elongated rostrum. We have previously shown that the fish use stochastic resonance to enhance prey capture near the detection threshold of their sensory system. But stochastic resonance requires an external source of electrical noise in order to function. The required noise can be provided by a swarm of plankton, for example Daphnia. Thus juvenile paddlefish can detect and attack single Daphnia as outliers in the vicinity of the swarm by making use of noise from the swarm itself. From the power spectral density of the noise plus the weak signal from a single Daphnia we calculate the signal-to-noise ratio and the Fisher information at the surface of the paddlefish's rostrum. The results predict a specific attack pattern for the paddlefish that appears to be experimentally testable.

The research status and development trend of stochastic resonance

Science.gov (United States)

Xu, Lei; Peng, Yueping; Liu, Man

2017-12-01

The synergistic reaction under specific conditions of the nonlinear system, weak driving signal and moderate noise can make noise to be advantageous in a certain extent, so as to achieve the purpose of signal enhancement, this seemingly anomalous phenomenon is defined as stochastic resonance. In this paper, the weak signal detection under strong noise background is the main line. The principle of white noise to counteract external noise is expounded, and the present research situation and development trend of stochastic resonance are reviewed in that paper, it also pointed out the direction of further research of stochastic resonance technology.

Stochastic resonance in a delayed triple-well potential driven by correlated noises.

Science.gov (United States)

Xu, Pengfei; Jin, Yanfei; Xiao, Shaomin

2017-11-01

In this paper, we investigate stochastic resonance (SR) in a delayed triple-well potential subject to correlated noises and a harmonic signal. The stationary probability density, together with the response amplitude of the system, is obtained by using the small time delay approximation. It is found that the time delay, noise intensities, and the cross-correlation between noises can induce the occurrence of the transition. Moreover, the appropriate choice of noise intensities and time delay can improve the output of the system, enhance the SR effect, and lead to the phenomenon of noise enhanced stability. Especially, the stochastic multi-resonance phenomenon is observed when the multiplicative and additive noises are correlated. Finally, the theoretical results are well verified through numerical simulations.

Stochastic charging of dust grains in planetary rings: Diffusion rates and their effects on Lorentz resonances

Science.gov (United States)

Schaffer, L.; Burns, J. A.

1995-01-01

Dust grains in planetary rings acquire stochastically fluctuating electric charges as they orbit through any corotating magnetospheric plasma. Here we investigate the nature of this stochastic charging and calculate its effect on the Lorentz resonance (LR). First we model grain charging as a Markov process, where the transition probabilities are identified as the ensemble-averaged charging fluxes due to plasma pickup and photoemission. We determine the distribution function P(t;N), giving the probability that a grain has N excess charges at time t. The autocorrelation function tau(sub q) for the strochastic charge process can be approximated by a Fokker-Planck treatment of the evolution equations for P(t; N). We calculate the mean square response to the stochastic fluctuations in the Lorentz force. We find that transport in phase space is very small compared to the resonant increase in amplitudes due to the mean charge, over the timescale that the oscillator is resonantly pumped up. Therefore the stochastic charge variations cannot break the resonant interaction; locally, the Lorentz resonance is a robust mechanism for the shaping of etheral dust ring systems. Slightly stronger bounds on plasma parameters are required when we consider the longer transit times between Lorentz resonances.

Stochastic resonance in small-world neuronal networks with hybrid electrical–chemical synapses

International Nuclear Information System (INIS)

Wang, Jiang; Guo, Xinmeng; Yu, Haitao; Liu, Chen; Deng, Bin; Wei, Xile; Chen, Yingyuan

2014-01-01

Highlights: •We study stochastic resonance in small-world neural networks with hybrid synapses. •The resonance effect depends largely on the probability of chemical synapse. •An optimal chemical synapse probability exists to evoke network resonance. •Network topology affects the stochastic resonance in hybrid neuronal networks. - Abstract: The dependence of stochastic resonance in small-world neuronal networks with hybrid electrical–chemical synapses on the probability of chemical synapse and the rewiring probability is investigated. A subthreshold periodic signal is imposed on one single neuron within the neuronal network as a pacemaker. It is shown that, irrespective of the probability of chemical synapse, there exists a moderate intensity of external noise optimizing the response of neuronal networks to the pacemaker. Moreover, the effect of pacemaker driven stochastic resonance of the system depends largely on the probability of chemical synapse. A high probability of chemical synapse will need lower noise intensity to evoke the phenomenon of stochastic resonance in the networked neuronal systems. In addition, for fixed noise intensity, there is an optimal chemical synapse probability, which can promote the propagation of the localized subthreshold pacemaker across neural networks. And the optimal chemical synapses probability turns even larger as the coupling strength decreases. Furthermore, the small-world topology has a significant impact on the stochastic resonance in hybrid neuronal networks. It is found that increasing the rewiring probability can always enhance the stochastic resonance until it approaches the random network limit

On square-wave-driven stochastic resonance for energy harvesting in a bistable system

Energy Technology Data Exchange (ETDEWEB)

Su, Dongxu, E-mail: sudx@iis.u-tokyo.ac.jp [Graduate School of Engineering, The University of Tokyo, Tokyo 1538505 (Japan); Zheng, Rencheng; Nakano, Kimihiko [Institute of Industrial Science, The University of Tokyo, Tokyo 1538505 (Japan); Cartmell, Matthew P [Department of Mechanical Engineering, University of Sheffield, Sheffield S1 3JD (United Kingdom)

2014-11-15

Stochastic resonance is a physical phenomenon through which the throughput of energy within an oscillator excited by a stochastic source can be boosted by adding a small modulating excitation. This study investigates the feasibility of implementing square-wave-driven stochastic resonance to enhance energy harvesting. The motivating hypothesis was that such stochastic resonance can be efficiently realized in a bistable mechanism. However, the condition for the occurrence of stochastic resonance is conventionally defined by the Kramers rate. This definition is inadequate because of the necessity and difficulty in estimating white noise density. A bistable mechanism has been designed using an explicit analytical model which implies a new approach for achieving stochastic resonance in the paper. Experimental tests confirm that the addition of a small-scale force to the bistable system excited by a random signal apparently leads to a corresponding amplification of the response that we now term square-wave-driven stochastic resonance. The study therefore indicates that this approach may be a promising way to improve the performance of an energy harvester under certain forms of random excitation.

On square-wave-driven stochastic resonance for energy harvesting in a bistable system

International Nuclear Information System (INIS)

Su, Dongxu; Zheng, Rencheng; Nakano, Kimihiko; Cartmell, Matthew P

2014-01-01

Stochastic resonance is a physical phenomenon through which the throughput of energy within an oscillator excited by a stochastic source can be boosted by adding a small modulating excitation. This study investigates the feasibility of implementing square-wave-driven stochastic resonance to enhance energy harvesting. The motivating hypothesis was that such stochastic resonance can be efficiently realized in a bistable mechanism. However, the condition for the occurrence of stochastic resonance is conventionally defined by the Kramers rate. This definition is inadequate because of the necessity and difficulty in estimating white noise density. A bistable mechanism has been designed using an explicit analytical model which implies a new approach for achieving stochastic resonance in the paper. Experimental tests confirm that the addition of a small-scale force to the bistable system excited by a random signal apparently leads to a corresponding amplification of the response that we now term square-wave-driven stochastic resonance. The study therefore indicates that this approach may be a promising way to improve the performance of an energy harvester under certain forms of random excitation

Stochastic resonance a mathematical approach in the small noise limit

CERN Document Server

Herrmann, Samuel; Pavlyukevich, Ilya; Peithmann, Dierk

2013-01-01

Stochastic resonance is a phenomenon arising in a wide spectrum of areas in the sciences ranging from physics through neuroscience to chemistry and biology. This book presents a mathematical approach to stochastic resonance which is based on a large deviations principle (LDP) for randomly perturbed dynamical systems with a weak inhomogeneity given by an exogenous periodicity of small frequency. Resonance, the optimal tuning between period length and noise amplitude, is explained by optimizing the LDP's rate function. The authors show that not all physical measures of tuning quality are robust with respect to dimension reduction. They propose measures of tuning quality based on exponential transition rates explained by large deviations techniques and show that these measures are robust. The book sheds some light on the shortcomings and strengths of different concepts used in the theory and applications of stochastic resonance without attempting to give a comprehensive overview of the many facets of stochastic ...

Stochastic Resonance in Neuronal Network Motifs with Ornstein-Uhlenbeck Colored Noise

Directory of Open Access Journals (Sweden)

Xuyang Lou

2014-01-01

Full Text Available We consider here the effect of the Ornstein-Uhlenbeck colored noise on the stochastic resonance of the feed-forward-loop (FFL network motif. The FFL motif is modeled through the FitzHugh-Nagumo neuron model as well as the chemical coupling. Our results show that the noise intensity and the correlation time of the noise process serve as the control parameters, which have great impacts on the stochastic dynamics of the FFL motif. We find that, with a proper choice of noise intensities and the correlation time of the noise process, the signal-to-noise ratio (SNR can display more than one peak.

Single-Molecule Stochastic Resonance

Directory of Open Access Journals (Sweden)

K. Hayashi

2012-08-01

Full Text Available Stochastic resonance (SR is a well-known phenomenon in dynamical systems. It consists of the amplification and optimization of the response of a system assisted by stochastic (random or probabilistic noise. Here we carry out the first experimental study of SR in single DNA hairpins which exhibit cooperatively transitions from folded to unfolded configurations under the action of an oscillating mechanical force applied with optical tweezers. By varying the frequency of the force oscillation, we investigate the folding and unfolding kinetics of DNA hairpins in a periodically driven bistable free-energy potential. We measure several SR quantifiers under varied conditions of the experimental setup such as trap stiffness and length of the molecular handles used for single-molecule manipulation. We find that a good quantifier of the SR is the signal-to-noise ratio (SNR of the spectral density of measured fluctuations in molecular extension of the DNA hairpins. The frequency dependence of the SNR exhibits a peak at a frequency value given by the resonance-matching condition. Finally, we carry out experiments on short hairpins that show how SR might be useful for enhancing the detection of conformational molecular transitions of low SNR.

Noise transmission and delay-induced stochastic oscillations in biochemical network motifs

International Nuclear Information System (INIS)

Liu Sheng-Jun; Wang Qi; Liu Bo; Yan Shi-Wei; Sakata Fumihiko

2011-01-01

With the aid of stochastic delayed-feedback differential equations, we derive an analytic expression for the power spectra of reacting molecules included in a generic biological network motif that is incorporated with a feedback mechanism and time delays in gene regulation. We systematically analyse the effects of time delays, the feedback mechanism, and biological stochasticity on the power spectra. It has been clarified that the time delays together with the feedback mechanism can induce stochastic oscillations at the molecular level and invalidate the noise addition rule for a modular description of the noise propagator. Delay-induced stochastic resonance can be expected, which is related to the stability loss of the reaction systems and Hopf bifurcation occurring for solutions of the corresponding deterministic reaction equations. Through the analysis of the power spectrum, a new approach is proposed to estimate the oscillation period. (interdisciplinary physics and related areas of science and technology)

Effect of the Potential Shape on the Stochastic Resonance Processes

Science.gov (United States)

Kenmoé, G. Djuidjé; Ngouongo, Y. J. Wadop; Kofané, T. C.

2015-10-01

The stochastic resonance (SR) induced by periodic signal and white noises in a periodic nonsinusoidal potential is investigated. This phenomenon is studied as a function of the friction coefficient as well as the shape of the potential. It is done through an investigation of the hysteresis loop area which is equivalent to the input energy lost by the system to the environment per period of the external force. SR is evident in some range of the shape parameter of the potential, but cannot be observed in the other range. Specially, variation of the shape potential affects significantly and not trivially the heigh of the potential barrier in the Kramers rate as well as the occurrence of SR. The finding results show crucial dependence of the temperature of occurrence of SR on the shape of the potential. It is noted that the maximum of the input energy generally decreases when the friction coefficient is increased.

Optimization of input parameters of supra-threshold stochastic resonance image processing algorithm for the detection of abdomino-pelvic tumors on PET/CT scan

International Nuclear Information System (INIS)

Pandey, Anil Kumar; Saroha, Kartik; Patel, C.D.; Bal, C.S.; Kumar, Rakesh

2016-01-01

Administration of diuretics increases the urine output to clear radioactive urine from kidneys and bladder. Hence post-diuretic pelvic PET/CT scan enhances the probability of detection of abdomino-pelvic tumor. However, it causes discomfort in patients and has some side effects also. Application of supra threshold stochastic resonance (SSR) image processing algorithm on Pre-diuretic PET/CT scan may also increase the probability of detection of these tumors. Amount of noise and threshold are two variable parameters that effect the final image quality. This study was conducted to investigate the effect of these two variable parameters on the detection of abdomen-pelvic tumor

Constructive role of Brownian motion: Brownian motors and Stochastic Resonance

Science.gov (United States)

Hänggi, Peter

2005-03-01

Noise is usually thought of as the enemy of order rather as a constructive influence. For the phenomena of Stochastic Resonance [1] and Brownian motors [2], however, stochastic noise can play a beneficial role in enhancing detection and/or facilitating directed transmission of information in absence of biasing forces. Brownian motion assisted Stochastic Resonance finds useful applications in physical, technological, biological and biomedical contexts [1,3]. The basic principles that underpin Stochastic Resonance are elucidated and novel applications for nonlinear classical and quantum systems will be addressed. The presence of non-equilibrium disturbances enables to rectify Brownian motion so that quantum and classical objects can be directed around on a priori designed routes in biological and physical systems (Brownian motors). In doing so, the energy from the haphazard motion of (quantum) Brownian particles is extracted to perform useful work against an external load. This very concept together with first experimental realizations are discussed [2,4,5]. [1] L. Gammaitoni, P. Hä'nggi, P. Jung and F. Marchesoni, Stochastic Resonance, Rev. Mod. Phys. 70, 223 (1998).[2] R. D. Astumian and P. Hä'nggi, Brownian motors, Physics Today 55 (11), 33 (2002).[3] P. Hä'nggi, Stochastic Resonace in Physics and Biology, ChemPhysChem 3, 285 (2002).[4] H. Linke, editor, Special Issue on Brownian Motors, Applied Physics A 75, No. 2 (2002).[5] P. Hä'nggi, F. Marchesoni, F. Nori, Brownian motors, Ann. Physik (Leipzig) 14, xxx (2004); cond-mat/0410033.

Frequency-difference-dependent stochastic resonance in neural systems

Science.gov (United States)

Guo, Daqing; Perc, Matjaž; Zhang, Yangsong; Xu, Peng; Yao, Dezhong

2017-08-01

Biological neurons receive multiple noisy oscillatory signals, and their dynamical response to the superposition of these signals is of fundamental importance for information processing in the brain. Here we study the response of neural systems to the weak envelope modulation signal, which is superimposed by two periodic signals with different frequencies. We show that stochastic resonance occurs at the beat frequency in neural systems at the single-neuron as well as the population level. The performance of this frequency-difference-dependent stochastic resonance is influenced by both the beat frequency and the two forcing frequencies. Compared to a single neuron, a population of neurons is more efficient in detecting the information carried by the weak envelope modulation signal at the beat frequency. Furthermore, an appropriate fine-tuning of the excitation-inhibition balance can further optimize the response of a neural ensemble to the superimposed signal. Our results thus introduce and provide insights into the generation and modulation mechanism of the frequency-difference-dependent stochastic resonance in neural systems.

Stochastic phenomena in a fiber Raman amplifier

Energy Technology Data Exchange (ETDEWEB)

Kalashnikov, Vladimir [Aston Institute of Photonic Technologies, Aston University, Birmingham (United Kingdom); Institute of Photonics, Vienna University of Technology (Austria); Sergeyev, Sergey V. [Aston Institute of Photonic Technologies, Aston University, Birmingham (United Kingdom); Ania-Castanon, Juan Diego [Instituto de Optica CSIC, Madrid (Spain); Jacobsen, Gunnar [Acreo, Kista (Sweden); Popov, Sergei [Royal Institute of Technology (KTH), Stockholm (Sweden)

2017-01-15

The interplay of such cornerstones of modern nonlinear fiber optics as a nonlinearity, stochasticity and polarization leads to variety of the noise induced instabilities including polarization attraction and escape phenomena harnessing of which is a key to unlocking the fiber optic systems specifications required in high resolution spectroscopy, metrology, biomedicine and telecommunications. Here, by using direct stochastic modeling, the mapping of interplay of the Raman scattering-based nonlinearity, the random birefringence of a fiber, and the pump-to-signal intensity noise transfer has been done in terms of the fiber Raman amplifier parameters, namely polarization mode dispersion, the relative intensity noise of the pump laser, fiber length, and the signal power. The obtained results reveal conditions for emergence of the random birefringence-induced resonance-like enhancement of the gain fluctuations (stochastic anti-resonance) accompanied by pulse broadening and rare events in the form of low power output signals having probability heavily deviated from the Gaussian distribution. (copyright 2016 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Logical stochastic resonance in triple-well potential systems driven by colored noise.

Science.gov (United States)

Zhang, Huiqing; Xu, Yong; Xu, Wei; Li, Xiuchun

2012-12-01

In this work, the logic stochastic resonance (LSR) phenomenon in a class of stochastic triple-well potential systems is investigated. Approximate Fokker-Planck equation is first obtained by using decoupling approximation. Then, we show that LSR can be successfully induced by additive or multiplicative Gaussian colored noise in some cases. In the absence of internal noise, LSR implementation seems impossible for a = 0 (The parameter a characterizes the depth of the potential well) since the two side wells are so deep that the particle cannot hop over the barrier into the middle well when the input signal is 0. With the increasing of a, the optimal noise band to yield flexible logic gates appears and moves to higher level of noise as the correlation time of noise increases. Compared with the Gaussian white noise, the reliable region in the parameter plane of potential depth parameter a and additive noise strength D first expands and then shrinks with increasing noise color. Furthermore, the effects of multiplicative Gaussian colored noise on LSR are investigated. It was found that the flexible and reliable logic behavior can be yielded for a = 0 due to the fact that the multiplicative Gaussian colored noise strongly affects the shape of the potential function. With the increasing of a, i.e., a = 0.25, multiplicative Gaussian white noise cannot yield desired logic behavior. Fortunately, LSR can also be expected by adjusting the correlation time of Gaussian colored noise. It can also be observed that the reliable region in the parameter plane of potential depth parameter a and multiplicative noise strength Q is small for the case of Gaussian white noise and it becomes larger with the increasing of noise color.

Lévy stable noise-induced transitions: stochastic resonance, resonant activation and dynamic hysteresis

International Nuclear Information System (INIS)

Dybiec, Bartłomiej; Gudowska-Nowak, Ewa

2009-01-01

A standard approach to analysis of noise-induced effects in stochastic dynamics assumes a Gaussian character of the noise term describing interaction of the analyzed system with its complex surroundings. An additional assumption about the existence of timescale separation between the dynamics of the measured observable and the typical timescale of the noise allows external fluctuations to be modeled as temporally uncorrelated and therefore white. However, in many natural phenomena the assumptions concerning the above mentioned properties of 'Gaussianity' and 'whiteness' of the noise can be violated. In this context, in contrast to the spatiotemporal coupling characterizing general forms of non-Markovian or semi-Markovian Lévy walks, so called Lévy flights correspond to the class of Markov processes which can still be interpreted as white, but distributed according to a more general, infinitely divisible, stable and non-Gaussian law. Lévy noise-driven non-equilibrium systems are known to manifest interesting physical properties and have been addressed in various scenarios of physical transport exhibiting a superdiffusive behavior. Here we present a brief overview of our recent investigations aimed at understanding features of stochastic dynamics under the influence of Lévy white noise perturbations. We find that the archetypal phenomena of noise-induced ordering are robust and can be detected also in systems driven by memoryless, non-Gaussian, heavy-tailed fluctuations with infinite variance

Inverse stochastic resonance induced by synaptic background activity with unreliable synapses

Energy Technology Data Exchange (ETDEWEB)

Uzuntarla, Muhammet, E-mail: muzuntarla@yahoo.com

2013-11-15

Inverse stochastic resonance (ISR) is a recently pronounced phenomenon that is the minimum occurrence in mean firing rate of a rhythmically firing neuron as noise level varies. Here, by using a realistic modeling approach for the noise, we investigate the ISR with concrete biophysical mechanisms. It is shown that mean firing rate of a single neuron subjected to synaptic bombardment exhibits a minimum as the spike transmission probability varies. We also demonstrate that the occurrence of ISR strongly depends on the synaptic input regime, where it is most prominent in the balanced state of excitatory and inhibitory inputs.

Stochastic resonance and stability for a stochastic metapopulation system subjected to non-Gaussian noise and multiplicative periodic signal

International Nuclear Information System (INIS)

Kang-Kang, Wang; Xian-Bin, Liu; Yu, Zhou

2015-01-01

In this paper, the stability and stochastic resonance (SR) phenomenon induced by the multiplicative periodic signal for a metapopulation system driven by the additive Gaussian noise, multiplicative non-Gaussian noise and noise correlation time is investigated. By using the fast descent method, unified colored noise approximation and McNamara and Wiesenfeld’s SR theory, the analytical expressions of the stationary probability distribution function and signal-to-noise ratio (SNR) are derived in the adiabatic limit. Via numerical calculations, each effect of the addictive noise intensity, the multiplicative noise intensity and the correlation time upon the steady state probability distribution function and the SNR is discussed, respectively. It is shown that multiplicative, additive noises and the departure parameter from the Gaussian noise can all destroy the stability of the population system. However, the noise correlation time can consolidate the stability of the system. On the other hand, the correlation time always plays an important role in motivating the SR and enhancing the SNR. Under different parameter conditions of the system, the multiplicative, additive noises and the departure parameter can not only excite SR phenomenon, but also restrain the SR phenomenon, which demonstrates the complexity of different noises upon the nonlinear system. (paper)

Long-Time Dynamic Response and Stochastic Resonance of Subdiffusive Overdamped Bistable Fractional Fokker-Planck Systems

International Nuclear Information System (INIS)

Yan-Mei, Kang; Yao-Lin, Jiang

2008-01-01

To explore the influence of anomalous diffusion on stochastic resonance (SR) more deeply and effectively, the method of moments is extended to subdiffusive overdamped bistable fractional Fokker-Planck systems for calculating the long-time linear dynamic response. It is found that the method of moments attains high accuracy with the truncation order N = 10, and in normal diffusion such obtained spectral amplification factor (SAF) of the first-order harmonic is also confirmed by stochastic simulation. Observing the SAF of the odd-order harmonics we find some interesting results, i.e. for smaller driving frequency the decrease of sub diffusion exponent inhibits the stochastic resonance (SR), while for larger driving frequency the decrease of sub diffusion exponent enhances the second SR peak, but the first one vanishes and a double SR is induced in the third-order harmonic at the same time. These observations suggest that the anomalous diffusion has important influence on the bistable dynamics

Adaptive logical stochastic resonance in time-delayed synthetic genetic networks

Science.gov (United States)

Zhang, Lei; Zheng, Wenbin; Song, Aiguo

2018-04-01

In the paper, the concept of logical stochastic resonance is applied to implement logic operation and latch operation in time-delayed synthetic genetic networks derived from a bacteriophage λ. Clear logic operation and latch operation can be obtained when the network is tuned by modulated periodic force and time-delay. In contrast with the previous synthetic genetic networks based on logical stochastic resonance, the proposed system has two advantages. On one hand, adding modulated periodic force to the background noise can increase the length of the optimal noise plateau of obtaining desired logic response and make the system adapt to varying noise intensity. On the other hand, tuning time-delay can extend the optimal noise plateau to larger range. The result provides possible help for designing new genetic regulatory networks paradigm based on logical stochastic resonance.

Inverse stochastic resonance in networks of spiking neurons.

Science.gov (United States)

Uzuntarla, Muhammet; Barreto, Ernest; Torres, Joaquin J

2017-07-01

Inverse Stochastic Resonance (ISR) is a phenomenon in which the average spiking rate of a neuron exhibits a minimum with respect to noise. ISR has been studied in individual neurons, but here, we investigate ISR in scale-free networks, where the average spiking rate is calculated over the neuronal population. We use Hodgkin-Huxley model neurons with channel noise (i.e., stochastic gating variable dynamics), and the network connectivity is implemented via electrical or chemical connections (i.e., gap junctions or excitatory/inhibitory synapses). We find that the emergence of ISR depends on the interplay between each neuron's intrinsic dynamical structure, channel noise, and network inputs, where the latter in turn depend on network structure parameters. We observe that with weak gap junction or excitatory synaptic coupling, network heterogeneity and sparseness tend to favor the emergence of ISR. With inhibitory coupling, ISR is quite robust. We also identify dynamical mechanisms that underlie various features of this ISR behavior. Our results suggest possible ways of experimentally observing ISR in actual neuronal systems.

Encoding efficiency of suprathreshold stochastic resonance on stimulus-specific information

Energy Technology Data Exchange (ETDEWEB)

Duan, Fabing, E-mail: fabing.duan@gmail.com [Institute of Complexity Science, Qingdao University, Qingdao 266071 (China); Chapeau-Blondeau, François, E-mail: chapeau@univ-angers.fr [Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d' Angers, 62 avenue Notre Dame du Lac, 49000 Angers (France); Abbott, Derek, E-mail: derek.abbott@adelaide.edu.au [Centre for Biomedical Engineering (CBME) and School of Electrical & Electronic Engineering, The University of Adelaide, Adelaide, SA 5005 (Australia)

2016-01-08

In this paper, we evaluate the encoding efficiency of suprathreshold stochastic resonance (SSR) based on a local information-theoretic measure of stimulus-specific information (SSI), which is the average specific information of responses associated with a particular stimulus. The theoretical and numerical analyses of SSIs reveal that noise can improve neuronal coding efficiency for a large population of neurons, which leads to produce increased information-rich responses. The SSI measure, in contrast to the global measure of average mutual information, can characterize the noise benefits in finer detail for describing the enhancement of neuronal encoding efficiency of a particular stimulus, which may be of general utility in the design and implementation of a SSR coding scheme. - Highlights: • Evaluating the noise-enhanced encoding efficiency via stimulus-specific information. • New form of stochastic resonance based on the measure of encoding efficiency. • Analyzing neural encoding schemes from suprathreshold stochastic resonance detailedly.

Periodic modulation-based stochastic resonance algorithm applied to quantitative analysis for weak liquid chromatography-mass spectrometry signal of granisetron in plasma

Science.gov (United States)

Xiang, Suyun; Wang, Wei; Xiang, Bingren; Deng, Haishan; Xie, Shaofei

2007-05-01

The periodic modulation-based stochastic resonance algorithm (PSRA) was used to amplify and detect the weak liquid chromatography-mass spectrometry (LC-MS) signal of granisetron in plasma. In the algorithm, the stochastic resonance (SR) was achieved by introducing an external periodic force to the nonlinear system. The optimization of parameters was carried out in two steps to give attention to both the signal-to-noise ratio (S/N) and the peak shape of output signal. By applying PSRA with the optimized parameters, the signal-to-noise ratio of LC-MS peak was enhanced significantly and distorted peak shape that often appeared in the traditional stochastic resonance algorithm was corrected by the added periodic force. Using the signals enhanced by PSRA, this method extended the limit of detection (LOD) and limit of quantification (LOQ) of granisetron in plasma from 0.05 and 0.2 ng/mL, respectively, to 0.01 and 0.02 ng/mL, and exhibited good linearity, accuracy and precision, which ensure accurate determination of the target analyte.

Stochastic resonance based on modulation instability in spatiotemporal chaos.

Science.gov (United States)

Han, Jing; Liu, Hongjun; Huang, Nan; Wang, Zhaolu

2017-04-03

A novel dynamic of stochastic resonance in spatiotemporal chaos is presented, which is based on modulation instability of perturbed partially coherent wave. The noise immunity of chaos can be reinforced through this effect and used to restore the coherent signal information buried in chaotic perturbation. A theoretical model with fluctuations term is derived from the complex Ginzburg-Landau equation via Wigner transform. It shows that through weakening the nonlinear threshold and triggering energy redistribution, the coherent component dominates the instability damped by incoherent component. The spatiotemporal output showing the properties of stochastic resonance may provide a potential application of signal encryption and restoration.

Stochastic resonance in a generalized Von Foerster population growth model

Energy Technology Data Exchange (ETDEWEB)

Lumi, N.; Mankin, R. [Institute of Mathematics and Natural Sciences, Tallinn University, 25 Narva Road, 10120 Tallinn (Estonia)

2014-11-12

The stochastic dynamics of a population growth model, similar to the Von Foerster model for human population, is studied. The influence of fluctuating environment on the carrying capacity is modeled as a multiplicative dichotomous noise. It is established that an interplay between nonlinearity and environmental fluctuations can cause single unidirectional discontinuous transitions of the mean population size versus the noise amplitude, i.e., an increase of noise amplitude can induce a jump from a state with a moderate number of individuals to that with a very large number, while by decreasing the noise amplitude an opposite transition cannot be effected. An analytical expression of the mean escape time for such transitions is found. Particularly, it is shown that the mean transition time exhibits a strong minimum at intermediate values of noise correlation time, i.e., the phenomenon of stochastic resonance occurs. Applications of the results in ecology are also discussed.

Sensitivity of Footbridge Vibrations to Stochastic Walking Parameters

DEFF Research Database (Denmark)

Pedersen, Lars; Frier, Christian

2010-01-01

of the pedestrian. A stochastic modelling approach is adopted for this paper and it facilitates quantifying the probability of exceeding various vibration levels, which is useful in a discussion of serviceability of a footbridge design. However, estimates of statistical distributions of footbridge vibration levels...... to walking loads might be influenced by the models assumed for the parameters of the load model (the walking parameters). The paper explores how sensitive estimates of the statistical distribution of vertical footbridge response are to various stochastic assumptions for the walking parameters. The basis...... for the study is a literature review identifying different suggestions as to how the stochastic nature of these parameters may be modelled, and a parameter study examines how the different models influence estimates of the statistical distribution of footbridge vibrations. By neglecting scatter in some...

Stochastic resonance in a time-delayed asymmetric bistable system with mixed periodic signal

International Nuclear Information System (INIS)

Yong-Feng, Guo; Wei, Xu; Liang, Wang

2010-01-01

This paper studies the phenomenon of stochastic resonance in an asymmetric bistable system with time-delayed feedback and mixed periodic signal by using the theory of signal-to-noise ratio in the adiabatic limit. A general approximate Fokker–Planck equation and the expression of the signal-to-noise ratio are derived through the small time delay approximation at both fundamental harmonics and mixed harmonics. The effects of the additive noise intensity Q, multiplicative noise intensity D, static asymmetry r and delay time τ on the signal-to-noise ratio are discussed. It is found that the higher mixed harmonics and the static asymmetry r can restrain stochastic resonance, and the delay time τ can enhance stochastic resonance. Moreover, the longer the delay time τ is, the larger the additive noise intensity Q and the multiplicative noise intensity D are, when the stochastic resonance appears. (general)

Parameter Diversity Induced Multiple Spatial Coherence Resonances and Spiral Waves in Neuronal Network with and Without Noise

International Nuclear Information System (INIS)

Li Yuye; Jia Bing; Gu Huaguang; An Shucheng

2012-01-01

Diversity in the neurons and noise are inevitable in the real neuronal network. In this paper, parameter diversity induced spiral waves and multiple spatial coherence resonances in a two-dimensional neuronal network without or with noise are simulated. The relationship between the multiple resonances and the multiple transitions between patterns of spiral waves are identified. The coherence degrees induced by the diversity are suppressed when noise is introduced and noise density is increased. The results suggest that natural nervous system might profit from both parameter diversity and noise, provided a possible approach to control formation and transition of spiral wave by the cooperation between the diversity and noise. (general)

Consistent Stochastic Modelling of Meteocean Design Parameters

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Sterndorff, M. J.

2000-01-01

Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...

Stochasticity of the energy absorption in the electron cyclotron resonance

International Nuclear Information System (INIS)

Gutierrez T, C.; Hernandez A, O.

1998-01-01

The energy absorption mechanism in cyclotron resonance of the electrons is a present problem, since it could be considered from the stochastic point of view or this related with a non-homogeneous but periodical of plasma spatial structure. In this work using the Bogoliubov average method for a multi periodical system in presence of resonances, the drift equations were obtained in presence of a RF field for the case of electron cyclotron resonance until first order terms with respect to inverse of its cyclotron frequency. The absorbed energy equation is obtained on part of electrons in a simple model and by drift method. It is showed the stochastic character of the energy absorption. (Author)

Stochastic heating in the cyclotron resonance of electrons

International Nuclear Information System (INIS)

Gutierrez T, C.; Hernandez A, O.

1999-01-01

The study of the different schemes of plasma heating by radiofrequency waves is a very actual problem related with the plasma heating in different machines and the particle acceleration mechanisms. In this work, it is obtained the expression for the temporal evolution of the energy absorbed in the cyclotron resonance of electrons where it is showed the stochastic character of the energy absorption. It is obtained the stochastic criteria in a magnetic configuration of an Ecr type plasma source. (Author)

Manipulating potential wells in Logical Stochastic Resonance to obtain XOR logic

International Nuclear Information System (INIS)

Storni, Remo; Ando, Hiroyasu; Aihara, Kazuyuki; Murali, K.; Sinha, Sudeshna

2012-01-01

Logical Stochastic Resonance (LSR) is the application of Stochastic Resonance to logic computation, namely the phenomenon where a nonlinear system driven by weak signals representing logic inputs, under optimal noise, can yield logic outputs. We extend the existing results, obtained in the context of bistable systems, to multi-stable dynamical systems, allowing us to obtain XOR logic, in addition to the AND (NAND) and OR (NOR) logic observed in earlier studies. This strategy widens the scope of LSR from the application point of view, as XOR forms the basis of ubiquitous bit-by-bit addition, and conceptually, showing the ability to yield non-monotonic input–output logic associations. -- Highlights: ► We generalize Logical Stochastic Resonance from bistable to multi-stable systems. ► We propose a tristable dynamical system formed of piecewise linear functions. ► The system can correctly reproduce XOR logic behavior using the LSR principle. ► The system yields different logic behavior without the need to change the dynamics.

Spatiotemporal Stochastic Resonance:Theory and Experiment

Science.gov (United States)

Peter, Jung

1996-03-01

The amplification of weak periodic signals in bistable or excitable systems via stochastic resonance has been studied intensively over the last years. We are going one step further and ask: Can noise enhance spatiotemporal patterns in excitable media and can this effect be observed in nature? To this end, we are looking at large, two dimensional arrays of coupled excitable elements. Due to the coupling, excitation can propagate through the array in form of nonlinear waves. We observe target waves, rotating spiral waves and other wave forms. If the coupling between the elements is below a critical threshold, any excitational pattern will die out in the absence of noise. Below this threshold, large scale rotating spiral waves - as they are observed above threshold - can be maintained by a proper level of the noise[1]. Furthermore, their geometric features, such as the curvature can be controlled by the homogeneous noise level[2]. If the noise level is too large, break up of spiral waves and collisions with spontaneously nucleated waves yields spiral turbulence. Driving our array with a spatiotemporal pattern, e.g. a rotating spiral wave, we show that for weak coupling the excitational response of the array shows stochastic resonance - an effect we have termed spatiotemporal stochastic resonance. In the last part of the talk I'll make contact with calcium waves, observed in astrocyte cultures and hippocampus slices[3]. A. Cornell-Bell and collaborators[3] have pointed out the role of calcium waves for long-range glial signaling. We demonstrate the similarity of calcium waves with nonlinear waves in noisy excitable media. The noise level in the tissue is characterized by spontaneous activity and can be controlled by applying neuro-transmitter substances[3]. Noise effects in our model are compared with the effect of neuro-transmitters on calcium waves. [1]P. Jung and G. Mayer-Kress, CHAOS 5, 458 (1995). [2]P. Jung and G. Mayer-Kress, Phys. Rev. Lett.62, 2682 (1995). [3

Parameter estimation in stochastic rainfall-runoff models

DEFF Research Database (Denmark)

Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

2006-01-01

A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...

Stochastic resonance for exploration geophysics

OpenAIRE

Omerbashich, Mensur

2008-01-01

Stochastic resonance (SR) is a phenomenon in which signal to noise (SN) ratio gets improved by noise addition rather than removal as envisaged classically. SR was first claimed in climatology a few decades ago and then in other disciplines as well. The same as it is observed in natural systems, SR is used also for allowable SN enhancements at will. Here I report a proof of principle that SR can be useful in exploration geophysics. For this I perform high frequency GaussVanicek variance spectr...

A Study of Stochastic Resonance in the Periodically Forced Rikitake Dynamo

Directory of Open Access Journals (Sweden)

Chien-Chih Chen Chih-Yuan Tseng

2007-01-01

Full Text Available The geodynamo has widely been thought to be an intuitive and selfsustained model of the Earth¡¦s magnetic field. In this paper, we elucidate how a periodic signal could be embedded in the geomagnetic filed via the mechanism of stochastic resonance in a forced Rikitake dynamo. Based on the stochastic resonance observed in the periodically forced Rikitake dynamo, we thus suggest a common triggering for geomagnetic reversal and glacial events. Both kinds of catastrophes may result from the cyclic variation of the Earth¡¦s orbital eccentricity.

Stochastic resonance on Newman-Watts networks of Hodgkin-Huxley neurons with local periodic driving

Energy Technology Data Exchange (ETDEWEB)

Ozer, Mahmut [Zonguldak Karaelmas University, Engineering Faculty, Department of Electrical and Electronics Engineering, 67100 Zonguldak (Turkey)], E-mail: mahmutozer2002@yahoo.com; Perc, Matjaz [University of Maribor, Faculty of Natural Sciences and Mathematics, Department of Physics, Koroska cesta 160, SI-2000 Maribor (Slovenia); Uzuntarla, Muhammet [Zonguldak Karaelmas University, Engineering Faculty, Department of Electrical and Electronics Engineering, 67100 Zonguldak (Turkey)

2009-03-02

We study the phenomenon of stochastic resonance on Newman-Watts small-world networks consisting of biophysically realistic Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise via voltage-gated ion channels embedded in neuronal membranes. Importantly thereby, the subthreshold periodic driving is introduced to a single neuron of the network, thus acting as a pacemaker trying to impose its rhythm on the whole ensemble. We show that there exists an optimal intensity of intrinsic ion channel noise by which the outreach of the pacemaker extends optimally across the whole network. This stochastic resonance phenomenon can be further amplified via fine-tuning of the small-world network structure, and depends significantly also on the coupling strength among neurons and the driving frequency of the pacemaker. In particular, we demonstrate that the noise-induced transmission of weak localized rhythmic activity peaks when the pacemaker frequency matches the intrinsic frequency of subthreshold oscillations. The implications of our findings for weak signal detection and information propagation across neural networks are discussed.

Aspects of stochastic resonance in Josephson junction, bimodal

Indian Academy of Sciences (India)

We present the results of extensive numerical studies on stochastic resonance and its characteristic features in three model systems, namely, a model for Josephson tunnel junctions, the bistable cubic map and a coupled map lattice formed by coupling the cubic maps. Some interesting features regarding the mechanism ...

Aspects of stochastic resonance in Josephson junction, bimodal ...

Indian Academy of Sciences (India)

Abstract. We present the results of extensive numerical studies on stochastic resonance and its characteristic features in three model systems, namely, a model for Josephson tunnel junctions, the bistable cubic map and a coupled map lattice formed by coupling the cubic maps. Some interesting features regarding the ...

Stochastic resonance in a single-mode laser driven by frequency modulated signal and coloured noises

Institute of Scientific and Technical Information of China (English)

Jin Guo-Xiang; Zhang Liang-Ying; Cao Li

2009-01-01

By adding frequency modulated signals to the intensity equation of gain-noise model of the single-mode laser driven by two coloured noises which are correlated, this paper uses the linear approximation method to calculate the power spectrum and signal-to-noise ratio (SNR) of the laser intensity. The results show that the SNR appears typical stochastic resonance with the variation of intensity of the pump noise and quantum noise. As the amplitude of a modulated signal has effects on the SNR, it shows suppression, monotone increasing, stochastic resonance, and multiple stochastic resonance with the variation of the frequency of a carrier signal and modulated signal.

Noise Enhances Action Potential Generation in Mouse Sensory Neurons via Stochastic Resonance.

Science.gov (United States)

Onorato, Irene; D'Alessandro, Giuseppina; Di Castro, Maria Amalia; Renzi, Massimiliano; Dobrowolny, Gabriella; Musarò, Antonio; Salvetti, Marco; Limatola, Cristina; Crisanti, Andrea; Grassi, Francesca

2016-01-01

Noise can enhance perception of tactile and proprioceptive stimuli by stochastic resonance processes. However, the mechanisms underlying this general phenomenon remain to be characterized. Here we studied how externally applied noise influences action potential firing in mouse primary sensory neurons of dorsal root ganglia, modelling a basic process in sensory perception. Since noisy mechanical stimuli may cause stochastic fluctuations in receptor potential, we examined the effects of sub-threshold depolarizing current steps with superimposed random fluctuations. We performed whole cell patch clamp recordings in cultured neurons of mouse dorsal root ganglia. Noise was added either before and during the step, or during the depolarizing step only, to focus onto the specific effects of external noise on action potential generation. In both cases, step + noise stimuli triggered significantly more action potentials than steps alone. The normalized power norm had a clear peak at intermediate noise levels, demonstrating that the phenomenon is driven by stochastic resonance. Spikes evoked in step + noise trials occur earlier and show faster rise time as compared to the occasional ones elicited by steps alone. These data suggest that external noise enhances, via stochastic resonance, the recruitment of transient voltage-gated Na channels, responsible for action potential firing in response to rapid step-wise depolarizing currents.

Parameter estimation in stochastic differential equations

CERN Document Server

Bishwal, Jaya P N

2008-01-01

Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modelling complex phenomena and making beautiful decisions. The subject has attracted researchers from several areas of mathematics and other related fields like economics and finance. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods. Useful because of the current availability of high frequency data is the study of refined asymptotic properties of several estimators when the observation time length is large and the observation time interval is small. Also space time white noise driven models, useful for spatial data, and more sophisticated non-Markovian and non-semimartingale models like fractional diffusions that model the long memory phenomena are examined in this volume.

Stochastic resonance and vibrational resonance in an excitable system: The golden mean barrier

International Nuclear Information System (INIS)

Stan, Cristina; Cristescu, C.P.; Alexandroaei, D.; Agop, M.

2009-01-01

We report on stochastic resonance and vibrational resonance in an electric charge double layer configuration as usually found in electrical discharges, biological cell membranes, chemical systems and nanostructures. The experiment and numerical computation show the existence of a barrier expressible in terms of the golden mean above which the two phenomena do not take place. We consider this as new evidence for the importance of the golden mean criticality in the oscillatory dynamics, in agreement with El Naschie's E-infinity theory. In our experiment, the dynamics of a charge double layer generated in the inter-anode space of a twin electrical discharge is investigated under noise-harmonic and harmonic-harmonic perturbations. In the first case, a Gaussian noise can enhance the response of the system to a weak injected periodic signal, a clear mark of stochastic resonance. In the second case, similar enhancement can appear if the noise is replaced by a harmonic perturbation with a frequency much higher than the frequency of the weak oscillation. The amplitude of the low frequency oscillation shows a maximum versus the amplitude of the high frequency perturbation demonstrating vibrational resonance. In order to model these dynamics, we derived an excitable system by modifying a biased van der Pol oscillator. The computational study considers the behaviour of this system under the same types of perturbation as in the experimental investigations and is found to give consistent results in both situations.

Effectiveness Testing of a Piezoelectric Energy Harvester for an Automobile Wheel Using Stochastic Resonance

Directory of Open Access Journals (Sweden)

Yunshun Zhang

2016-10-01

Full Text Available The collection of clean power from ambient vibrations is considered a promising method for energy harvesting. For the case of wheel rotation, the present study investigates the effectiveness of a piezoelectric energy harvester, with the application of stochastic resonance to optimize the efficiency of energy harvesting. It is hypothesized that when the wheel rotates at variable speeds, the energy harvester is subjected to on-road noise as ambient excitations and a tangentially acting gravity force as a periodic modulation force, which can stimulate stochastic resonance. The energy harvester was miniaturized with a bistable cantilever structure, and the on-road noise was measured for the implementation of a vibrator in an experimental setting. A validation experiment revealed that the harvesting system was optimized to capture power that was approximately 12 times that captured under only on-road noise excitation and 50 times that captured under only the periodic gravity force. Moreover, the investigation of up-sweep excitations with increasing rotational frequency confirmed that stochastic resonance is effective in optimizing the performance of the energy harvester, with a certain bandwidth of vehicle speeds. An actual-vehicle experiment validates that the prototype harvester using stochastic resonance is capable of improving power generation performance for practical tire application.

Subcritical Hopf Bifurcation and Stochastic Resonance of Electrical Activities in Neuron under Electromagnetic Induction

Directory of Open Access Journals (Sweden)

Yu-Xuan Fu

2018-02-01

Full Text Available The FitzHugh–Nagumo model is improved to consider the effect of the electromagnetic induction on single neuron. On the basis of investigating the Hopf bifurcation behavior of the improved model, stochastic resonance in the stochastic version is captured near the bifurcation point. It is revealed that a weak harmonic oscillation in the electromagnetic disturbance can be amplified through stochastic resonance, and it is the cooperative effect of random transition between the resting state and the large amplitude oscillating state that results in the resonant phenomenon. Using the noise dependence of the mean of interburst intervals, we essentially suggest a biologically feasible clue for detecting weak signal by means of neuron model with subcritical Hopf bifurcation. These observations should be helpful in understanding the influence of the magnetic field to neural electrical activity.

Stochastic resonance in a time-delayed mono-stable system with correlated multiplicative and additive white noise

International Nuclear Information System (INIS)

Zhou Yu-Rong

2011-01-01

This paper considers the stochastic resonance for a time-delayed mono-stable system, driven by correlated multiplicative and additive white noise. It finds that the output signal-to-noise ratio (SNR) varies non-monotonically with the delayed times. The SNR varies non-monotonically with the increase of the intensities of the multiplicative and additive noise, with the increase of the correlation strength between the two noises, as well as with the system parameter. (general)

Test models for improving filtering with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

Gershgorin, B.; Harlim, J.; Majda, A.J.

2010-01-01

The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.

Parameter-free resolution of the superposition of stochastic signals

Energy Technology Data Exchange (ETDEWEB)

Scholz, Teresa, E-mail: tascholz@fc.ul.pt [Center for Theoretical and Computational Physics, University of Lisbon (Portugal); Raischel, Frank [Center for Geophysics, IDL, University of Lisbon (Portugal); Closer Consulting, Av. Eng. Duarte Pacheco Torre 1 15" 0, 1070-101 Lisboa (Portugal); Lopes, Vitor V. [DEIO-CIO, University of Lisbon (Portugal); UTEC–Universidad de Ingeniería y Tecnología, Lima (Peru); Lehle, Bernd; Wächter, Matthias; Peinke, Joachim [Institute of Physics and ForWind, Carl-von-Ossietzky University of Oldenburg, Oldenburg (Germany); Lind, Pedro G. [Institute of Physics and ForWind, Carl-von-Ossietzky University of Oldenburg, Oldenburg (Germany); Institute of Physics, University of Osnabrück, Osnabrück (Germany)

2017-01-30

This paper presents a direct method to obtain the deterministic and stochastic contribution of the sum of two independent stochastic processes, one of which is an Ornstein–Uhlenbeck process and the other a general (non-linear) Langevin process. The method is able to distinguish between the stochastic processes, retrieving their corresponding stochastic evolution equations. This framework is based on a recent approach for the analysis of multidimensional Langevin-type stochastic processes in the presence of strong measurement (or observational) noise, which is here extended to impose neither constraints nor parameters and extract all coefficients directly from the empirical data sets. Using synthetic data, it is shown that the method yields satisfactory results.

The unsaturated bistable stochastic resonance system.

Science.gov (United States)

Zhao, Wenli; Wang, Juan; Wang, Linze

2013-09-01

We investigated the characteristics of the output saturation of the classical continuous bistable system (saturation bistable system) and its impact on stochastic resonance (SR). We further proposed a piecewise bistable SR system (unsaturated bistable system) and developed the expression of signal-to-noise ratio (SNR) using the adiabatic approximation theory. Compared with the saturation bistable system, the SNR is significantly improved in our unsaturated bistable SR system. The numerical simulation showed that the unsaturated bistable system performed better in extracting weak signals from strong background noise than the saturation bistable system.

Stochastic resonance in a periodic potential system under a constant force

International Nuclear Information System (INIS)

Hu Gang.

1992-10-01

An overdamped particle moving in a periodic potential, and subject to a constant force and a stochastic force (i.e., χ = -sin(2πχ) + B + Γ(t),Γ(t) is a white noise) is considered. The mobility of the particle, d /dt, is investigated. The stochastic resonance type of behaviour is revealed. The study of the SR problem can thus be extended to systems with periodic force. (author). 13 refs

How does stochastic resonance work within the human brain? - Psychophysics of internal and external noise

International Nuclear Information System (INIS)

Aihara, Takatsugu; Kitajo, Keiichi; Nozaki, Daichi; Yamamoto, Yoshiharu

2010-01-01

We review how research on stochastic resonance (SR) in neuroscience has evolved and point out that the previous studies have overlooked the interaction between internal and external noise. We propose a new psychometric function incorporating SR effects, and show that a Bayesian adaptive method applied to the function efficiently estimates the parameters of the function. Using this procedure in visual detection experiments, we provide significant insight into the relationship between internal and external noise in SR within the human brain.

Accelerated maximum likelihood parameter estimation for stochastic biochemical systems

Directory of Open Access Journals (Sweden)

Daigle Bernie J

2012-05-01

Full Text Available Abstract Background A prerequisite for the mechanistic simulation of a biochemical system is detailed knowledge of its kinetic parameters. Despite recent experimental advances, the estimation of unknown parameter values from observed data is still a bottleneck for obtaining accurate simulation results. Many methods exist for parameter estimation in deterministic biochemical systems; methods for discrete stochastic systems are less well developed. Given the probabilistic nature of stochastic biochemical models, a natural approach is to choose parameter values that maximize the probability of the observed data with respect to the unknown parameters, a.k.a. the maximum likelihood parameter estimates (MLEs. MLE computation for all but the simplest models requires the simulation of many system trajectories that are consistent with experimental data. For models with unknown parameters, this presents a computational challenge, as the generation of consistent trajectories can be an extremely rare occurrence. Results We have developed Monte Carlo Expectation-Maximization with Modified Cross-Entropy Method (MCEM2: an accelerated method for calculating MLEs that combines advances in rare event simulation with a computationally efficient version of the Monte Carlo expectation-maximization (MCEM algorithm. Our method requires no prior knowledge regarding parameter values, and it automatically provides a multivariate parameter uncertainty estimate. We applied the method to five stochastic systems of increasing complexity, progressing from an analytically tractable pure-birth model to a computationally demanding model of yeast-polarization. Our results demonstrate that MCEM2 substantially accelerates MLE computation on all tested models when compared to a stand-alone version of MCEM. Additionally, we show how our method identifies parameter values for certain classes of models more accurately than two recently proposed computationally efficient methods

Stochastic evolution of cosmological parameters in the early universe

Indian Academy of Sciences (India)

We develop a stochastic formulation of cosmology in the early universe, after considering the scatter in the redshift-apparent magnitude diagram in the early epochs as an observational evidence for the non-deterministic evolution of early universe. We consider the stochastic evolution of density parameter in the early ...

Effect of mechanical tactile noise on amplitude of visual evoked potentials: multisensory stochastic resonance.

Science.gov (United States)

Méndez-Balbuena, Ignacio; Huidobro, Nayeli; Silva, Mayte; Flores, Amira; Trenado, Carlos; Quintanar, Luis; Arias-Carrión, Oscar; Kristeva, Rumyana; Manjarrez, Elias

2015-10-01

The present investigation documents the electrophysiological occurrence of multisensory stochastic resonance in the human visual pathway elicited by tactile noise. We define multisensory stochastic resonance of brain evoked potentials as the phenomenon in which an intermediate level of input noise of one sensory modality enhances the brain evoked response of another sensory modality. Here we examined this phenomenon in visual evoked potentials (VEPs) modulated by the addition of tactile noise. Specifically, we examined whether a particular level of mechanical Gaussian noise applied to the index finger can improve the amplitude of the VEP. We compared the amplitude of the positive P100 VEP component between zero noise (ZN), optimal noise (ON), and high mechanical noise (HN). The data disclosed an inverted U-like graph for all the subjects, thus demonstrating the occurrence of a multisensory stochastic resonance in the P100 VEP. Copyright © 2015 the American Physiological Society.

Enhancement of epidemic spread by noise and stochastic resonance in spatial network models with viral dynamics.

Science.gov (United States)

Tuckwell, H C; Toubiana, L; Vibert, J F

2000-05-01

We extend a previous dynamical viral network model to include stochastic effects. The dynamical equations for the viral and immune effector densities within a host population of size n are bilinear, and the noise is white, additive, and Gaussian. The individuals are connected with an n x n transmission matrix, with terms which decay exponentially with distance. In a single individual, for the range of noise parameters considered, it is found that increasing the amplitude of the noise tends to decrease the maximum mean virion level, and slightly accelerate its attainment. Two different spatial dynamical models are employed to ascertain the effects of environmental stochasticity on viral spread. In the first model transmission is unrestricted and there is no threshold within individuals. This model has the advantage that it can be analyzed using a Fokker-Planck approach. The noise is found both to synchronize and uniformize the trajectories of the viral levels across the population of infected individuals, and thus to promote the epidemic spread of the virus. Quantitative measures of the speed of spread and overall amplitude of the epidemic are obtained as functions of the noise and virulence parameters. The mean amplitude increases steadily without threshold effects for a fixed value of the virulence as the noise amplitude sigma is increased, and there is no evidence of a stochastic resonance. However, the speed of transmission, both with respect to its mean and variance, undergoes rapid increases as sigma changes by relatively small amounts. In the second, more realistic, model, there is a threshold for infection and an upper limit to the transmission rate. There may be no spread of infection at all in the absence of noise. With increasing noise level and a low threshold, the mean maximum virion level grows quickly and shows a broad-based stochastic resonance effect. When the threshold within individuals is increased, the mean population virion level increases only

Analysis of stochastic magnetic fields formed by the application of resonant magnetic perturbations on MAST and comparison with experiment

International Nuclear Information System (INIS)

Denner, P.; Liu, Yueqiang; Kirk, A.; Nardon, E.

2012-01-01

In MAST experiments with applied resonant magnetic perturbations (RMPs), clear reduction in line-averaged density has been observed in a wide range of L-mode plasmas when there is an alignment between the perturbation and the equilibrium magnetic field that maximizes the size of the resonant components of the applied magnetic field, as well as in a few H-mode plasmas but with a much stronger sensitivity to this alignment. This density pump-out is the result of increased particle transport, which is thought to be caused by the formation of a stochastic magnetic field in the plasma edge. This paper presents an analysis of the magnetic field structures formed by the application of n = 3 RMPs on MAST, including various parameters characterizing the degree of stochasticity in the plasma edge. Values for these parameters are calculated and compared with the amount of density pump-out observed in MAST experiments. It is found that density pump-out is fairly well correlated with some of the parameters calculated using vacuum modelling, but none of them provides a single threshold value for pump-out that applies to both L- and H-mode plasmas. Plasma response modelling provides a robust criterion for density pump-out that applies both to L- and H-mode plasmas. (paper)

Heart rate variability as determinism with jump stochastic parameters.

Science.gov (United States)

Zheng, Jiongxuan; Skufca, Joseph D; Bollt, Erik M

2013-08-01

We use measured heart rate information (RR intervals) to develop a one-dimensional nonlinear map that describes short term deterministic behavior in the data. Our study suggests that there is a stochastic parameter with persistence which causes the heart rate and rhythm system to wander about a bifurcation point. We propose a modified circle map with a jump process noise term as a model which can qualitatively capture such this behavior of low dimensional transient determinism with occasional (stochastically defined) jumps from one deterministic system to another within a one parameter family of deterministic systems.

Synthetic Computation: Chaos Computing, Logical Stochastic Resonance, and Adaptive Computing

Science.gov (United States)

Kia, Behnam; Murali, K.; Jahed Motlagh, Mohammad-Reza; Sinha, Sudeshna; Ditto, William L.

Nonlinearity and chaos can illustrate numerous behaviors and patterns, and one can select different patterns from this rich library of patterns. In this paper we focus on synthetic computing, a field that engineers and synthesizes nonlinear systems to obtain computation. We explain the importance of nonlinearity, and describe how nonlinear systems can be engineered to perform computation. More specifically, we provide an overview of chaos computing, a field that manually programs chaotic systems to build different types of digital functions. Also we briefly describe logical stochastic resonance (LSR), and then extend the approach of LSR to realize combinational digital logic systems via suitable concatenation of existing logical stochastic resonance blocks. Finally we demonstrate how a chaotic system can be engineered and mated with different machine learning techniques, such as artificial neural networks, random searching, and genetic algorithm, to design different autonomous systems that can adapt and respond to environmental conditions.

Resonant neutron-induced atomic displacements

Energy Technology Data Exchange (ETDEWEB)

Elmaghraby, Elsayed K., E-mail: e.m.k.elmaghraby@gmail.com

2017-05-01

Highlights: • Neutron induced atomic displacements was investigated based on scattering of energy of neutron. • Model for cascade function (multiplication of displacements with increasing energy transfer) was proposed and justified. • Parameterizations for the dpa induced in all elements were performed. • Table containing all necessary parameters to calculate the displacement density induced by neutron is given. • Contribution of non resonance displacement and resonant-neutron induced displacements are distinguished. - Abstract: A model for displacement cascade function was modified to account for the continuous variation of displacement density in the material in response to neutron exposure. The model is based on the Gaussian distribution of displacement energies of atoms in a material. Analytical treatment for moderated epithermal neutron field was given in which the displacement density was divided into two terms, discrete-resonance term and continuum term. Calculation are done for all isotopes using ENDF/B VII.1 data files and temperature dependent cross section library. Weighted elemental values were reported a fitting was performed to obtain energy-dependent formula of displacement density and reduce the number of parameters. Results relevant the present specification of the cascade function are tabulated for each element to enable calculation of displacement density at any value of displacement energy in the between 5 eV and 55 eV.

Estimation of Parameters in Mean-Reverting Stochastic Systems

Directory of Open Access Journals (Sweden)

Tianhai Tian

2014-01-01

Full Text Available Stochastic differential equation (SDE is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models.

Estimation of parameter sensitivities for stochastic reaction networks

KAUST Repository

Gupta, Ankit

2016-01-07

Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a continuous-time Markov chain whose states represent the molecular counts of various species. For such models, effects of parameter uncertainty are often quantified by estimating the infinitesimal sensitivities of some observables with respect to model parameters. The aim of this talk is to present a holistic approach towards this problem of estimating parameter sensitivities for stochastic reaction networks. Our approach is based on a generic formula which allows us to construct efficient estimators for parameter sensitivity using simulations of the underlying model. We will discuss how novel simulation techniques, such as tau-leaping approximations, multi-level methods etc. can be easily integrated with our approach and how one can deal with stiff reaction networks where reactions span multiple time-scales. We will demonstrate the efficiency and applicability of our approach using many examples from the biological literature.

Stochastic resonance in a piecewise nonlinear model driven by multiplicative non-Gaussian noise and additive white noise

Science.gov (United States)

Guo, Yongfeng; Shen, Yajun; Tan, Jianguo

2016-09-01

The phenomenon of stochastic resonance (SR) in a piecewise nonlinear model driven by a periodic signal and correlated noises for the cases of a multiplicative non-Gaussian noise and an additive Gaussian white noise is investigated. Applying the path integral approach, the unified colored noise approximation and the two-state model theory, the analytical expression of the signal-to-noise ratio (SNR) is derived. It is found that conventional stochastic resonance exists in this system. From numerical computations we obtain that: (i) As a function of the non-Gaussian noise intensity, the SNR is increased when the non-Gaussian noise deviation parameter q is increased. (ii) As a function of the Gaussian noise intensity, the SNR is decreased when q is increased. This demonstrates that the effect of the non-Gaussian noise on SNR is different from that of the Gaussian noise in this system. Moreover, we further discuss the effect of the correlation time of the non-Gaussian noise, cross-correlation strength, the amplitude and frequency of the periodic signal on SR.

Comparison of stochastic resonance in static and dynamical nonlinearities

International Nuclear Information System (INIS)

Ma, Yumei; Duan, Fabing

2014-01-01

We compare the stochastic resonance (SR) effects in parallel arrays of static and dynamical nonlinearities via the measure of output signal-to-noise ratio (SNR). For a received noisy periodic signal, parallel arrays of both static and dynamical nonlinearities can enhance the output SNR by optimizing the internal noise level. The static nonlinearity is easily implementable, while the dynamical nonlinearity has more parameters to be tuned, at the risk of not exploiting the beneficial role of internal noise components. It is of interest to note that, for an input signal buried in the external Laplacian noise, we show that the dynamical nonlinearity is superior to the static nonlinearity in obtaining a better output SNR. This characteristic is assumed to be closely associated with the kurtosis of noise distribution. - Highlights: • Comparison of SR effects in arrays of both static and dynamical nonlinearities. • Static nonlinearity is easily implementable for the SNR enhancement. • Dynamical nonlinearity yields a better output SNR for external Laplacian noise

Selective adsorption resonances: Quantum and stochastic approaches

International Nuclear Information System (INIS)

Sanz, A.S.; Miret-Artes, S.

2007-01-01

In this review we cover recent advances in the theory of the selective adsorption phenomenon that appears in light atom/molecule scattering off solid surfaces. Due to the universal van der Waals attractive interaction incoming gas particles can get trapped by the surface, this giving rise to the formation of quasi-bound states or resonances. The knowledge of the position and width of these resonances provides relevant direct information about the nature of the gas-surface interaction as well as about the evaporation and desorption mechanisms. This information can be obtained by means of a plethora of theoretical methods developed in both the energy and time domains, which we analyze and discuss here in detail. In particular, special emphasis is given to close-coupling, wave-packet, and trajectory-based formalisms. Furthermore, a novel description of selective adsorption resonances from a stochastic quantum perspective within the density matrix and Langevin formalisms, when correlations and fluctuations of the surface (considered as a thermal bath) are taken into account, is also proposed and discussed

Stochastic resonance whole-body vibration improves postural control in health care professionals: a worksite randomized controlled trial.

Science.gov (United States)

Elfering, Achim; Schade, Volker; Stoecklin, Lukas; Baur, Simone; Burger, Christian; Radlinger, Lorenz

2014-05-01

Slip, trip, and fall injuries are frequent among health care workers. Stochastic resonance whole-body vibration training was tested to improve postural control. Participants included 124 employees of a Swiss university hospital. The randomized controlled trial included an experimental group given 8 weeks of training and a control group with no intervention. In both groups, postural control was assessed as mediolateral sway on a force plate before and after the 8-week trial. Mediolateral sway was significantly decreased by stochastic resonance whole-body vibration training in the experimental group but not in the control group that received no training (p < .05). Stochastic resonance whole-body vibration training is an option in the primary prevention of balance-related injury at work. Copyright 2014, SLACK Incorporated.

Estafette of drift resonances, stochasticity and control of particle motion in a toroidal magnetic trap

International Nuclear Information System (INIS)

Shishkin, Alexander A.

2001-02-01

A new method of particle motion control in toroidal magnetic traps with rotational transform using the estafette of drift resonances and stochasticity of particle trajectories is proposed. The use of the word estafette' here means that the particle passes through a set of resonances in consecutive order from one to another during its motion. The overlapping of adjacent resonances can be moved radially from the center to the edge of the plasma by switching on the corresponding perturbations in accordance with a particular rule in time. In this way particles (e.g. cold alpha-particle) can be removed from the center of the confinement volume to the plasma periphery. For the analytical treatment of the stochastic behaviour of particle motion the stochastic diffusion coefficients D r, r, D r,θ , D θ,θ are introduced. The new approach is demonstrated by numerical computations of the test helium particle trajectories in the toroidal trap Large Helical Device. (author)

Stochastic Resonance algorithms to enhance damage detection in bearing faults

Directory of Open Access Journals (Sweden)

Castiglione Roberto

2015-01-01

Full Text Available Stochastic Resonance is a phenomenon, studied and mainly exploited in telecommunication, which permits the amplification and detection of weak signals by the assistance of noise. The first papers on this technique are dated early 80 s and were developed to explain the periodically recurrent ice ages. Other applications mainly concern neuroscience, biology, medicine and obviously signal analysis and processing. Recently, some researchers have applied the technique for detecting faults in mechanical systems and bearings. In this paper, we try to better understand the conditions of applicability and which is the best algorithm to be adopted for these purposes. In fact, to get the methodology profitable and efficient to enhance the signal spikes due to fault in rings and balls/rollers of bearings, some parameters have to be properly selected. This is a problem since in system identification this procedure should be as blind as possible. Two algorithms are analysed: the first exploits classical SR with three parameters mutually dependent, while the other uses Woods-Saxon potential, with three parameters yet but holding a different meaning. The comparison of the performances of the two algorithms and the optimal choice of their parameters are the scopes of this paper. Algorithms are tested on simulated and experimental data showing an evident capacity of increasing the signal to noise ratio.

Phenomenon of entropic stochastic resonance with asymmetric dichotomous noise and white noise

International Nuclear Information System (INIS)

Guo, Feng; Li, Shao-Fu; Cheng, Xiao-Feng

2012-01-01

The entropic stochastic resonance (ESR) in a confined system subject to asymmetric dichotomous noise, white noise, and a periodic square-wave signal is investigated. Under the adiabatic approximation condition, by use of the properties of the dichotomous noise, we obtain the expression of the output signal-to-noise ratio (SNR) based on two-state theory. The SNR is shown to be a nonmonotonic function of the strength and asymmetry of the dichotomous noise, the intensity of the white noise, and the amplitude of the square-wave signal. The SNR varies non-monotonically with increases in the parameters of the confined structure. The influence of the correlation rate of the dichotomous noise and the frequency of the external constant force on the SNR is also discussed.

On Volatility Induced Stationarity for Stochastic Differential Equations

DEFF Research Database (Denmark)

Albin, J.M.P.; Astrup Jensen, Bjarne; Muszta, Anders

2006-01-01

This article deals with stochastic differential equations with volatility induced stationarity. We study of theoretical properties of such equations, as well as numerical aspects, together with a detailed study of three examples.......This article deals with stochastic differential equations with volatility induced stationarity. We study of theoretical properties of such equations, as well as numerical aspects, together with a detailed study of three examples....

Suprathreshold stochastic resonance in neural processing tuned by correlation.

Science.gov (United States)

Durrant, Simon; Kang, Yanmei; Stocks, Nigel; Feng, Jianfeng

2011-07-01

Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.

Förster resonance energy transfer, absorption and emission spectra in multichromophoric systems. III. Exact stochastic path integral evaluation.

Science.gov (United States)

Moix, Jeremy M; Ma, Jian; Cao, Jianshu

2015-03-07

A numerically exact path integral treatment of the absorption and emission spectra of open quantum systems is presented that requires only the straightforward solution of a stochastic differential equation. The approach converges rapidly enabling the calculation of spectra of large excitonic systems across the complete range of system parameters and for arbitrary bath spectral densities. With the numerically exact absorption and emission operators, one can also immediately compute energy transfer rates using the multi-chromophoric Förster resonant energy transfer formalism. Benchmark calculations on the emission spectra of two level systems are presented demonstrating the efficacy of the stochastic approach. This is followed by calculations of the energy transfer rates between two weakly coupled dimer systems as a function of temperature and system-bath coupling strength. It is shown that the recently developed hybrid cumulant expansion (see Paper II) is the only perturbative method capable of generating uniformly reliable energy transfer rates and emission spectra across a broad range of system parameters.

A Framework to Analyze the Stochastic Harmonics and Resonance of Wind Energy Grid Interconnection

Directory of Open Access Journals (Sweden)

Youngho Cho

2016-08-01

Full Text Available This paper addresses a modeling and analysis methodology for investigating the stochastic harmonics and resonance concerns of wind power plants (WPPs. Wideband harmonics from modern wind turbines (WTs are observed to be stochastic, associated with real power production, and they may adversely interact with the grid impedance and cause unexpected harmonic resonance, if not comprehensively addressed in the planning and commissioning of the WPPs. These issues should become more critical as wind penetration levels increase. We thus propose a planning study framework comprising the following functional steps: First, the best fitted probability density functions (PDFs of the harmonic components of interest in the frequency domain are determined. In operations planning, maximum likelihood estimations (MLEs followed by a chi-square test are used once field measurements or manufacturers’ data are available. Second, harmonic currents from the WPP are represented by randomly-generating harmonic components based on their PDFs (frequency spectrum and then synthesized for time domain simulations via inverse Fourier transform. Finally, we conduct a comprehensive assessment by including the impacts of feeder configurations, harmonic filters and the variability of parameters. We demonstrate the efficacy of the proposed study approach for a 100-MW offshore WPP consisting of 20 units of 5-MW full converter turbines, a realistic benchmark system adapted from a WPP under development in Korea and discuss lessons learned through this research.

Internal additive noise effects in stochastic resonance using organic field effect transistor

Energy Technology Data Exchange (ETDEWEB)

Suzuki, Yoshiharu; Asakawa, Naoki [Division of Molecular Science, Graduate School of Science and Technology, Gunma University, 1-5-1 Tenjin-cho, Kiryu, Gunma 376-8515 (Japan); Matsubara, Kiyohiko [KOOROGI LLC, 6-1585-1-B Sakaino-cho, Kiryu, Gunma 376-0002 (Japan)

2016-08-29

Stochastic resonance phenomenon was observed in organic field effect transistor using poly(3-hexylthiophene), which enhances performance of signal transmission with application of noise. The enhancement of correlation coefficient between the input and output signals was low, and the variation of correlation coefficient was not remarkable with respect to the intensity of external noise, which was due to the existence of internal additive noise following the nonlinear threshold response. In other words, internal additive noise plays a positive role on the capability of approximately constant signal transmission regardless of noise intensity, which can be said “homeostatic” behavior or “noise robustness” against external noise. Furthermore, internal additive noise causes emergence of the stochastic resonance effect even on the threshold unit without internal additive noise on which the correlation coefficient usually decreases monotonically.

Effects of time delay on stochastic resonance of the stock prices in financial system

Energy Technology Data Exchange (ETDEWEB)

Li, Jiang-Cheng [Department of Physics, Yunnan University, Kunming, 650091 (China); Li, Chun [Department of Computer Science, Puer Teachers' College, Puer 665000 (China); Mei, Dong-Cheng, E-mail: meidch@ynu.edu.cn [Department of Physics, Yunnan University, Kunming, 650091 (China)

2014-06-13

The effect of time delay on stochastic resonance of the stock prices in finance system was investigated. The time delay is introduced into the Heston model driven by the extrinsic and intrinsic periodic information for stock price. The signal power amplification (SPA) was calculated by numerical simulation. The results indicate that an optimal critical value of delay time maximally enhances the reverse-resonance in the behaviors of SPA as a function of long-run variance of volatility or cross correlation coefficient between noises for both cases of intrinsic and extrinsic periodic information. Moreover, in both cases, being a critical value in the delay time, when the delay time takes value below the critical value, reverse-resonance increases with the delay time increasing, however, when the delay time takes value above the critical value, the reverse-resonance decrease with the delay time increasing. - Highlights: • The effects of delay time on stochastic resonance of the stock prices was investigated. • There is an optimal critical value of delay time maximally enhances the reverse-resonance • The reverse-resonance increases with the delay time increasing as the delay time takes value below the critical value • The reverse-resonance decrease with the delay time increasing as the delay time takes value above the critical value.

Effects of time delay on stochastic resonance of the stock prices in financial system

International Nuclear Information System (INIS)

Li, Jiang-Cheng; Li, Chun; Mei, Dong-Cheng

2014-01-01

The effect of time delay on stochastic resonance of the stock prices in finance system was investigated. The time delay is introduced into the Heston model driven by the extrinsic and intrinsic periodic information for stock price. The signal power amplification (SPA) was calculated by numerical simulation. The results indicate that an optimal critical value of delay time maximally enhances the reverse-resonance in the behaviors of SPA as a function of long-run variance of volatility or cross correlation coefficient between noises for both cases of intrinsic and extrinsic periodic information. Moreover, in both cases, being a critical value in the delay time, when the delay time takes value below the critical value, reverse-resonance increases with the delay time increasing, however, when the delay time takes value above the critical value, the reverse-resonance decrease with the delay time increasing. - Highlights: • The effects of delay time on stochastic resonance of the stock prices was investigated. • There is an optimal critical value of delay time maximally enhances the reverse-resonance • The reverse-resonance increases with the delay time increasing as the delay time takes value below the critical value • The reverse-resonance decrease with the delay time increasing as the delay time takes value above the critical value

Estimation of parameter sensitivities for stochastic reaction networks

KAUST Repository

Gupta, Ankit

2016-01-01

Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a

Stochastic resonance in multi-stable coupled systems driven by two driving signals

Science.gov (United States)

Xu, Pengfei; Jin, Yanfei

2018-02-01

The stochastic resonance (SR) in multi-stable coupled systems subjected to Gaussian white noises and two different driving signals is investigated in this paper. Using the adiabatic approximation and the perturbation method, the coupled systems with four-well potential are transformed into the master equations and the amplitude of the response is obtained. The signal-to-noise ratio (SNR) is calculated numerically to demonstrate the occurrence of SR. For the case of two driving signals with different amplitudes, the interwell resonance between two wells S1 and S3 emerges for strong coupling. The SR can appear in the subsystem with weaker signal amplitude or even without driving signal with the help of coupling. For the case of two driving signals with different frequencies, the effects of SR in two subsystems driven by high and low frequency signals are both weakened with an increase in coupling strength. The stochastic multi-resonance phenomenon is observed in the subsystem subjected to the low frequency signal. Moreover, an effective scheme for phase suppressing SR is proposed by using a relative phase between two driving signals.

Information transfer with rate-modulated Poisson processes: a simple model for nonstationary stochastic resonance.

Science.gov (United States)

Goychuk, I

2001-08-01

Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.

Weak-periodic stochastic resonance in a parallel array of static nonlinearities.

Directory of Open Access Journals (Sweden)

Yumei Ma

Full Text Available This paper studies the output-input signal-to-noise ratio (SNR gain of an uncoupled parallel array of static, yet arbitrary, nonlinear elements for transmitting a weak periodic signal in additive white noise. In the small-signal limit, an explicit expression for the SNR gain is derived. It serves to prove that the SNR gain is always a monotonically increasing function of the array size for any given nonlinearity and noisy environment. It also determines the SNR gain maximized by the locally optimal nonlinearity as the upper bound of the SNR gain achieved by an array of static nonlinear elements. With locally optimal nonlinearity, it is demonstrated that stochastic resonance cannot occur, i.e. adding internal noise into the array never improves the SNR gain. However, in an array of suboptimal but easily implemented threshold nonlinearities, we show the feasibility of situations where stochastic resonance occurs, and also the possibility of the SNR gain exceeding unity for a wide range of input noise distributions.

Intrinsic periodic and aperiodic stochastic resonance in an electrochemical cell

Science.gov (United States)

Tiwari, Ishant; Phogat, Richa; Parmananda, P.; Ocampo-Espindola, J. L.; Rivera, M.

2016-08-01

In this paper we show the interaction of a composite of a periodic or aperiodic signal and intrinsic electrochemical noise with the nonlinear dynamics of an electrochemical cell configured to study the corrosion of iron in an acidic media. The anodic voltage setpoint (V0) in the cell is chosen such that the anodic current (I ) exhibits excitable fixed point behavior in the absence of noise. The subthreshold periodic (aperiodic) signal consists of a train of rectangular pulses with a fixed amplitude and width, separated by regular (irregular) time intervals. The irregular time intervals chosen are of deterministic and stochastic origins. The amplitude of the intrinsic internal noise, regulated by the concentration of chloride ions, is then monotonically increased, and the provoked dynamics are analyzed. The signal to noise ratio and the cross-correlation coefficient versus the chloride ions' concentration curves have a unimodal shape indicating the emergence of an intrinsic periodic or aperiodic stochastic resonance. The abscissa for the maxima of these unimodal curves correspond to the optimum value of intrinsic noise where maximum regularity of the invoked dynamics is observed. In the particular case of the intrinsic periodic stochastic resonance, the scanning electron microscope images for the electrode metal surfaces are shown for certain values of chloride ions' concentrations. These images, qualitatively, corroborate the emergence of order as a result of the interaction between the nonlinear dynamics and the composite signal.

Stochastic Resonance in an Underdamped System with Pinning Potential for Weak Signal Detection

Directory of Open Access Journals (Sweden)

Haibin Zhang

2015-08-01

Full Text Available Stochastic resonance (SR has been proved to be an effective approach for weak sensor signal detection. This study presents a new weak signal detection method based on a SR in an underdamped system, which consists of a pinning potential model. The model was firstly discovered from magnetic domain wall (DW in ferromagnetic strips. We analyze the principle of the proposed underdamped pinning SR (UPSR system, the detailed numerical simulation and system performance. We also propose the strategy of selecting the proper damping factor and other system parameters to match a weak signal, input noise and to generate the highest output signal-to-noise ratio (SNR. Finally, we have verified its effectiveness with both simulated and experimental input signals. Results indicate that the UPSR performs better in weak signal detection than the conventional SR (CSR with merits of higher output SNR, better anti-noise and frequency response capability. Besides, the system can be designed accurately and efficiently owing to the sensibility of parameters and potential diversity. The features also weaken the limitation of small parameters on SR system.

Stochastic Resonance in an Underdamped System with Pinning Potential for Weak Signal Detection.

Science.gov (United States)

Zhang, Haibin; He, Qingbo; Kong, Fanrang

2015-08-28

Stochastic resonance (SR) has been proved to be an effective approach for weak sensor signal detection. This study presents a new weak signal detection method based on a SR in an underdamped system, which consists of a pinning potential model. The model was firstly discovered from magnetic domain wall (DW) in ferromagnetic strips. We analyze the principle of the proposed underdamped pinning SR (UPSR) system, the detailed numerical simulation and system performance. We also propose the strategy of selecting the proper damping factor and other system parameters to match a weak signal, input noise and to generate the highest output signal-to-noise ratio (SNR). Finally, we have verified its effectiveness with both simulated and experimental input signals. Results indicate that the UPSR performs better in weak signal detection than the conventional SR (CSR) with merits of higher output SNR, better anti-noise and frequency response capability. Besides, the system can be designed accurately and efficiently owing to the sensibility of parameters and potential diversity. The features also weaken the limitation of small parameters on SR system.

Stochastic Resonance-Like and Resonance Suppression-Like Phenomena in a Bistable System with Time Delay and Additive Noise

International Nuclear Information System (INIS)

Shu Chang-Zheng; Nie Lin-Ru; Zhou Zhong-Rao

2012-01-01

Stochastic resonance (SR)-like and resonance suppression (RS)-like phenomena in a time-delayed bistable system driven by additive white noise are investigated by means of stochastic simulations of the power spectrum, the quality factor of the power spectrum, and the mean first-passage time (MFPT) of the system. The calculative results indicate that: (i) as the system is driven by a small periodic signal, the quality factor as a function delay time exhibits a maximal value at smaller noise intensities, i.e., an SR-like phenomenon. With the increment in additive noise intensity, the extremum gradually disappears and the quality factor decreases monotonously with delay time. (ii) As the additive noise intensity is smaller, the curve of the MFPT with respect to delay time displays a peak, i.e., an RS-like phenomenon. At higher levels of noise, however, the non-monotonic behavior is lost. (general)

Research on Stochastic Resonance Signal’s Recovery

Directory of Open Access Journals (Sweden)

Hao Wang

2013-01-01

Full Text Available Using stochastic resonance to detect weak periodic signals has been widely used in various fields of science, which attracts much attention of researchers due to its advantages of revealing recessive periodic laws. This paper utilized this method to seek the underlying rule of setting weather index, so we can find that how to obtain the accurate expression of original periodic law by further investigation. This paper deals with the noise-contained signal restoring on the basis of the established system coupling the inversion system and bistable system. The simulation shows that this signal recovery method inversion effect is better and the application range is wider.

Stochastic resonance for a metapopulation system driven by multiplicative and additive colored noises

International Nuclear Information System (INIS)

Wang Kang-Kang; Liu Xian-Bin

2014-01-01

We investigate the stochastic resonance (SR) phenomenon induced by the periodic signal in a metapopulation system with colored noises. The analytical expression of signal-to-noise is derived in the adiabatic limit. By numerical calculation, the effects of the addictive noise intensity, the multiplicative noise intensity and two noise self-correlation times on SNR are respectively discussed. It shows that: (i) in the case that the addictive noise intensity M takes a small value, a SR phenomenon for the curve of SNR appears; however, when M takes a large value, SNR turns into a monotonic function on the multiplicative noise intensity Q. (ii) The resonance peaks in the plots of the multiplicative noise intensity Q versus its self-correlation time τ 1 and the addictive noise intensity M versus its self-correlation time τ 2 translate in parallel. Meanwhile, a parallel translation also appears in the plots of τ 1 versus Q and τ 2 versus M. (iii) The interactive effects between self-correlation times τ 1 and τ 2 are opposite. (general)

A termination criterion for parameter estimation in stochastic models in systems biology.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven

2015-11-01

Parameter estimation procedures are a central aspect of modeling approaches in systems biology. They are often computationally expensive, especially when the models take stochasticity into account. Typically parameter estimation involves the iterative optimization of an objective function that describes how well the model fits some measured data with a certain set of parameter values. In order to limit the computational expenses it is therefore important to apply an adequate stopping criterion for the optimization process, so that the optimization continues at least until a reasonable fit is obtained, but not much longer. In the case of stochastic modeling, at least some parameter estimation schemes involve an objective function that is itself a random variable. This means that plain convergence tests are not a priori suitable as stopping criteria. This article suggests a termination criterion suited to optimization problems in parameter estimation arising from stochastic models in systems biology. The termination criterion is developed for optimization algorithms that involve populations of parameter sets, such as particle swarm or evolutionary algorithms. It is based on comparing the variance of the objective function over the whole population of parameter sets with the variance of repeated evaluations of the objective function at the best parameter set. The performance is demonstrated for several different algorithms. To test the termination criterion we choose polynomial test functions as well as systems biology models such as an Immigration-Death model and a bistable genetic toggle switch. The genetic toggle switch is an especially challenging test case as it shows a stochastic switching between two steady states which is qualitatively different from the model behavior in a deterministic model. Copyright © 2015. Published by Elsevier Ireland Ltd.

Fractional noise destroys or induces a stochastic bifurcation

Energy Technology Data Exchange (ETDEWEB)

Yang, Qigui, E-mail: qgyang@scut.edu.cn [School of Sciences, South China University of Technology, Guangzhou 510640 (China); Zeng, Caibin, E-mail: zeng.cb@mail.scut.edu.cn [School of Sciences, South China University of Technology, Guangzhou 510640 (China); School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640 (China); Wang, Cong, E-mail: wangcong@scut.edu.cn [School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640 (China)

2013-12-15

Little seems to be known about the stochastic bifurcation phenomena of non-Markovian systems. Our intention in this paper is to understand such complex dynamics by a simple system, namely, the Black-Scholes model driven by a mixed fractional Brownian motion. The most interesting finding is that the multiplicative fractional noise not only destroys but also induces a stochastic bifurcation under some suitable conditions. So it opens a possible way to explore the theory of stochastic bifurcation in the non-Markovian framework.

Amplification of weak signals via the non-adiabatic regime of stochastic resonance in a bistable dynamical system with time delay

International Nuclear Information System (INIS)

Du Luchun; Mei Dongcheng

2011-01-01

The non-adiabatic regime of stochastic resonance (SR) in a bistable system with time delay, an additive white noise and a periodic signal was investigated. The signal power amplification η was employed to characterize the SR of the system. The simulation results indicate that (i) in the case of intermediate frequency Ω of the periodic signal, the typical behavior of SR is lowered monotonically by increasing the delay time τ; in the case of large Ω, τ weakens the SR behavior and then enhances it, with a non-monotonic behavior as a function of time delay; (ii) time delay induces SR when A is above the threshold, whereas no such resonance exists in the absence of time delay; (iii) time delay induces a transition from bimodal to unimodal configuration of η; (iv) varying the particular form of time delay results in different phenomena.

Stochastic Mixed-Effects Parameters Bertalanffy Process, with Applications to Tree Crown Width Modeling

Directory of Open Access Journals (Sweden)

Petras Rupšys

2015-01-01

Full Text Available A stochastic modeling approach based on the Bertalanffy law gained interest due to its ability to produce more accurate results than the deterministic approaches. We examine tree crown width dynamic with the Bertalanffy type stochastic differential equation (SDE and mixed-effects parameters. In this study, we demonstrate how this simple model can be used to calculate predictions of crown width. We propose a parameter estimation method and computational guidelines. The primary goal of the study was to estimate the parameters by considering discrete sampling of the diameter at breast height and crown width and by using maximum likelihood procedure. Performance statistics for the crown width equation include statistical indexes and analysis of residuals. We use data provided by the Lithuanian National Forest Inventory from Scots pine trees to illustrate issues of our modeling technique. Comparison of the predicted crown width values of mixed-effects parameters model with those obtained using fixed-effects parameters model demonstrates the predictive power of the stochastic differential equations model with mixed-effects parameters. All results were implemented in a symbolic algebra system MAPLE.

Adaptive control of chaotic systems with stochastic time varying unknown parameters

Energy Technology Data Exchange (ETDEWEB)

Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

2008-10-15

In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.

Review of 241 Pu resonance parameters

International Nuclear Information System (INIS)

Derrien, H.

1981-10-01

The status of 241 Pu resonance parameters is reviewed. The most important recent results are compared in some energy ranges, both from single level and multilevel point of view. It appears that an accurate set of resonance parameters is not still obtained for a general description of the cross-sections in the resonance region. Some recommendations are given for further experiments or evaluations

Entropic stochastic resonance without external force in oscillatory confined space

Energy Technology Data Exchange (ETDEWEB)

Ding, Huai; Jiang, Huijun; Hou, Zhonghuai, E-mail: hzhlj@ustc.edu.cn [Department of Chemical Physics and Hefei National Laboratory for Physical Sciences at Microscales, iChEM, University of Science and Technology of China, Hefei, Anhui 230026 (China)

2015-05-21

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.

Stochastic resonance

International Nuclear Information System (INIS)

Wellens, Thomas; Shatokhin, Vyacheslav; Buchleitner, Andreas

2004-01-01

We are taught by conventional wisdom that the transmission and detection of signals is hindered by noise. However, during the last two decades, the paradigm of stochastic resonance (SR) proved this assertion wrong: indeed, addition of the appropriate amount of noise can boost a signal and hence facilitate its detection in a noisy environment. Due to its simplicity and robustness, SR has been implemented by mother nature on almost every scale, thus attracting interdisciplinary interest from physicists, geologists, engineers, biologists and medical doctors, who nowadays use it as an instrument for their specific purposes. At the present time, there exist a lot of diversified models of SR. Taking into account the progress achieved in both theoretical understanding and practical application of this phenomenon, we put the focus of the present review not on discussing in depth technical details of different models and approaches but rather on presenting a general and clear physical picture of SR on a pedagogical level. Particular emphasis will be given to the implementation of SR in generic quantum systems-an issue that has received limited attention in earlier review papers on the topic. The major part of our presentation relies on the two-state model of SR (or on simple variants thereof), which is general enough to exhibit the main features of SR and, in fact, covers many (if not most) of the examples of SR published so far. In order to highlight the diversity of the two-state model, we shall discuss several examples from such different fields as condensed matter, nonlinear and quantum optics and biophysics. Finally, we also discuss some situations that go beyond the generic SR scenario but are still characterized by a constructive role of noise

A new unbiased stochastic derivative estimator for discontinuous sample performances with structural parameters

NARCIS (Netherlands)

Peng, Yijie; Fu, Michael C.; Hu, Jian Qiang; Heidergott, Bernd

In this paper, we propose a new unbiased stochastic derivative estimator in a framework that can handle discontinuous sample performances with structural parameters. This work extends the three most popular unbiased stochastic derivative estimators: (1) infinitesimal perturbation analysis (IPA), (2)

Stochastic Resonance algorithms to enhance damage detection in bearing faults

OpenAIRE

Castiglione Roberto; Garibaldi Luigi; Marchesiello Stefano

2015-01-01

Stochastic Resonance is a phenomenon, studied and mainly exploited in telecommunication, which permits the amplification and detection of weak signals by the assistance of noise. The first papers on this technique are dated early 80 s and were developed to explain the periodically recurrent ice ages. Other applications mainly concern neuroscience, biology, medicine and obviously signal analysis and processing. Recently, some researchers have applied the technique for detecting faults in mecha...

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

Science.gov (United States)

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Far from Equilibrium Percolation, Stochastic and Shape Resonances in the Physics of Life

Directory of Open Access Journals (Sweden)

Antonio Bianconi

2011-10-01

Full Text Available Key physical concepts, relevant for the cross-fertilization between condensed matter physics and the physics of life seen as a collective phenomenon in a system out-of-equilibrium, are discussed. The onset of life can be driven by: (a the critical fluctuations at the protonic percolation threshold in membrane transport; (b the stochastic resonance in biological systems, a mechanism that can exploit external and self-generated noise in order to gain efficiency in signal processing; and (c the shape resonance (or Fano resonance or Feshbach resonance in the association and dissociation processes of bio-molecules (a quantum mechanism that could play a key role to establish a macroscopic quantum coherence in the cell.

Delay-controlled primary and stochastic resonances of the SD oscillator with stiffness nonlinearities

Science.gov (United States)

Yang, Tao; Cao, Qingjie

2018-03-01

This work presents analytical studies of the stiffness nonlinearities SD (smooth and discontinuous) oscillator under displacement and velocity feedback control with a time delay. The SD oscillator can capture the qualitative characteristics of quasi-zero-stiffness and negative-stiffness. We focus mainly on the primary resonance of the quasi-zero-stiffness SD oscillator and the stochastic resonance (SR) of the negative-stiffness SD oscillator. Using the averaging method, we have been analyzed the amplitude response of the quasi-zero-stiffness SD oscillator. In this regard, the optimum time delay for changing the control intensity according to the optimization standard proposed can be obtained. For the optimum time delay, increasing the displacement feedback intensity is advantageous to suppress the vibrations in resonant regime where vibration isolation is needed, however, increasing the velocity feedback intensity is advantageous to strengthen the vibrations. Moreover, the effects of time-delayed feedback on the SR of the negative-stiffness SD oscillator are investigated under harmonic forcing and Gaussian white noise, based on the Langevin and Fokker-Planck approaches. The time-delayed feedback can enhance the SR phenomenon where vibrational energy harvesting is needed. This paper established the relationship between the parameters and vibration properties of a stiffness nonlinearities SD which provides the guidance for optimizing time-delayed control for vibration isolation and vibrational energy harvesting of the nonlinear systems.

Do basal Ganglia amplify willed action by stochastic resonance? A model.

Directory of Open Access Journals (Sweden)

V Srinivasa Chakravarthy

Full Text Available Basal ganglia are usually attributed a role in facilitating willed action, which is found to be impaired in Parkinson's disease, a pathology of basal ganglia. We hypothesize that basal ganglia possess the machinery to amplify will signals, presumably weak, by stochastic resonance. Recently we proposed a computational model of Parkinsonian reaching, in which the contributions from basal ganglia aid the motor cortex in learning to reach. The model was cast in reinforcement learning framework. We now show that the above basal ganglia computational model has all the ingredients of stochastic resonance process. In the proposed computational model, we consider the problem of moving an arm from a rest position to a target position: the two positions correspond to two extrema of the value function. A single kick (a half-wave of sinusoid, of sufficiently low amplitude given to the system in resting position, succeeds in taking the system to the target position, with high probability, only at a critical noise level. But for suboptimal noise levels, the model arm's movements resemble Parkinsonian movement symptoms like akinetic rigidity (low noise and dyskinesias (high noise.

Integral data analysis for resonance parameters determination

International Nuclear Information System (INIS)

Larson, N.M.; Leal, L.C.; Derrien, H.

1997-09-01

Neutron time-of-flight experiments have long been used to determine resonance parameters. Those resonance parameters have then been used in calculations of integral quantities such as Maxwellian averages or resonance integrals, and results of those calculations in turn have been used as a criterion for acceptability of the resonance analysis. However, the calculations were inadequate because covariances on the parameter values were not included in the calculations. In this report an effort to correct for that deficiency is documented: (1) the R-matrix analysis code SAMMY has been modified to include integral quantities of importance, (2) directly within the resonance parameter analysis, and (3) to determine the best fit to both differential (microscopic) and integral (macroscopic) data simultaneously. This modification was implemented because it is expected to have an impact on the intermediate-energy range that is important for criticality safety applications

Robust nonlinear autoregressive moving average model parameter estimation using stochastic recurrent artificial neural networks

DEFF Research Database (Denmark)

Chon, K H; Hoyer, D; Armoundas, A A

1999-01-01

In this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic...... part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction...... error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate...

Neutron capture measurements and resonance parameters of dysprosium

Energy Technology Data Exchange (ETDEWEB)

Shin, S.G.; Kye, Y.U.; Namkung, W.; Cho, M.H. [Pohang University of Science and Technology, Division of Advanced Nuclear Engineering, Pohang, Gyeongbuk (Korea, Republic of); Kang, Y.R.; Lee, M.W. [Dongnam Inst. of Radiological and Medical Sciences, Research Center, Busan (Korea, Republic of); Kim, G.N. [Kyungpook National University, Department of Physics, Daegu (Korea, Republic of); Ro, T.I. [Dong-A University, Department of Physics, Busan (Korea, Republic of); Danon, Y.; Williams, D. [Rensselaer Polytechnic Institute, Department of Mechanical, Aerospace, and Nuclear Engineering, Troy, NY (United States); Leinweber, G.; Block, R.C.; Barry, D.P.; Rapp, M.J. [Naval Nuclear Laboratory, Knolls Atomic Power Laboratory, Schenectady, NY (United States)

2017-10-15

Neutron capture yields of dysprosium isotopes ({sup 161}Dy, {sup 162}Dy, {sup 163}Dy, and {sup 164}Dy) were measured using the time-of-flight method with a 16 segment sodium iodide multiplicity detector. The measurements were made at the 25m flight station at the Gaerttner LINAC Center at Rensselaer Polytechnic Institute. Resonance parameters were obtained using the multilevel R-matrix Bayesian code SAMMY. The neutron capture data for four enriched dysprosium isotopes and one natural dysprosium sample were sequentially fitted. New resonances not listed in ENDF/B-VII.1 were observed. There were 29 and 17 new resonances from {sup 161}Dy and {sup 163}Dy isotopes, respectively. Six resonances from {sup 161}Dy isotope, two resonances from {sup 163}Dy, and four resonances from {sup 164}Dy were not observed. The capture resonance integrals of each isotope were calculated with the resulting resonance parameters and those of ENDF/B-VII.1 in the energy region from 0.5 eV to 20 MeV and were compared to the capture resonance integrals with the resonance parameters from ENDF/B-VII.1. A resonance integral value of the natural dysprosium calculated with present resonance parameters was 1405 ± 3.5 barn. The value is ∝ 0.3% higher than that obtained with the ENDF/B-VII.1 parameters. The distributions of the present and ENDF/B-VII.1 neutron widths were compared to a Porter-Thomas distribution. Neutron strength functions for {sup 161}Dy and {sup 163}Dy were calculated with the present resonance parameters and both values were in between the values of ''Atlas of Neutron Resonances'' and ENDF/B-VII.1. The present radiation width distributions of {sup 161}Dy and {sup 163}Dy were fitted with the χ{sup 2} distribution by varying the degrees of freedom. (orig.)

Stochastic Parameter Development for PORFLOW Simulations of the Hanford AX Tank Farm

International Nuclear Information System (INIS)

Ho, C.K.; Baca, R.G.; Conrad, S.H.; Smith, G.A.; Shyr, L.; Wheeler, T.A.

1999-01-01

Parameters have been identified that can be modeled stochastically using PORFLOW and Latin Hypercube Sampling (LHS). These parameters include hydrologic and transport properties in the vadose and saturated zones, as well as source-term parameters and infiltration rates. A number of resources were used to define the parameter distributions, primarily those provided in the Retrieval Performance Evaluation Report (Jacobs, 1998). A linear rank regression was performed on the vadose-zone hydrologic parameters given in Khaleel and Freeman (1995) to determine if correlations existed between pairs of parameters. No strong correlations were found among the vadose-zone hydrologic parameters, and it was recommended that these parameters be sampled independently until future data or analyses reveal a strong correlation or functional relationship between parameters. Other distributions for source-term parameters, infiltration rates, and saturated-zone parameters that are required to stochastically analyze the performance of the AX Tank Farm using LHS/PORFLOW were adapted from distributions and values reported in Jacobs (1998) and other literature sources. Discussions pertaining to the geologic conceptualization, vadose-zone modeling, and saturated-zone modeling of the AX Tank Farm are also presented

The LIPAR-5 resonance parameter library

International Nuclear Information System (INIS)

Abagyan, L.P.

1997-08-01

The LIPAR-5 neutron resolved resonance parameter library has been elaborated. It contains data for 94 isotopes. The author's evaluations are included in LIPAR. Other authors' results are also included after re-evaluation. The codes used for the evaluation are described briefly. Tables of results are included for every isotope: the boundaries of the resolved resonance region, the numbers of s- and p-resonances, the thermal neutron partial cross-sections and the resonance integrals. The parameters are presented in ENDF/B-6 format. LIPAR is part of the nuclear data library of the MCU Monte Carlo code for neutron transport calculations. LIPAR was verified by comparing the benchmark experiment and Monte Carlo calculation results. (author). 44 refs, 6 tabs

Stochastic Resonance with a Joint Woods-Saxon and Gaussian Potential for Bearing Fault Diagnosis

Directory of Open Access Journals (Sweden)

Haibin Zhang

2014-01-01

Full Text Available This work aims for a new stochastic resonance (SR model which performs well in bearing fault diagnosis. Different from the traditional bistable SR system, we realize the SR based on the joint of Woods-Saxon potential (WSP and Gaussian potential (GP instead of a reflection-symmetric quartic potential. With this potential model, all the parameters in the Woods-Saxon and Gaussian SR (WSGSR system are not coupled when compared to the traditional one, so the output signal-to-noise ratio (SNR can be optimized much more easily by tuning the system parameters. Besides, a smoother potential bottom and steeper potential wall lead to a stable particle motion within each potential well and avoid the unexpected noise. Different from the SR with only WSP which is a monostable system, we improve it into a bistable one as a general form offering a higher SNR and a wider bandwidth. Finally, the proposed model is verified to be outstanding in weak signal detection for bearing fault diagnosis and the strategy offers us a more effective and feasible diagnosis conclusion.

Parameter Estimation in Stochastic Grey-Box Models

DEFF Research Database (Denmark)

Kristensen, Niels Rode; Madsen, Henrik; Jørgensen, Sten Bay

2004-01-01

An efficient and flexible parameter estimation scheme for grey-box models in the sense of discretely, partially observed Ito stochastic differential equations with measurement noise is presented along with a corresponding software implementation. The estimation scheme is based on the extended...... Kalman filter and features maximum likelihood as well as maximum a posteriori estimation on multiple independent data sets, including irregularly sampled data sets and data sets with occasional outliers and missing observations. The software implementation is compared to an existing software tool...... and proves to have better performance both in terms of quality of estimates for nonlinear systems with significant diffusion and in terms of reproducibility. In particular, the new tool provides more accurate and more consistent estimates of the parameters of the diffusion term....

Brownian motion model with stochastic parameters for asset prices

Science.gov (United States)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.

Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations

Science.gov (United States)

Samoilov, Michael; Plyasunov, Sergey; Arkin, Adam P.

2005-02-01

Stochastic effects in biomolecular systems have now been recognized as a major physiologically and evolutionarily important factor in the development and function of many living organisms. Nevertheless, they are often thought of as providing only moderate refinements to the behaviors otherwise predicted by the classical deterministic system description. In this work we show by using both analytical and numerical investigation that at least in one ubiquitous class of (bio)chemical-reaction mechanisms, enzymatic futile cycles, the external noise may induce a bistable oscillatory (dynamic switching) behavior that is both quantitatively and qualitatively different from what is predicted or possible deterministically. We further demonstrate that the noise required to produce these distinct properties can itself be caused by a set of auxiliary chemical reactions, making it feasible for biological systems of sufficient complexity to generate such behavior internally. This new stochastic dynamics then serves to confer additional functional modalities on the enzymatic futile cycle mechanism that include stochastic amplification and signaling, the characteristics of which could be controlled by both the type and parameters of the driving noise. Hence, such noise-induced phenomena may, among other roles, potentially offer a novel type of control mechanism in pathways that contain these cycles and the like units. In particular, observations of endogenous or externally driven noise-induced dynamics in regulatory networks may thus provide additional insight into their topology, structure, and kinetics. network motif | signal transduction | chemical reaction | synthetic biology | systems biology

Multilevel resonance parameters of 241Pu

International Nuclear Information System (INIS)

Weston, L.W.; Todd, J.H.

1978-01-01

The data previously reported by the authors on the neutron fission and capture cross sections of 241 Pu were simultaneously fit with the Adler formalism to obtain multilevel resonance parameters. The neutron energy range of the fit was 0.01 to 100 eV. The 241 Pu cross sections in the resonance region of neutron energies are complex, and the Adler parameters present an efficient method of representing these cross sections, which are important for plutonium-fueled reactors. The parameters represent the data to an accuracy within the quoted experimental errors. 5 figures, 2 tables

Influence of resonance parameters' correlations on the resonance integral uncertainty; 55Mn case

International Nuclear Information System (INIS)

Zerovnik, Gasper; Trkov, Andrej; Capote, Roberto; Rochman, Dimitri

2011-01-01

For nuclides with a large number of resonances the covariance matrix of resonance parameters can become very large and expensive to process in terms of the computation time. By converting covariance matrix of resonance parameters into covariance matrices of background cross-section in a more or less coarse group structure a considerable amount of computer time and memory can be saved. The question is how important is the information that is discarded in the process. First, the uncertainty of the 55 Mn resonance integral was estimated in narrow resonance approximation for different levels of self-shielding using Bondarenko method by random sampling of resonance parameters according to their covariance matrices from two different 55 Mn evaluations: one from Nuclear Research and Consultancy Group NRG (with large uncertainties but no correlations between resonances), the other from Oak Ridge National Laboratory (with smaller uncertainties but full covariance matrix). We have found out that if all (or at least significant part of the) resonance parameters are correlated, the resonance integral uncertainty greatly depends on the level of self-shielding. Second, it was shown that the commonly used 640-group SAND-II representation cannot describe the increase of the resonance integral uncertainty. A much finer energy mesh for the background covariance matrix would have to be used to take the resonance structure into account explicitly, but then the objective of a more compact data representation is lost.

New evaluation of 238U neutron resonance parameters

International Nuclear Information System (INIS)

Derrien, Herve; Leal, Luiz C.; Larson, Nancy M.

2003-01-01

The neutron resonance parameters of 238 U were obtained in the energy range 1 keV to 20 keV from a SAMMY Reich-Moore analysis of high resolution transmission measurements performed at ORELA. In the energy range 1 keV to 10 keV, the analysis used as prior values the ENDF/B-VI resonance parameters. The analysis in the energy range 10 keV to 20 keV resulted in the creation of a set of resonance parameters for the representation of the cross section in this energy range. The results are compared to the ENDF/B-VI evaluation. Some statistical properties of the new resonance parameters are examined. (author)

Effects of error feedback on a nonlinear bistable system with stochastic resonance

International Nuclear Information System (INIS)

Li Jian-Long; Zhou Hui

2012-01-01

In this paper, we discuss the effects of error feedback on the output of a nonlinear bistable system with stochastic resonance. The bit error rate is employed to quantify the performance of the system. The theoretical analysis and the numerical simulation are presented. By investigating the performances of the nonlinear systems with different strengths of error feedback, we argue that the presented system may provide guidance for practical nonlinear signal processing

Stochastic resonance and the evolution of Daphnia foraging strategy

International Nuclear Information System (INIS)

Dees, Nathan D; Bahar, Sonya; Moss, Frank

2008-01-01

Search strategies are currently of great interest, with reports on foraging ranging from albatrosses and spider monkeys to microzooplankton. Here, we investigate the role of noise in optimizing search strategies. We focus on the zooplankton Daphnia, which move in successive sequences consisting of a hop, a pause and a turn through an angle. Recent experiments have shown that their turning angle distributions (TADs) and underlying noise intensities are similar across species and age groups, suggesting an evolutionary origin of this internal noise. We explore this hypothesis further with a digital simulation (EVO) based solely on the three central Darwinian themes: inheritability, variability and survivability. Separate simulations utilizing stochastic resonance (SR) indicate that foraging success, and hence fitness, is maximized at an optimum TAD noise intensity, which is represented by the distribution's characteristic width, σ. In both the EVO and SR simulations, foraging success is the criterion, and the results are the predicted characteristic widths of the TADs that maximize success. Our results are twofold: (1) the evolving characteristic widths achieve stasis after many generations; (2) as a hop length parameter is changed, variations in the evolved widths generated by EVO parallel those predicted by SR. These findings provide support for the hypotheses that (1) σ is an evolved quantity and that (2) SR plays a role in evolution. (communication)

Stochastic population oscillations in spatial predator-prey models

International Nuclear Information System (INIS)

Taeuber, Uwe C

2011-01-01

It is well-established that including spatial structure and stochastic noise in models for predator-prey interactions invalidates the classical deterministic Lotka-Volterra picture of neutral population cycles. In contrast, stochastic models yield long-lived, but ultimately decaying erratic population oscillations, which can be understood through a resonant amplification mechanism for density fluctuations. In Monte Carlo simulations of spatial stochastic predator-prey systems, one observes striking complex spatio-temporal structures. These spreading activity fronts induce persistent correlations between predators and prey. In the presence of local particle density restrictions (finite prey carrying capacity), there exists an extinction threshold for the predator population. The accompanying continuous non-equilibrium phase transition is governed by the directed-percolation universality class. We employ field-theoretic methods based on the Doi-Peliti representation of the master equation for stochastic particle interaction models to (i) map the ensuing action in the vicinity of the absorbing state phase transition to Reggeon field theory, and (ii) to quantitatively address fluctuation-induced renormalizations of the population oscillation frequency, damping, and diffusion coefficients in the species coexistence phase.

Enhancement of ohmic and stochastic heating by resonance effects in capacitive radio frequency discharges: a theoretical approach.

Science.gov (United States)

Mussenbrock, T; Brinkmann, R P; Lieberman, M A; Lichtenberg, A J; Kawamura, E

2008-08-22

In low-pressure capacitive radio frequency discharges, two mechanisms of electron heating are dominant: (i) Ohmic heating due to collisions of electrons with neutrals of the background gas and (ii) stochastic heating due to momentum transfer from the oscillating boundary sheath. In this work we show by means of a nonlinear global model that the self-excitation of the plasma series resonance which arises in asymmetric capacitive discharges due to nonlinear interaction of plasma bulk and sheath significantly affects both Ohmic heating and stochastic heating. We observe that the series resonance effect increases the dissipation by factors of 2-5. We conclude that the nonlinear plasma dynamics should be taken into account in order to describe quantitatively correct electron heating in asymmetric capacitive radio frequency discharges.

Parameter estimation in a simple stochastic differential equation for phytoplankton modelling

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Madsen, Henrik; Carstensen, Jacob

2011-01-01

The use of stochastic differential equations (SDEs) for simulation of aquatic ecosystems has attracted increasing attention in recent years. The SDE setting also provides the opportunity for statistical estimation of ecosystem parameters. We present an estimation procedure, based on Kalman...

Stochastic volatility and stochastic leverage

DEFF Research Database (Denmark)

Veraart, Almut; Veraart, Luitgard A. M.

This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...

Stochastic analysis of uncertain thermal parameters for random thermal regime of frozen soil around a single freezing pipe

Science.gov (United States)

Wang, Tao; Zhou, Guoqing; Wang, Jianzhou; Zhou, Lei

2018-03-01

The artificial ground freezing method (AGF) is widely used in civil and mining engineering, and the thermal regime of frozen soil around the freezing pipe affects the safety of design and construction. The thermal parameters can be truly random due to heterogeneity of the soil properties, which lead to the randomness of thermal regime of frozen soil around the freezing pipe. The purpose of this paper is to study the one-dimensional (1D) random thermal regime problem on the basis of a stochastic analysis model and the Monte Carlo (MC) method. Considering the uncertain thermal parameters of frozen soil as random variables, stochastic processes and random fields, the corresponding stochastic thermal regime of frozen soil around a single freezing pipe are obtained and analyzed. Taking the variability of each stochastic parameter into account individually, the influences of each stochastic thermal parameter on stochastic thermal regime are investigated. The results show that the mean temperatures of frozen soil around the single freezing pipe with three analogy method are the same while the standard deviations are different. The distributions of standard deviation have a great difference at different radial coordinate location and the larger standard deviations are mainly at the phase change area. The computed data with random variable method and stochastic process method have a great difference from the measured data while the computed data with random field method well agree with the measured data. Each uncertain thermal parameter has a different effect on the standard deviation of frozen soil temperature around the single freezing pipe. These results can provide a theoretical basis for the design and construction of AGF.

Stochasticity of the energy absorption in the electron cyclotron resonance; Estocasticidad de la absorcion de energia en la resonancia electron-ciclotronica

Energy Technology Data Exchange (ETDEWEB)

Gutierrez T, C. [Departamento de Fisica, ININ, A.P. 18-1027, 11801 Mexico D.F. (Mexico); Hernandez A, O

1998-07-01

The energy absorption mechanism in cyclotron resonance of the electrons is a present problem, since it could be considered from the stochastic point of view or this related with a non-homogeneous but periodical of plasma spatial structure. In this work using the Bogoliubov average method for a multi periodical system in presence of resonances, the drift equations were obtained in presence of a RF field for the case of electron cyclotron resonance until first order terms with respect to inverse of its cyclotron frequency. The absorbed energy equation is obtained on part of electrons in a simple model and by drift method. It is showed the stochastic character of the energy absorption. (Author)

Resonances and anti-resonances in the material parameters of 2-D dielectric ENG, MNG, and DNG materials

DEFF Research Database (Denmark)

Wu, Yunqiu; Arslanagic, Samel

The resonant/anti-resonant behavior of parameters extracted by the S-parameter method for two-dimensional epsilon-, mu- and double-negative (ENG, MNG, DNG) materials is investigated. The unit cells consist of infinite dielectric cylinders supporting electric dipole, magnetic dipole, or both....... It is shown that the extraction procedure yields one resonant material parameter, and one anti-resonant material parameter in MNG and ENG configurations. However, both parameters display an over-all resonant response in DNG configurations where electric and magnetic dipole modes are excited simultaneously....

Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

Gershgorin, B.; Harlim, J.; Majda, A.J.

2010-01-01

The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates

Prediction of interest rate using CKLS model with stochastic parameters

International Nuclear Information System (INIS)

Ying, Khor Chia; Hin, Pooi Ah

2014-01-01

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ (j) of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ (j) , we assume that φ (j) depends on φ (j−m) , φ (j−m+1) ,…, φ (j−1) and the interest rate r j+n at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r j+n+1 of the interest rate at the next time point when the value r j+n of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r j+n+d at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters

Prediction of interest rate using CKLS model with stochastic parameters

Energy Technology Data Exchange (ETDEWEB)

Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)

2014-06-19

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.

Stochastic heating in the cyclotron resonance of electrons; Calentamiento estocastico en la resonancia ciclotronica de los electrones

Energy Technology Data Exchange (ETDEWEB)

Gutierrez T, C.; Hernandez A, O. [Instituto Nacional de Investigaciones Nucleares, A.P. 18-1027, 11801 Mexico D.F. (Mexico)

1999-07-01

The study of the different schemes of plasma heating by radiofrequency waves is a very actual problem related with the plasma heating in different machines and the particle acceleration mechanisms. In this work, it is obtained the expression for the temporal evolution of the energy absorbed in the cyclotron resonance of electrons where it is showed the stochastic character of the energy absorption. It is obtained the stochastic criteria in a magnetic configuration of an Ecr type plasma source. (Author)

Pacemaker-driven stochastic resonance on diffusive and complex networks of bistable oscillators

Energy Technology Data Exchange (ETDEWEB)

Perc, Matjaz; Gosak, Marko [Department of Physics, Faculty of Natural Sciences and Mathematics, University of Maribor, Koroska cesta 160, SI-2000 Maribor (Slovenia)], E-mail: matjaz.perc@uni-mb.si

2008-05-15

We study the phenomenon of stochastic resonance on diffusive, small-world and scale-free networks consisting of bistable overdamped oscillators. Important thereby is the fact that the external subthreshold periodic forcing is introduced only to a single oscillator of the network. Hence, the forcing acts as a pacemaker trying to impose its rhythm on the whole network through the unit to which it is introduced. Without the addition of additive spatiotemporal noise, however, the whole network, including the unit that is directly exposed to the pacemaker, remains trapped forever in one of the two stable steady states of the local dynamics. We show that the correlation between the frequency of subthreshold pacemaker activity and the response of the network is resonantly dependent on the intensity of additive noise. The reported pacemaker-driven stochastic resonance depends most significantly on the coupling strength and the underlying network structure. Namely, the outreach of the pacemaker obeys the classic diffusion law in the case of nearest-neighbor interactions, thus being proportional to the square root of the coupling strength, whereas it becomes superdiffusive by an appropriate small-world or scale-free topology of the interaction network. In particular, the scale-free topology is identified as being optimal for the dissemination of localized rhythmic activity across the whole network. Also, we show that the ratio between the clustering coefficient and the characteristic path length is the crucial quantity defining the ability of a small-world network to facilitate the outreach of the pacemaker-emitted subthreshold rhythm. We additionally confirm these findings by using the FitzHugh-Nagumo excitable system as an alternative to the bistable overdamped oscillator.

Pacemaker-driven stochastic resonance on diffusive and complex networks of bistable oscillators

International Nuclear Information System (INIS)

Perc, Matjaz; Gosak, Marko

2008-01-01

We study the phenomenon of stochastic resonance on diffusive, small-world and scale-free networks consisting of bistable overdamped oscillators. Important thereby is the fact that the external subthreshold periodic forcing is introduced only to a single oscillator of the network. Hence, the forcing acts as a pacemaker trying to impose its rhythm on the whole network through the unit to which it is introduced. Without the addition of additive spatiotemporal noise, however, the whole network, including the unit that is directly exposed to the pacemaker, remains trapped forever in one of the two stable steady states of the local dynamics. We show that the correlation between the frequency of subthreshold pacemaker activity and the response of the network is resonantly dependent on the intensity of additive noise. The reported pacemaker-driven stochastic resonance depends most significantly on the coupling strength and the underlying network structure. Namely, the outreach of the pacemaker obeys the classic diffusion law in the case of nearest-neighbor interactions, thus being proportional to the square root of the coupling strength, whereas it becomes superdiffusive by an appropriate small-world or scale-free topology of the interaction network. In particular, the scale-free topology is identified as being optimal for the dissemination of localized rhythmic activity across the whole network. Also, we show that the ratio between the clustering coefficient and the characteristic path length is the crucial quantity defining the ability of a small-world network to facilitate the outreach of the pacemaker-emitted subthreshold rhythm. We additionally confirm these findings by using the FitzHugh-Nagumo excitable system as an alternative to the bistable overdamped oscillator

'PSA-SPN' - A Parameter Sensitivity Analysis Method Using Stochastic Petri Nets: Application to a Production Line System

International Nuclear Information System (INIS)

Labadi, Karim; Saggadi, Samira; Amodeo, Lionel

2009-01-01

The dynamic behavior of a discrete event dynamic system can be significantly affected for some uncertain changes in its decision parameters. So, parameter sensitivity analysis would be a useful way in studying the effects of these changes on the system performance. In the past, the sensitivity analysis approaches are frequently based on simulation models. In recent years, formal methods based on stochastic process including Markov process are proposed in the literature. In this paper, we are interested in the parameter sensitivity analysis of discrete event dynamic systems by using stochastic Petri nets models as a tool for modelling and performance evaluation. A sensitivity analysis approach based on stochastic Petri nets, called PSA-SPN method, will be proposed with an application to a production line system.

Compton harmonic resonances, stochastic instabilities, quasilinear diffusion, and collisionless damping with ultra-high intensity laser waves

International Nuclear Information System (INIS)

Rax, J.M.

1992-04-01

The dynamics of electrons in two-dimensional, linearly or circularly polarized, ultra-high intensity (above 10 18 W/cm 2 ) laser waves, is investigated. The Compton harmonic resonances are identified as the source of various stochastic instabilities. Both Arnold diffusion and resonance overlap are considered. The quasilinear kinetic equation, describing the evolution of the electron distribution function, is derived, and the associated collisionless damping coefficient is calculated. The implications of these new processes are considered and discussed

Alfven-wave current drive and magnetic field stochasticity

International Nuclear Information System (INIS)

Litwin, C.; Hegna, C.C.

1993-01-01

Propagating Alfven waves can generate parallel current through an alpha effect. In resistive MHD however, the dynamo field is proportional to resistivity and as such cannot drive significant currents for realistic parameters. In the search for an enhancement of this effect the authors investigate the role of magnetic field stochasticity. They show that the presence of a stochastic magnetic field, either spontaneously generated by instabilities or induced externally, can enhance the alpha effect of the wave. This enhancement is caused by an increased wave dissipation due to both current diffusion and filamentation. For the range of parameters of current drive experiments at Phaedrus-T tokamak, a moderate field stochasticity leads to significant modifications in the loop voltage

Stochastic multiresonance in coupled excitable FHN neurons

Science.gov (United States)

Li, Huiyan; Sun, Xiaojuan; Xiao, Jinghua

2018-04-01

In this paper, effects of noise on Watts-Strogatz small-world neuronal networks, which are stimulated by a subthreshold signal, have been investigated. With the numerical simulations, it is surprisingly found that there exist several optimal noise intensities at which the subthreshold signal can be detected efficiently. This indicates the occurrence of stochastic multiresonance in the studied neuronal networks. Moreover, it is revealed that the occurrence of stochastic multiresonance has close relationship with the period of subthreshold signal Te and the noise-induced mean period of the neuronal networks T0. In detail, we find that noise could induce the neuronal networks to generate stochastic resonance for M times if Te is not very large and falls into the interval ( M × T 0 , ( M + 1 ) × T 0 ) with M being a positive integer. In real neuronal system, subthreshold signal detection is very meaningful. Thus, the obtained results in this paper could give some important implications on detecting subthreshold signal and propagating neuronal information in neuronal systems.

Gearbox damage identification and quantification using stochastic resonance

Science.gov (United States)

Mba, Clement U.; Marchesiello, Stefano; Fasana, Alessandro; Garibaldi, Luigi

2018-03-01

Amongst the many new tools used for vibration based mechanical fault diagnosis in rotating machineries, stochastic resonance (SR) has been shown to be able to identify as well as quantify gearbox damage via numerical simulations. To validate the numerical simulation results that were obtained in a previous work by the authors, SR is applied in the present study to data from an experimental gearbox that is representative of an industrial gearbox. Both spur and helical gears are used in the gearbox setup. While the results of the direct application of SR to experimental data do not exactly corroborate the numerical simulation results, applying SR to experimental data in pre-processed form is shown to be quite effective. In addition, it is demonstrated that traditional statistical techniques used for gearbox diagnosis can be used as a reference to check how well SR performs.

Exponential Synchronization for Stochastic Neural Networks with Mixed Time Delays and Markovian Jump Parameters via Sampled Data

Directory of Open Access Journals (Sweden)

Yingwei Li

2014-01-01

Full Text Available The exponential synchronization issue for stochastic neural networks (SNNs with mixed time delays and Markovian jump parameters using sampled-data controller is investigated. Based on a novel Lyapunov-Krasovskii functional, stochastic analysis theory, and linear matrix inequality (LMI approach, we derived some novel sufficient conditions that guarantee that the master systems exponentially synchronize with the slave systems. The design method of the desired sampled-data controller is also proposed. To reflect the most dynamical behaviors of the system, both Markovian jump parameters and stochastic disturbance are considered, where stochastic disturbances are given in the form of a Brownian motion. The results obtained in this paper are a little conservative comparing the previous results in the literature. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.

The Effect of Stochastically Varying Creep Parameters on Residual Stresses in Ceramic Matrix Composites

Science.gov (United States)

Pineda, Evan J.; Mital, Subodh K.; Bednarcyk, Brett A.; Arnold, Steven M.

2015-01-01

Constituent properties, along with volume fraction, have a first order effect on the microscale fields within a composite material and influence the macroscopic response. Therefore, there is a need to assess the significance of stochastic variation in the constituent properties of composites at the higher scales. The effect of variability in the parameters controlling the time-dependent behavior, in a unidirectional SCS-6 SiC fiber-reinforced RBSN matrix composite lamina, on the residual stresses induced during processing is investigated numerically. The generalized method of cells micromechanics theory is utilized to model the ceramic matrix composite lamina using a repeating unit cell. The primary creep phases of the constituents are approximated using a Norton-Bailey, steady state, power law creep model. The effect of residual stresses on the proportional limit stress and strain to failure of the composite is demonstrated. Monte Carlo simulations were conducted using a normal distribution for the power law parameters and the resulting residual stress distributions were predicted.

Systematic parameter inference in stochastic mesoscopic modeling

Energy Technology Data Exchange (ETDEWEB)

Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

A Geršgorin-type eigenvalue localization set with n parameters for stochastic matrices

Directory of Open Access Journals (Sweden)

Wang Xiaoxiao

2018-04-01

Full Text Available A set in the complex plane which involves n parameters in [0, 1] is given to localize all eigenvalues different from 1 for stochastic matrices. As an application of this set, an upper bound for the moduli of the subdominant eigenvalues of a stochastic matrix is obtained. Lastly, we fix n parameters in [0, 1] to give a new set including all eigenvalues different from 1, which is tighter than those provided by Shen et al. (Linear Algebra Appl. 447 (2014 74-87 and Li et al. (Linear and Multilinear Algebra 63(11 (2015 2159-2170 for estimating the moduli of subdominant eigenvalues.

Stochastic stability analysis for delayed neural networks of neutral type with Markovian jump parameters

International Nuclear Information System (INIS)

Lou Xuyang; Cui Baotong

2009-01-01

In this paper, the problem of stochastic stability for a class of delayed neural networks of neutral type with Markovian jump parameters is investigated. The jumping parameters are modelled as a continuous-time, discrete-state Markov process. A sufficient condition guaranteeing the stochastic stability of the equilibrium point is derived for the Markovian jumping delayed neural networks (MJDNNs) with neutral type. The stability criterion not only eliminates the differences between excitatory and inhibitory effects on the neural networks, but also can be conveniently checked. The sufficient condition obtained can be essentially solved in terms of linear matrix inequality. A numerical example is given to show the effectiveness of the obtained results.

An iterative stochastic ensemble method for parameter estimation of subsurface flow models

International Nuclear Information System (INIS)

Elsheikh, Ahmed H.; Wheeler, Mary F.; Hoteit, Ibrahim

2013-01-01

Parameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss–Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates

An iterative stochastic ensemble method for parameter estimation of subsurface flow models

KAUST Repository

Elsheikh, Ahmed H.

2013-06-01

Parameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss-Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates. © 2013 Elsevier Inc.

Neutron resonance parameters of CM isotopes

International Nuclear Information System (INIS)

Belanova, T.S.; Kolesov, A.G.; Poruchikov, V.A.

1977-01-01

The total neutron cross sections of isotopes 244, 245, 246, 248 Curium have been measured on reactor CM-2 using the time-of-flight method. Single-level Breit-Wigner resonance parameters: energy E 0 , neutron width 2g GITAn, total width GITA, total neutron cross section in resonance sigma 0 have been obtained by the shape and area methods

Exact solutions to chaotic and stochastic systems

Science.gov (United States)

González, J. A.; Reyes, L. I.; Guerrero, L. E.

2001-03-01

We investigate functions that are exact solutions to chaotic dynamical systems. A generalization of these functions can produce truly random numbers. For the first time, we present solutions to random maps. This allows us to check, analytically, some recent results about the complexity of random dynamical systems. We confirm the result that a negative Lyapunov exponent does not imply predictability in random systems. We test the effectiveness of forecasting methods in distinguishing between chaotic and random time series. Using the explicit random functions, we can give explicit analytical formulas for the output signal in some systems with stochastic resonance. We study the influence of chaos on the stochastic resonance. We show, theoretically, the existence of a new type of solitonic stochastic resonance, where the shape of the kink is crucial. Using our models we can predict specific patterns in the output signal of stochastic resonance systems.

Conductance with stochastic resonance in Mn{sub 12} redox network without tuning

Energy Technology Data Exchange (ETDEWEB)

Hirano, Yoshiaki [Department of Chemistry, Graduate School of Science, Osaka University, 1-1 Machikaneyama-cho, Toyonaka, Osaka 560-0043 (Japan); Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507 (Japan); Segawa, Yuji; Kawai, Tomoji [Institute of Scientific and Industrial Research (ISIR), Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047 (Japan); Kuroda-Sowa, Takayoshi [Department of Chemistry, Faculty of Science and Engineering, Kinki University, 3-4-1 Kowakae, Higashi-Osaka, Osaka 577-8502 (Japan); Matsumoto, Takuya, E-mail: matsumoto-t@chem.sci.osaka-u.ac.jp [Department of Chemistry, Graduate School of Science, Osaka University, 1-1 Machikaneyama-cho, Toyonaka, Osaka 560-0043 (Japan)

2014-06-09

Artificial neuron-based information processing is one of the attractive approaches of molecular-scale electronics, which can exploit the ability of molecular system for self-assembling or self-organization. The self-organized Mn{sub 12}/DNA redox network shows nonlinear current-voltage characteristics that can be described by the Coulomb blockade network model. As a demonstration of the nonlinear network system, we have observed stochastic resonance without tuning for weak periodic input signals and thermal noise, which suggests a route to neural network composed of molecular materials.

Identification of a Discontinuous Parameter in Stochastic Parabolic Systems

International Nuclear Information System (INIS)

Aihara, S. I.

1998-01-01

The purpose of this paper is to study the identification problem for a spatially varying discontinuous parameter in stochastic diffusion equations. The consistency property of the maximum likelihood estimate (M.L.E.) and a generating algorithm for M.L.E. have been explored under the condition that the unknown parameter is in a sufficiently regular space with respect to spatial variables. In order to prove the consistency property of the M.L.E. for a discontinuous diffusion coefficient, we use the method of sieves, i.e., first the admissible class of unknown parameters is projected into a finite-dimensional space and next the convergence of the derived finite-dimensional M.L.E. to the infinite-dimensional M.L.E. is justified under some conditions. An iterative algorithm for generating the M.L.E. is also proposed with two numerical examples

Stochastic interaction between TAE and alpha particles

International Nuclear Information System (INIS)

Krlin, L.; Pavlo, P.; Malijevsky, I.

1996-01-01

The interaction of toroidicity-induced Alfven eigenmodes with thermonuclear alpha particles in the intrinsic stochasticity regime was investigated based on the numerical integration of the equation of motion of alpha particles in the tokamak. The first results obtained for the ITER parameters and moderate wave amplitudes indicate that the stochasticity is highest in the trapped/passing boundary region, where the alpha particles jump stochastically between the two regimes with an appreciable radial excursion (about 0.5 m amplitudes). A similar chaotic behavior was also found for substantially lower energies (about 350 keV). 7 figs., 15 refs

Stochastic exponential stability of the delayed reaction-diffusion recurrent neural networks with Markovian jumping parameters

International Nuclear Information System (INIS)

Wang Linshan; Zhang Zhe; Wang Yangfan

2008-01-01

Some criteria for the global stochastic exponential stability of the delayed reaction-diffusion recurrent neural networks with Markovian jumping parameters are presented. The jumping parameters considered here are generated from a continuous-time discrete-state homogeneous Markov process, which are governed by a Markov process with discrete and finite state space. By employing a new Lyapunov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish some easy-to-test criteria of global exponential stability in the mean square for the stochastic neural networks. The criteria are computationally efficient, since they are in the forms of some linear matrix inequalities

Simulation of Higher-Order Electrical Circuits with Stochastic Parameters via SDEs

Directory of Open Access Journals (Sweden)

BRANCIK, L.

2013-02-01

Full Text Available The paper deals with a technique for the simulation of higher-order electrical circuits with parameters varying randomly. The principle consists in the utilization of the theory of stochastic differential equations (SDE, namely the vector form of the ordinary SDEs. Random changes of both excitation voltage and some parameters of passive circuit elements are considered, and circuit responses are analyzed. The voltage and/or current responses are computed and represented in the form of the sample means accompanied by their confidence intervals to provide reliable estimates. The method is applied to analyze responses of the circuit models of optional orders, specially those consisting of a cascade connection of the RLGC networks. To develop the model equations the state-variable method is used, afterwards a corresponding vector SDE is formulated and a stochastic Euler numerical method applied. To verify the results the deterministic responses are also computed by the help of the PSpice simulator or the numerical inverse Laplace transforms (NILT procedure in MATLAB, while removing random terms from the circuit model.

Estimating the parameters of stochastic differential equations using a criterion function based on the Kolmogorov-Smirnov statistic

OpenAIRE

McDonald, A. David; Sandal, Leif Kristoffer

1998-01-01

Estimation of parameters in the drift and diffusion terms of stochastic differential equations involves simulation and generally requires substantial data sets. We examine a method that can be applied when available time series are limited to less than 20 observations per replication. We compare and contrast parameter estimation for linear and nonlinear first-order stochastic differential equations using two criterion functions: one based on a Chi-square statistic, put forward by Hurn and Lin...

Boosting Bayesian parameter inference of nonlinear stochastic differential equation models by Hamiltonian scale separation.

Science.gov (United States)

Albert, Carlo; Ulzega, Simone; Stoop, Ruedi

2016-04-01

Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In many situations, the dominant sources of uncertainty must be included into the model for making reliable predictions. This naturally leads to stochastic models. Stochastic models render parameter inference much harder, as the aim then is to find a distribution of likely parameter values. In Bayesian statistics, which is a consistent framework for data-driven learning, this so-called posterior distribution can be used to make probabilistic predictions. We propose a novel, exact, and very efficient approach for generating posterior parameter distributions for stochastic differential equation models calibrated to measured time series. The algorithm is inspired by reinterpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, where the measurements are mapped on heavier beads compared to those of the simulated data. To arrive at distribution samples, we employ a Hamiltonian Monte Carlo approach combined with a multiple time-scale integration. A separation of time scales naturally arises if either the number of measurement points or the number of simulation points becomes large. Furthermore, at least for one-dimensional problems, we can decouple the harmonic modes between measurement points and solve the fastest part of their dynamics analytically. Our approach is applicable to a wide range of inference problems and is highly parallelizable.

Dissipative Double-Well Potential for Cold Atoms: Kramers Rate and Stochastic Resonance.

Science.gov (United States)

Stroescu, Ion; Hume, David B; Oberthaler, Markus K

2016-12-09

We experimentally study particle exchange in a dissipative double-well potential using laser-cooled atoms in a hybrid trap. We measure the particle hopping rate as a function of barrier height, temperature, and atom number. Single-particle resolution allows us to measure rates over more than 4 orders of magnitude and distinguish the effects of loss and hopping. Deviations from the Arrhenius-law scaling at high barrier heights occur due to cold collisions between atoms within a well. By driving the system periodically, we characterize the phenomenon of stochastic resonance in the system response.

Nonlinear stochastic systems with network-induced phenomena recursive filtering and sliding-mode design

CERN Document Server

Hu, Jun; Gao, Huijun

2014-01-01

This monograph introduces methods for handling filtering and control problems in nonlinear stochastic systems arising from network-induced phenomena consequent on limited communication capacity. Such phenomena include communication delay, packet dropout, signal quantization or saturation, randomly occurring nonlinearities and randomly occurring uncertainties.The text is self-contained, beginning with an introduction to nonlinear stochastic systems, network-induced phenomena and filtering and control, moving through a collection of the latest research results which focuses on the three aspects

A Langevin Canonical Approach to the Study of Quantum Stochastic Resonance in Chiral Molecules

Directory of Open Access Journals (Sweden)

Germán Rojas-Lorenzo

2016-09-01

Full Text Available A Langevin canonical framework for a chiral two-level system coupled to a bath of harmonic oscillators is used within a coupling scheme different from the well-known spin-boson model to study the quantum stochastic resonance for chiral molecules. This process refers to the amplification of the response to an external periodic signal at a certain value of the noise strength, being a cooperative effect of friction, noise, and periodic driving occurring in a bistable system. Furthermore, from this stochastic dynamics within the Markovian regime and Ohmic friction, the competing process between tunneling and the parity violating energy difference present in this type of chiral systems plays a fundamental role. This mechanism is finally proposed to observe the so-far elusive parity-violating energy difference in chiral molecules.

An Interval-Parameter Fuzzy Linear Programming with Stochastic Vertices Model for Water Resources Management under Uncertainty

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Yan Han

2013-01-01

Full Text Available An interval-parameter fuzzy linear programming with stochastic vertices (IFLPSV method is developed for water resources management under uncertainty by coupling interval-parameter fuzzy linear programming (IFLP with stochastic programming (SP. As an extension of existing interval parameter fuzzy linear programming, the developed IFLPSV approach has advantages in dealing with dual uncertainty optimization problems, which uncertainty presents as interval parameter with stochastic vertices in both of the objective functions and constraints. The developed IFLPSV method improves upon the IFLP method by allowing dual uncertainty parameters to be incorporated into the optimization processes. A hybrid intelligent algorithm based on genetic algorithm and artificial neural network is used to solve the developed model. The developed method is then applied to water resources allocation in Beijing city of China in 2020, where water resources shortage is a challenging issue. The results indicate that reasonable solutions have been obtained, which are helpful and useful for decision makers. Although the amount of water supply from Guanting and Miyun reservoirs is declining with rainfall reduction, water supply from the South-to-North Water Transfer project will have important impact on water supply structure of Beijing city, particularly in dry year and extraordinary dry year.

Stochastic resonance in an ensemble of single-electron neuromorphic devices and its application to competitive neural networks

International Nuclear Information System (INIS)

Oya, Takahide; Asai, Tetsuya; Amemiya, Yoshihito

2007-01-01

Neuromorphic computing based on single-electron circuit technology is gaining prominence because of its massively increased computational efficiency and the increasing relevance of computer technology and nanotechnology [Likharev K, Mayr A, Muckra I, Tuerel O. CrossNets: High-performance neuromorphic architectures for CMOL circuits. Molec Electron III: Ann NY Acad Sci 1006;2003:146-63; Oya T, Schmid A, Asai T, Leblebici Y, Amemiya Y. On the fault tolerance of a clustered single-electron neural network for differential enhancement. IEICE Electron Expr 2;2005:76-80]. The maximum impact of these technologies will be strongly felt when single-electron circuits based on fault- and noise-tolerant neural structures can operate at room temperature. In this paper, inspired by stochastic resonance (SR) in an ensemble of spiking neurons [Collins JJ, Chow CC, Imhoff TT. Stochastic resonance without tuning. Nature 1995;376:236-8], we propose our design of a basic single-electron neural component and report how we examined its statistical results on a network

Exhibition of Stochastic Resonance in Vestibular Perception

Science.gov (United States)

Galvan-Garza, R. C.; Clark, T. K.; Merfeld, D. M.; Bloomberg, J. J.; Oman, C. M.; Mulavara, A. P.

2016-01-01

Astronauts experience sensorimotor changes during spaceflight, particularly during G-transitions. Post flight sensorimotor changes include spatial disorientation, along with postural and gait instability that may degrade operational capabilities of the astronauts and endanger the crew. A sensorimotor countermeasure that mitigates these effects would improve crewmember safety and decrease risk. The goal of this research is to investigate the potential use of stochastic vestibular stimulation (SVS) as a technology to improve sensorimotor function. We hypothesize that low levels of SVS will improve sensorimotor perception through the phenomenon of stochastic resonance (SR), when the response of a nonlinear system to a weak input signal is enhanced by the application of a particular nonzero level of noise. This study aims to advance the development of SVS as a potential countermeasure by 1) demonstrating the exhibition of stochastic resonance in vestibular perception, a vital component of sensorimotor function, 2) investigating the repeatability of SR exhibition, and 3) determining the relative contribution of the semicircular canals (SCC) and otolith (OTO) organs to vestibular perceptual SR. A constant current stimulator was used to deliver bilateral bipolar SVS via electrodes placed on each of the mastoid processes, as previously done. Vestibular perceptual motion recognition thresholds were measured using a 6-degree of freedom MOOG platform and a 150 trial 3-down/1-up staircase procedure. In the first test session, we measured vestibular perceptual thresholds in upright roll-tilt at 0.2 Hz (SCC+OTO) with SVS ranging from 0-700 µA. In a second test session a week later, we re-measured roll-tilt thresholds with 0, optimal (from test session 1), and 1500 µA SVS levels. A subset of these subjects, plus naive subjects, participated in two additional test sessions in which we measured thresholds in supine roll-rotation at 0.2 Hz (SCC) and upright y-translation at 1 Hz

Mechanisms of Stochastic Diffusion of Energetic Ions in Spherical Tori

Energy Technology Data Exchange (ETDEWEB)

Ya.I. Kolesnichenko; R.B. White; Yu.V. Yakovenko

2001-01-18

Stochastic diffusion of the energetic ions in spherical tori is considered. The following issues are addressed: (I) Goldston-White-Boozer diffusion in a rippled field; (ii) cyclotron-resonance-induced diffusion caused by the ripple; (iii) effects of non-conservation of the magnetic moment in an axisymmetric field. It is found that the stochastic diffusion in spherical tori with a weak magnetic field has a number of peculiarities in comparison with conventional tokamaks; in particular, it is characterized by an increased role of mechanisms associated with non-conservation of the particle magnetic moment. It is concluded that in current experiments on National Spherical Torus eXperiment (NSTX) the stochastic diffusion does not have a considerable influence on the confinement of energetic ions.

The effect of stochasticity on the lac operon: an evolutionary perspective.

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Milan van Hoek

2007-06-01

Full Text Available The role of stochasticity on gene expression is widely discussed. Both potential advantages and disadvantages have been revealed. In some systems, noise in gene expression has been quantified, in among others the lac operon of Escherichia coli. Whether stochastic gene expression in this system is detrimental or beneficial for the cells is, however, still unclear. We are interested in the effects of stochasticity from an evolutionary point of view. We study this question in the lac operon, taking a computational approach: using a detailed, quantitative, spatial model, we evolve through a mutation-selection process the shape of the promoter function and therewith the effective amount of stochasticity. We find that noise values for lactose, the natural inducer, are much lower than for artificial, nonmetabolizable inducers, because these artificial inducers experience a stronger positive feedback. In the evolved promoter functions, noise due to stochasticity in gene expression, when induced by lactose, only plays a very minor role in short-term physiological adaptation, because other sources of population heterogeneity dominate. Finally, promoter functions evolved in the stochastic model evolve to higher repressed transcription rates than those evolved in a deterministic version of the model. This causes these promoter functions to experience less stochasticity in gene expression. We show that a high repression rate and hence high stochasticity increases the delay in lactose uptake in a variable environment. We conclude that the lac operon evolved such that the impact of stochastic gene expression is minor in its natural environment, but happens to respond with much stronger stochasticity when confronted with artificial inducers. In this particular system, we have shown that stochasticity is detrimental. Moreover, we demonstrate that in silico evolution in a quantitative model, by mutating the parameters of interest, is a promising way to unravel

Effects of Colored Noise on Stochastic Resonance in Sensory Neurons

International Nuclear Information System (INIS)

Nozaki, D.; Mar, D.J.; Collins, J.J.; Grigg, P.

1999-01-01

Noise can assist neurons in the detection of weak signals via a mechanism known as stochastic resonance (SR). We demonstrate experimentally that SR-type effects can be obtained in rat sensory neurons with white noise, 1/f noise, or 1/f 2 noise. For low-frequency input noise, we show that the optimal noise intensity is the lowest and the output signal-to-noise ratio the highest for conventional white noise. We also show that under certain circumstances, 1/f noise can be better than white noise for enhancing the response of a neuron to a weak signal. We present a theory to account for these results and discuss the biological implications of 1/f noise. copyright 1999 The American Physical Society

Adaptive Synchronization for Two Different Stochastic Chaotic Systems with Unknown Parameters via a Sliding Mode Controller

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Zengyun Wang

2013-01-01

Full Text Available This paper investigates the problem of synchronization for two different stochastic chaotic systems with unknown parameters and uncertain terms. The main work of this paper consists of the following aspects. Firstly, based on the Lyapunov theory in stochastic differential equations and the theory of sliding mode control, we propose a simple sliding surface and discuss the occurrence of the sliding motion. Secondly, we design an adaptive sliding mode controller to realize the asymptotical synchronization in mean squares. Thirdly, we design an adaptive sliding mode controller to realize the almost surely synchronization. Finally, the designed adaptive sliding mode controllers are used to achieve synchronization between two pairs of different stochastic chaos systems (Lorenz-Chen and Chen-Lu in the presence of the uncertainties and unknown parameters. Numerical simulations are given to demonstrate the robustness and efficiency of the proposed robust adaptive sliding mode controller.

Delay-induced stochastic bifurcations in a bistable system under white noise

International Nuclear Information System (INIS)

Sun, Zhongkui; Fu, Jin; Xu, Wei; Xiao, Yuzhu

2015-01-01

In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses

Delay-induced stochastic bifurcations in a bistable system under white noise

Energy Technology Data Exchange (ETDEWEB)

Sun, Zhongkui, E-mail: sunzk@nwpu.edu.cn; Fu, Jin; Xu, Wei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Xiao, Yuzhu [Department of Mathematics and Information Science, Chang' an University, Xi' an 710086 (China)

2015-08-15

In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses.

Development of a collision induced dissociation ion cyclotron resonance spectrometer

International Nuclear Information System (INIS)

Fan, Y.N.

1982-01-01

A transient analysis ion cyclotron resonance spectrometer is developed to investigate the phenomena of collision induced dissociation. The Fourier transform method and the modified maximum entropy spectral analysis or covariance least square method are implemented in measuring the mass spectrum of the ion ensemble. The Fourier transform method can be used in quantitative analysis while the maximum entropy method as developed here is useful for qualitative analysis only. The cyclotron resonance frequency, relaxation time constant, and the relative ion population are observable from the Fourier transform spectrum. These parameters are very important in investigating collision induced dissociation process and other topics in gas phase chemistry. The ion cyclotron resonance spectrometer is not only developed to study fragments and their abundance from a parent ion, but also to determine the threshold energy and reaction cross section in the collision induced dissociation process. When hard sphere model is used in the ion-molecule collision, the radius of acetone ion measured from the reactive cross section is 2.2 angstrom which is very close to the physical dimension of acetone. The threshold energy for acetone ion in collision induced dissociation process is 1.8 eV which is similar to the result obtained by the angle-resolved mass spectrometer

Stochastic resonance in feedforward acupuncture networks

Science.gov (United States)

Qin, Ying-Mei; Wang, Jiang; Men, Cong; Deng, Bin; Wei, Xi-Le; Yu, Hai-Tao; Chan, Wai-Lok

2014-10-01

Effects of noises and some other network properties on the weak signal propagation are studied systematically in feedforward acupuncture networks (FFN) based on FitzHugh-Nagumo neuron model. It is found that noises with medium intensity can enhance signal propagation and this effect can be further increased by the feedforward network structure. Resonant properties in the noisy network can also be altered by several network parameters, such as heterogeneity, synapse features, and feedback connections. These results may also provide a novel potential explanation for the propagation of acupuncture signal.

Stochastic population dynamics in spatially extended predator-prey systems

Science.gov (United States)

Dobramysl, Ulrich; Mobilia, Mauro; Pleimling, Michel; Täuber, Uwe C.

2018-02-01

Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting many-particle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steady-state and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species’ population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with ‘rock-paper-scissors’ interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex

An illustration of new methods in machine condition monitoring, Part I: stochastic resonance

International Nuclear Information System (INIS)

Worden, K.; Antoniadou, I.; Marchesiello, S.; Mba, C.; Garibaldi, L.

2017-01-01

There have been many recent developments in the application of data-based methods to machine condition monitoring. A powerful methodology based on machine learning has emerged, where diagnostics are based on a two-step procedure: extraction of damage-sensitive features, followed by unsupervised learning (novelty detection) or supervised learning (classification). The objective of the current pair of papers is simply to illustrate one state-of-the-art procedure for each step, using synthetic data representative of reality in terms of size and complexity. The first paper in the pair will deal with feature extraction. Although some papers have appeared in the recent past considering stochastic resonance as a means of amplifying damage information in signals, they have largely relied on ad hoc specifications of the resonator used. In contrast, the current paper will adopt a principled optimisation-based approach to the resonator design. The paper will also show that a discrete dynamical system can provide all the benefits of a continuous system, but also provide a considerable speed-up in terms of simulation time in order to facilitate the optimisation approach. (paper)

A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors

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Hengwei Li

2007-02-01

Full Text Available In this paper, an approach is presented to detect faint signals with strong noises in sensors by stochastic resonance (SR. We adopt the power spectrum as the evaluation tool of SR, which can be obtained by the fast Fourier transform (FFT. Furthermore, we introduce the adaptive filtering scheme to realize signal processing automatically. The key of the scheme is how to adjust the barrier height to satisfy the optimal condition of SR in the presence of any input. For the given input signal, we present an operable procedure to execute the adjustment scheme. An example utilizing one audio sensor to detect the fault information from the power supply is given. Simulation results show that th

Nuclear data adjustment methodology utilizing resonance parameter sensitivities and uncertainties

International Nuclear Information System (INIS)

Broadhead, B.L.

1983-01-01

This work presents the development and demonstration of a Nuclear Data Adjustment Method that allows inclusion of both energy and spatial self-shielding into the adjustment procedure. The resulting adjustments are for the basic parameters (i.e. resonance parameters) in the resonance regions and for the group cross sections elsewhere. The majority of this development effort concerns the production of resonance parameter sensitivity information which allows the linkage between the responses of interest and the basic parameters. The resonance parameter sensitivity methodology developed herein usually provides accurate results when compared to direct recalculations using existng and well-known cross section processing codes. However, it has been shown in several cases that self-shielded cross sections can be very non-linear functions of the basic parameters. For this reason caution must be used in any study which assumes that a linear relatonship exists between a given self-shielded group cross section and its corresponding basic data parameters. The study also has pointed out the need for more approximate techniques which will allow the required sensitivity information to be obtained in a more cost effective manner

Uncertainty calculation for modal parameters used with stochastic subspace identification: an application to a bridge structure

Science.gov (United States)

Hsu, Wei-Ting; Loh, Chin-Hsiung; Chao, Shu-Hsien

2015-03-01

Stochastic subspace identification method (SSI) has been proven to be an efficient algorithm for the identification of liner-time-invariant system using multivariate measurements. Generally, the estimated modal parameters through SSI may be afflicted with statistical uncertainty, e.g. undefined measurement noises, non-stationary excitation, finite number of data samples etc. Therefore, the identified results are subjected to variance errors. Accordingly, the concept of the stabilization diagram can help users to identify the correct model, i.e. through removing the spurious modes. Modal parameters are estimated at successive model orders where the physical modes of the system are extracted and separated from the spurious modes. Besides, an uncertainty computation scheme was derived for the calculation of uncertainty bounds for modal parameters at some given model order. The uncertainty bounds of damping ratios are particularly interesting, as the estimation of damping ratios are difficult to obtain. In this paper, an automated stochastic subspace identification algorithm is addressed. First, the identification of modal parameters through covariance-driven stochastic subspace identification from the output-only measurements is used for discussion. A systematic way of investigation on the criteria for the stabilization diagram is presented. Secondly, an automated algorithm of post-processing on stabilization diagram is demonstrated. Finally, the computation of uncertainty bounds for each mode with all model order in the stabilization diagram is utilized to determine system natural frequencies and damping ratios. Demonstration of this study on the system identification of a three-span steel bridge under operation condition is presented. It is shown that the proposed new operation procedure for the automated covariance-driven stochastic subspace identification can enhance the robustness and reliability in structural health monitoring.

Determination of Intermediate Resonance Parameter with RMET21 for nTRACER

International Nuclear Information System (INIS)

Sohail, Muhammad; Kim, Myung Hyun

2012-01-01

Ray Tracing based code nTRACER is being developed in Seoul National University that has the capability of 3-dimensional whole core neutron transport calculation. As a part of development of multi-group neutron cross section library for nTRACER, the current work is intended to accurately determine intermediate resonance parameters. Beside the systematic calculation of subgroup parameters for resonance self shielding calculation, intermediate resonance parameters itself can be as important as the multi-group neutron cross section in the library and its overall accuracy. In this paper lambda factors were computed using RMET21 from ENDF/B-VII.1 for nTRACER to investigate its dependence on temperature and background cross section and replaced with lambda factors from HELIOS multi-group library. The procedure used for determining the intermediate resonance parameter for the isotope under study is introduced in the next section. Oxygen being one of the primary nuclide in PWR fuel has been selected for intermediate resonance parameters calculation

Phenomenological analysis of the Δ resonance parameters

International Nuclear Information System (INIS)

Vasan, S.S.

1976-01-01

The positions of the poles in the complex energy plane corresponding to the resonances Δ ++ and Δ 0 , and the associated residues, are determined by fitting the π + p and π - p hadronic phase shift data from the CARTER 73 analysis. As an illustration of the use of the Δ pole parameters, their application to the problem of parametrizing the residue function associated with the Δ Regge trajectory is considered. The input for the parametrization is given partly by the pole position and the residue of the Δ(1950), the first recurrence of the Δ(1236). These pole parameters are deduced from fits to the F 37 partial wave data from the AYED 74 phase shift analysis. Together with the Δ(1236) pole parameters, these provide information on the behavior of the Regge residue in the resonance region u less than 0 (in the context of s-channel backward scattering being dominated by u-channel Regge exchanges). Attempts to incorporate this information in parametrizations of the residue by means of real and complex functions lead to the conclusion that both the residue and the trajectory are better represented in the resonance region by complex parametrizations

Resolved resonance parameters for 236Np

International Nuclear Information System (INIS)

Morogovskij, G.B.; Bakhanovich, L.A.

2002-01-01

Multilevel Breit-Wigner parameters were obtained for fission cross-section representation in the 0.01-33 eV energy region from evaluation of a 236 Np experimental fission cross-section in the resolved resonance region. (author)

Channel noise enhances signal detectability in a model of acoustic neuron through the stochastic resonance paradigm.

Science.gov (United States)

Liberti, M; Paffi, A; Maggio, F; De Angelis, A; Apollonio, F; d'Inzeo, G

2009-01-01

A number of experimental investigations have evidenced the extraordinary sensitivity of neuronal cells to weak input stimulations, including electromagnetic (EM) fields. Moreover, it has been shown that biological noise, due to random channels gating, acts as a tuning factor in neuronal processing, according to the stochastic resonant (SR) paradigm. In this work the attention is focused on noise arising from the stochastic gating of ionic channels in a model of Ranvier node of acoustic fibers. The small number of channels gives rise to a high noise level, which is able to cause a spike train generation even in the absence of stimulations. A SR behavior has been observed in the model for the detection of sinusoidal signals at frequencies typical of the speech.

Influence of the Basset force on the resonant behavior of an oscillator with fluctuating frequency

Energy Technology Data Exchange (ETDEWEB)

Rekker, A., E-mail: Astrid.Rekker@tlu.ee; Mankin, R., E-mail: Romi.Mankin@tlu.ee [Institute of Mathematics and Natural Sciences, Tallinn University, 29 Narva Road, 10120 Tallinn (Estonia)

2015-10-28

The influence of hydrodynamic interactions, such as Stokes and Basset forces, on the dynamics of a harmonically trapped Brownian tracer is considered. A generalized Langevin equation is used to describe the tracer’s response to an external periodic force and to dichotomous fluctuations of the stiffness of the trapping potential. Relying on the Shapiro-Loginov formula, exact expressions for the complex susceptibility and for the response function are presented. On the basis of these exact formulas, it is demonstrated that interplay of a multiplicative colored noise and the Basset force induced memory effects can generate a variety of cooperation effects, such as multiresonance versus the driving frequency, as well as stochastic resonance versus noise parameters. In particular, in certain parameter regions the response function exhibits a resonance-like enhancement at intermediate values of the intensity of the Basset force. Conditions for the appearance of these effects are also discussed.

Influence of the Basset force on the resonant behavior of an oscillator with fluctuating frequency

Science.gov (United States)

Rekker, A.; Mankin, R.

2015-10-01

The influence of hydrodynamic interactions, such as Stokes and Basset forces, on the dynamics of a harmonically trapped Brownian tracer is considered. A generalized Langevin equation is used to describe the tracer's response to an external periodic force and to dichotomous fluctuations of the stiffness of the trapping potential. Relying on the Shapiro-Loginov formula, exact expressions for the complex susceptibility and for the response function are presented. On the basis of these exact formulas, it is demonstrated that interplay of a multiplicative colored noise and the Basset force induced memory effects can generate a variety of cooperation effects, such as multiresonance versus the driving frequency, as well as stochastic resonance versus noise parameters. In particular, in certain parameter regions the response function exhibits a resonance-like enhancement at intermediate values of the intensity of the Basset force. Conditions for the appearance of these effects are also discussed.

Influence of the Basset force on the resonant behavior of an oscillator with fluctuating frequency

International Nuclear Information System (INIS)

Rekker, A.; Mankin, R.

2015-01-01

The influence of hydrodynamic interactions, such as Stokes and Basset forces, on the dynamics of a harmonically trapped Brownian tracer is considered. A generalized Langevin equation is used to describe the tracer’s response to an external periodic force and to dichotomous fluctuations of the stiffness of the trapping potential. Relying on the Shapiro-Loginov formula, exact expressions for the complex susceptibility and for the response function are presented. On the basis of these exact formulas, it is demonstrated that interplay of a multiplicative colored noise and the Basset force induced memory effects can generate a variety of cooperation effects, such as multiresonance versus the driving frequency, as well as stochastic resonance versus noise parameters. In particular, in certain parameter regions the response function exhibits a resonance-like enhancement at intermediate values of the intensity of the Basset force. Conditions for the appearance of these effects are also discussed

Stochastic multiresonance for a fractional linear oscillator with time-delayed kernel and quadratic noise

Science.gov (United States)

Guo, Feng; Wang, Xue-Yuan; Zhu, Cheng-Yin; Cheng, Xiao-Feng; Zhang, Zheng-Yu; Huang, Xu-Hui

2017-12-01

The stochastic resonance for a fractional oscillator with time-delayed kernel and quadratic trichotomous noise is investigated. Applying linear system theory and Laplace transform, the system output amplitude (SPA) for the fractional oscillator is obtained. It is found that the SPA is a periodical function of the kernel delayed-time. Stochastic multiplicative phenomenon appears on the SPA versus the driving frequency, versus the noise amplitude, and versus the fractional exponent. The non-monotonous dependence of the SPA on the system parameters is also discussed.

n+235U resonance parameters and neutron multiplicities in the energy region below 100 eV

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Pigni Marco T.

2017-01-01

Full Text Available In August 2016, following the recent effort within the Collaborative International Evaluated Library Organization (CIELO pilot project to improve the neutron cross sections of 235U, Oak Ridge National Laboratory (ORNL collaborated with the International Atomic Energy Agency (IAEA to release a resonance parameter evaluation. This evaluation restores the performance of the evaluated cross sections for the thermal- and above-thermal-solution benchmarks on the basis of newly evaluated thermal neutron constants (TNCs and thermal prompt fission neutron spectra (PFNS. Performed with support from the US Nuclear Criticality Safety Program (NCSP in an effort to provide the highest fidelity general purpose nuclear database for nuclear criticality applications, the resonance parameter evaluation was submitted as an ENDF-compatible file to be part of the next release of the ENDF/B-VIII.0 nuclear data library. The resonance parameter evaluation methodology used the Reich-Moore approximation of the R-matrix formalism implemented in the code SAMMY to fit the available time-of-flight (TOF measured data for the thermal induced cross section of n+235U up to 100 eV. While maintaining reasonably good agreement with the experimental data, the validation analysis focused on restoring the benchmark performance for 235U solutions by combining changes to the resonance parameters and to the prompt resonance v̅ below 100 eV.

Partly Duffing Oscillator Stochastic Resonance Method and Its Application on Mechanical Fault Diagnosis

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Jian Dang

2016-01-01

Full Text Available Due to the fact that the slight fault signals in early failure of mechanical system are usually submerged in heavy background noise, it is unfeasible to extract the weak fault feature via the traditional vibration analysis. Stochastic resonance (SR, as a method of utilizing noise to amplify weak signals in nonlinear dynamical systems, can detect weak signals overwhelmed in the noise. However, based on the analysis of the impact of noise intensity on SR effect, it is concluded that the detection results are dramatically limited by the noise intensity of measured signals, especially for incipient fault feature of mechanical system with poor working environment. Therefore, this paper proposes a partly Duffing oscillator SR method to extract the fault feature of mechanical system. In this method, to locate the appearance of weak fault feature and decrease noise intensity, the permutation entropy index is constructed to select the measured signals for the input of Duffing oscillator system. Then, according to the regulation of system parameters, a reasonable match between the selected signals and Duffing oscillator model is achieved to produce a SR phenomenon and realize the fault diagnosis of mechanical system. Experiment results demonstrate that the proposed method achieves a better effect on the fault diagnosis of mechanical system.

Recommended formulae and formats for a resonance parameter library

International Nuclear Information System (INIS)

James, M.F.

1968-08-01

It is proposed that a library of neutron resonance parameters be set up, on punched cards and magnetic tape, which will complement the cross section data in the present U.K. Nuclear Data Library. This report gives parametric formulae for the resolved resonance region, based on:- (i) the Breit-Wigner approximation, (ii) other approximations of R-matrix theory and (iii) the formulae of Adler and Adler. In addition, the statistical distributions of the parameters are given. The final section of the report contains the recommended formats for the parameters of the various formulae. (author)

Active multiple plasmon-induced transparencies with detuned asymmetric multi-rectangle resonators

Science.gov (United States)

Liu, Dongdong; Wang, Jicheng; Lu, Jian

2016-11-01

The phenomenon of plasmon-induced transparency (PIT) is realized in surface plasmon polariton waveguide at the visible and near-infrared ranges. By adding one and two resonant cavities, the PIT peak(s) was (were) achieved due to destructive interference between the side-coupled rectangle cavity and the bus waveguide. The proposed structures were demonstrated by the finite element method. The simulation results showed that for three rectangle resonators system, not only can we manipulate each single PIT window, but also the double PIT windows simultaneously by adjusting one of the geometrical parameters of the system; for four rectangle resonators system, by changing the widths, the lengths and the refractive index of three cavities simultaneously, we would realize treble PIT peaks and induce an off-to-on PIT optical response. Our novel plasmonic structures and the findings pave the way for new design and engineering of highly integrated optical circuit such as nanoscale optical switching, nanosensor and wavelength-selecting nanostructure.

A Two-Stage Maximum Entropy Prior of Location Parameter with a Stochastic Multivariate Interval Constraint and Its Properties

Directory of Open Access Journals (Sweden)

Hea-Jung Kim

2016-05-01

Full Text Available This paper proposes a two-stage maximum entropy prior to elicit uncertainty regarding a multivariate interval constraint of the location parameter of a scale mixture of normal model. Using Shannon’s entropy, this study demonstrates how the prior, obtained by using two stages of a prior hierarchy, appropriately accounts for the information regarding the stochastic constraint and suggests an objective measure of the degree of belief in the stochastic constraint. The study also verifies that the proposed prior plays the role of bridging the gap between the canonical maximum entropy prior of the parameter with no interval constraint and that with a certain multivariate interval constraint. It is shown that the two-stage maximum entropy prior belongs to the family of rectangle screened normal distributions that is conjugate for samples from a normal distribution. Some properties of the prior density, useful for developing a Bayesian inference of the parameter with the stochastic constraint, are provided. We also propose a hierarchical constrained scale mixture of normal model (HCSMN, which uses the prior density to estimate the constrained location parameter of a scale mixture of normal model and demonstrates the scope of its applicability.

Stochastic bifurcation in a model of love with colored noise

Science.gov (United States)

Yue, Xiaokui; Dai, Honghua; Yuan, Jianping

2015-07-01

In this paper, we wish to examine the stochastic bifurcation induced by multiplicative Gaussian colored noise in a dynamical model of love where the random factor is used to describe the complexity and unpredictability of psychological systems. First, the dynamics in deterministic love-triangle model are considered briefly including equilibrium points and their stability, chaotic behaviors and chaotic attractors. Then, the influences of Gaussian colored noise with different parameters are explored such as the phase plots, top Lyapunov exponents, stationary probability density function (PDF) and stochastic bifurcation. The stochastic P-bifurcation through a qualitative change of the stationary PDF will be observed and bifurcation diagram on parameter plane of correlation time and noise intensity is presented to find the bifurcation behaviors in detail. Finally, the top Lyapunov exponent is computed to determine the D-bifurcation when the noise intensity achieves to a critical value. By comparison, we find there is no connection between two kinds of stochastic bifurcation.

Enhancement of Otolith Specific Ocular Responses Using Vestibular Stochastic Resonance

Science.gov (United States)

Fiedler, Matthew; De Dios, Yiri E.; Esteves, Julie; Galvan, Raquel; Wood, Scott; Bloomberg, Jacob; Mulavara, Ajitkumar

2011-01-01

Introduction: Astronauts experience disturbances in sensorimotor function after spaceflight during the initial introduction to a gravitational environment, especially after long-duration missions. Our goal is to develop a countermeasure based on vestibular stochastic resonance (SR) that could improve central interpretation of vestibular input and mitigate these risks. SR is a mechanism by which noise can assist and enhance the response of neural systems to relevant, imperceptible sensory signals. We have previously shown that imperceptible electrical stimulation of the vestibular system enhances balance performance while standing on an unstable surface. Methods: Eye movement data were collected from 10 subjects during variable radius centrifugation (VRC). Subjects performed 11 trials of VRC that provided equivalent tilt stimuli from otolith and other graviceptor input without the normal concordant canal cues. Bipolar stochastic electrical stimulation, in the range of 0-1500 microamperes, was applied to the vestibular system using a constant current stimulator through electrodes placed over the mastoid process behind the ears. In the VRC paradigm, subjects were accelerated to 216 deg./s. After the subjects no longer sensed rotation, the chair oscillated along a track at 0.1 Hz to provide tilt stimuli of 10 deg. Eye movements were recorded for 6 cycles while subjects fixated on a target in darkness. Ocular counter roll (OCR) movement was calculated from the eye movement data during periods of chair oscillations. Results: Preliminary analysis of the data revealed that 9 of 10 subjects showed an average increase of 28% in the magnitude of OCR responses to the equivalent tilt stimuli while experiencing vestibular SR. The signal amplitude at which performance was maximized was in the range of 100-900 microamperes. Discussion: These results indicate that stochastic electrical stimulation of the vestibular system can improve otolith specific responses. This will have a

STOCHASTIC FLOWS OF MAPPINGS

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.

Parallel logic gates in synthetic gene networks induced by non-Gaussian noise.

Science.gov (United States)

Xu, Yong; Jin, Xiaoqin; Zhang, Huiqing

2013-11-01

The recent idea of logical stochastic resonance is verified in synthetic gene networks induced by non-Gaussian noise. We realize the switching between two kinds of logic gates under optimal moderate noise intensity by varying two different tunable parameters in a single gene network. Furthermore, in order to obtain more logic operations, thus providing additional information processing capacity, we obtain in a two-dimensional toggle switch model two complementary logic gates and realize the transformation between two logic gates via the methods of changing different parameters. These simulated results contribute to improve the computational power and functionality of the networks.

SU-E-J-161: Inverse Problems for Optical Parameters in Laser Induced Thermal Therapy

International Nuclear Information System (INIS)

Fahrenholtz, SJ; Stafford, RJ; Fuentes, DT

2014-01-01

Purpose: Magnetic resonance-guided laser-induced thermal therapy (MRgLITT) is investigated as a neurosurgical intervention for oncological applications throughout the body by active post market studies. Real-time MR temperature imaging is used to monitor ablative thermal delivery in the clinic. Additionally, brain MRgLITT could improve through effective planning for laser fiber's placement. Mathematical bioheat models have been extensively investigated but require reliable patient specific physical parameter data, e.g. optical parameters. This abstract applies an inverse problem algorithm to characterize optical parameter data obtained from previous MRgLITT interventions. Methods: The implemented inverse problem has three primary components: a parameter-space search algorithm, a physics model, and training data. First, the parameter-space search algorithm uses a gradient-based quasi-Newton method to optimize the effective optical attenuation coefficient, μ-eff. A parameter reduction reduces the amount of optical parameter-space the algorithm must search. Second, the physics model is a simplified bioheat model for homogeneous tissue where closed-form Green's functions represent the exact solution. Third, the training data was temperature imaging data from 23 MRgLITT oncological brain ablations (980 nm wavelength) from seven different patients. Results: To three significant figures, the descriptive statistics for μ-eff were 1470 m −1 mean, 1360 m −1 median, 369 m −1 standard deviation, 933 m −1 minimum and 2260 m −1 maximum. The standard deviation normalized by the mean was 25.0%. The inverse problem took <30 minutes to optimize all 23 datasets. Conclusion: As expected, the inferred average is biased by underlying physics model. However, the standard deviation normalized by the mean is smaller than literature values and indicates an increased precision in the characterization of the optical parameters needed to plan MRgLITT procedures. This investigation

Stochasticity and superadiabaticity in radiofrequency plasma heating

International Nuclear Information System (INIS)

Stix, T.H.

1979-04-01

In a plasma subject to radiofrequency fields, it is only the resonant particles - comprising just a minor portion of the total velocity distribution - which are strongly affected. Under near-fusion conditions, thermalization by Coulomb collisions is slow, and noncollisional stochasticity can play an important role in reshaping f(v). It is found that the common rf interactions, including Landau, cyclotron and transit-time damping, can be fitted in a unified manner by a simple two-step one-parameter (epsilon) mapping which can display collision-free stochastic or adiabatic (also called superadiabatic) behavior, depending on the choice of epsilon. The effect on the evolution of the space averaged f (x,v,t) is reasonably well described by a pseudo-stochastic diffusion function, D/sub PS/(v,epsilon) which is the quasilinear diffusion coefficient but with appropriate widening of the delta-function spikes. Coulomb collisions, leading to D/sub Coul/(v) which may be added and directly compared to D/sub PS/(v,epsilon), are introduced by Langevin terms in the mapping equations

Neutron Capture and Transmission Measurements and Resonance Parameter Analysis of Samarium

International Nuclear Information System (INIS)

Leinweber, G.; Burke, J.A.; Knox, H.D.; Drindak, N.J.; Mesh, D.W.; Haines, W.T.; Ballad, R.V.; Block, R.C.; Slovacek, R.E.; Werner, C.J.; Trbovich, M.J.; Barry, D.P.; Sato, T.

2001-01-01

The purpose of the present work is to accurately measure the neutron cross sections of samarium. The most significant isotope is 149 Sm, which has a large neutron absorption cross section at thermal energies and is a 235 U fission product with a 1% yield. Its cross sections are thus of concern to reactor neutronics. Neutron capture and transmission measurements were performed by the time-of-flight technique at the Rensselaer Polytechnic institute (RPI) LINAC facility using metallic and liquid Sm samples. The capture measurements were made at the 25 meter flight station with a multiplicity-type capture detector, and the transmission total cross-section measurements were performed at 15- and 25-meter flight stations with 6 Li glass scintillation detectors. Resonance parameters were determined by a combined analysis of six experiments (three capture and three transmission) using the multi-level R-matrix Bayesian code SAMMY version M2. The significant features of this work are as follows. Dilute samples of samarium nitrate in deuterated water (D 2 O) were prepared to measure the strong resonances at 0.1 and 8 eV without saturation. Disk-shaped spectroscopic quartz cells were obtained with parallel inner surfaces to provide a uniform thickness of solution. The diluent feature of the SAMMY program was used to analyze these data. The SAMMY program also includes multiple scattering corrections to capture yield data and resolution functions specific to the RPI facility. Resonance parameters for all stable isotopes of samarium were deduced for all resonances up to 30 eV. Thermal capture cross-section and capture resonance integral calculations were made using the resultant resonance parameters and were compared to results obtained using resonance parameters from ENDF/B-VI updated through release 3. Extending the definition of the capture resonance integral to include the strong 0.1 eV resonance in 149 Sm, present measurements agree within estimated uncertainties with En

Self-induced steps in a small Josephson junction strongly coupled to a multimode resonator

DEFF Research Database (Denmark)

Larsen, A.; Jensen, H. Dalsgaard; Mygind, Jesper

1991-01-01

An equally spaced series of very large and nearly constant-voltage self-induced singularities has been observed in the dc I-V characteristics of a small Josephson tunnel junction strongly coupled to a resonant section of a superconducting transmission line. The system allows extremely high values...... of the coupling parameter. The current steps are due to subharmonic parametric excitation of the fundamental mode of the resonator loaded by the junction admittance. Using an applied magnetic field to vary the coupling parameter, we traced out half-integer steps as well as the mode steps known from more weakly...

Entropic noises-induced resonance in a geometrically confined system

International Nuclear Information System (INIS)

Zeng, Chunhua; Gong, Ailing; Wang, Hua

2012-01-01

We consider the motion of Brownian particles through a narrow tube of varying cross-section in a geometrically confined system subjected to a sinusoidal oscillating force. The varying cross-section of the confinement results in an effective purely entropic potential in reduced dimension. Besides an additive Langevin force, one external additive and another multiplicative noise are acting along the x-direction. We demonstrate that the presence of a periodic input may give rise to a maximum and a minimum of the spectral amplification at corresponding optimal values of the noise strength, and therefore to the appearance of the purely entropic stochastic resonance and reverse-resonance phenomena. Furthermore, we show that the cross-correlation between two noises leads to a decrease of the spectral amplification, i.e., we observe the cross-correlation between two noises weakening the resonance. Mechanisms for the cross-correlation weakening the resonance are explained from the point of view of the effective purely entropic potential. (paper)

Effect of Asymmetric Potential and Gaussian Colored Noise on Stochastic Resonance

International Nuclear Information System (INIS)

Han Yinxia; Li Jinghui; Chen Shigang

2005-01-01

The phenomenon of stochastic resonance (SR) in a bistable nonlinear system is studied when the system is driven by the asymmetric potential and additive Gaussian colored noise. Using the unified colored noise approximation method, the additive Gaussian colored noise can be simplified to additive Gaussian white noise. The signal-to-noise ratio (SNR) is calculated according to the generalized two-state theory (shown in [H.S. Wio and S. Bouzat, Brazilian J. Phys. 29 (1999) 136]). We find that the SNR increases with the proximity of a to zero. In addition, the correlation time τ between the additive Gaussian colored noise is also an ingredient to improve SR. The shorter the correlation time τ between the Gaussian additive colored noise is, the higher of the peak value of SNR.

Stochastic quantization of Einstein gravity

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

We determine a one-parameter family of covariant Langevin equations for the metric tensor of general relativity corresponding to DeWitt's one-parameter family of supermetrics. The stochastic source term in these equations can be expressed in terms of a Gaussian white noise upon the introduction of a stochastic tetrad field. The only physically acceptable resolution of a mathematical ambiguity in the ansatz for the source term is the adoption of Ito's calculus. By taking the formal equilibrium limit of the stochastic metric a one-parameter family of covariant path-integral measures for general relativity is obtained. There is a unique parameter value, distinguished by any one of the following three properties: (i) the metric is harmonic with respect to the supermetric, (ii) the path-integral measure is that of DeWitt, (iii) the supermetric governs the linearized Einstein dynamics. Moreover the Feynman propagator corresponding to this parameter is causal. Finally we show that a consistent stochastic perturbation theory gives rise to a new type of diagram containing ''stochastic vertices.''

A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty

Science.gov (United States)

Llopis-Albert, Carlos; Palacios-Marqués, Daniel; Merigó, José M.

2014-04-01

In this paper a methodology for the stochastic management of groundwater quality problems is presented, which can be used to provide agricultural advisory services. A stochastic algorithm to solve the coupled flow and mass transport inverse problem is combined with a stochastic management approach to develop methods for integrating uncertainty; thus obtaining more reliable policies on groundwater nitrate pollution control from agriculture. The stochastic inverse model allows identifying non-Gaussian parameters and reducing uncertainty in heterogeneous aquifers by constraining stochastic simulations to data. The management model determines the spatial and temporal distribution of fertilizer application rates that maximizes net benefits in agriculture constrained by quality requirements in groundwater at various control sites. The quality constraints can be taken, for instance, by those given by water laws such as the EU Water Framework Directive (WFD). Furthermore, the methodology allows providing the trade-off between higher economic returns and reliability in meeting the environmental standards. Therefore, this new technology can help stakeholders in the decision-making process under an uncertainty environment. The methodology has been successfully applied to a 2D synthetic aquifer, where an uncertainty assessment has been carried out by means of Monte Carlo simulation techniques.

Measurement of J/ψ resonance parameters

International Nuclear Information System (INIS)

Bai Jingzhi; Chen Guangpei; Chen Shaomin

1995-01-01

The cross sections of e + e - →hadrons, e + e - , μ + μ - have been measured in the vicinity of J/ψ resonance at BES/BEPC. The fit of the observed cross sections gives the new results of J/ψ resonance parameters: the partial widths to hadrons, electrons and muons are Γ h = 74.1 +- 8.1 keV, Γ e = 5.14 +- 0.39 keV and Γ μ = 5.13 +-0.52 keV respectively; the total width Γ = 84.4 +- 8.9 keV; the branching fractions Γ h /Γ = (87.8 +- 0.5)%, Γ e /Γ (6.09 +- 0.33)%, and Γ μ /Γ = (6.08 +- 0.33)%

Statistics of Poincare recurrences and the structure of the stochastic layer of a nonlinear resonance

International Nuclear Information System (INIS)

Chirikov, B.V.; Shepelyansky, D.L.

1983-02-01

Motion in the stochastic layer around the separatrix of a nonlinear resonance was investigated. The integral distribution function F(tau) of trajectory recurrence times tau to the center of the layer was numerically determined. It was found that the distribution F(tau) = A tau - /sup p/ is a power function, the exponent assuming two different values: for tau less than or equal to tau 0 , p = 1/2 and for tau >> tau 0 , p = 3/2 (time tau 0 is determined by the characteristics of the layer)

UPSILON'(10.01) resonance parameters

International Nuclear Information System (INIS)

Niczyporuk, B.; Zeludziewicz, T.; Chen, K.W.; Hartung, R.

1980-09-01

The resonance parameters of the UPSILON'(10.01) were measured using the LENA detector at the DORIS e + e - storage ring. We obtained a mass of M(UPSILON') = (10 013.6 +- 1.2 +- 10.0) MeV and an electronic width of GAMMAsub(ee)(UPSILON') = (0.53 +- 0.07sup(+0.09)sub(-0.05) keV. The upper limit set to the μ-pair branching ratio is 3.8% which implies a lower limit on the total UPSILON' widUPSILON parameters we obtain a mass difference M(UPSILON') - M(UPSILON) = (552.0 +- 1.3 +- 10.0) MeV and GAMMAsub(ee)UPSILON')/ = 0.43 +- 0.07sup(+0.05)sub(-0.00). (orig.)

Robust authentication through stochastic femtosecond laser filament induced scattering surfaces

International Nuclear Information System (INIS)

Zhang, Haisu; Tzortzakis, Stelios

2016-01-01

We demonstrate a reliable authentication method by femtosecond laser filament induced scattering surfaces. The stochastic nonlinear laser fabrication nature results in unique authentication robust properties. This work provides a simple and viable solution for practical applications in product authentication, while also opens the way for incorporating such elements in transparent media and coupling those in integrated optical circuits.

Robust authentication through stochastic femtosecond laser filament induced scattering surfaces

Energy Technology Data Exchange (ETDEWEB)

Zhang, Haisu [Institute of Electronic Structure and Laser, Foundation for Research and Technology Hellas, Heraklion 71110 (Greece); Tzortzakis, Stelios, E-mail: stzortz@iesl.forth.gr [Institute of Electronic Structure and Laser, Foundation for Research and Technology Hellas, Heraklion 71110 (Greece); Materials Science and Technology Department, University of Crete, 71003 Heraklion (Greece); Science Program, Texas A& M University at Qatar, P.O. Box 23874, Doha (Qatar)

2016-05-23

We demonstrate a reliable authentication method by femtosecond laser filament induced scattering surfaces. The stochastic nonlinear laser fabrication nature results in unique authentication robust properties. This work provides a simple and viable solution for practical applications in product authentication, while also opens the way for incorporating such elements in transparent media and coupling those in integrated optical circuits.

Stochasticity induced by coherent wavepackets

International Nuclear Information System (INIS)

Fuchs, V.; Krapchev, V.; Ram, A.; Bers, A.

1983-02-01

We consider the momentum transfer and diffusion of electrons periodically interacting with a coherent longitudinal wavepacket. Such a problem arises, for example, in lower-hybrid current drive. We establish the stochastic threshold, the stochastic region δv/sub stoch/ in velocity space, the associated momentum transfer j, and the diffusion coefficient D. We concentrate principally on the weak-field regime, tau/sub autocorrelation/ < tau/sub bounce/

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models

Science.gov (United States)

Butler, T.; Graham, L.; Estep, D.; Dawson, C.; Westerink, J. J.

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

A method for generating subgroup parameters from resonance tables

International Nuclear Information System (INIS)

Devan, K.; Mohanakrishnan, P.

1993-01-01

A method for generating subgroup or band parameters from resonance tables is described. A computer code SPART was written using this method. This code generates the subgroup parameters for any number of bands within the specified broad groups at different temperatures by reading the required input data from the binary cross section library in the Cadarache format. The results obtained with SPART code for two bands were compared with that obtained from GROUPIE code and a good agreement was obtained. Results of the generation of subgroup parameters in four bands for sample case of 239 Pu from resonance tables of Cadarache Ver.2 library is also presented. (author). 8 refs., 2 tabs

Determination of kinetics parameters using stochastic methods in a 252Cf system

International Nuclear Information System (INIS)

Difilippo, F.C.

1988-01-01

Safety analysis and control system design of nuclear systems require the knowledge of neutron kinetics related parameters like effective delayed neutron fraction, neutron lifetime, time between neutron generations and subcriticality margins. Many methods, deterministic and stochastic, are being used, some since the beginning of nuclear power, to measure these important parameters. The method based on the use of the 252 Cf neutron source has been under intense study at the Oak Ridge National Laboratory, both experimentally and theoretically, during the last years. The increasing demand for this isotope in industrial and medical applications and new designs of advanced high flux reactors to produce it make the isotope available as neutron source (only few micrograms are necessary). A thin layer of 252 Cf is deposited in one of the electrodes of a fission chamber which produces pulses each time the 252 Cf disintegrates via α or spontaneous fission decay; the smaller pulses associated with the α decay can be easily discriminated with the important result that we known the time when v/sub c/ neutrons are injected into the system (number of neutrons per fission of 252 Cf). Thus, a small (few cm 3 ) and nonintrusive device can be used as a random pulsed neutron source with known natural properties that do no depend on biases associated with more complex interrogating devices like accelerators. This paper presents a general formalism that relates the kinetics parameters with stochastic descriptors that naturally appear because of the random nature of the production and transport of neutrons

Discrete ambiguity resolution and baryon-resonance parameter determination

International Nuclear Information System (INIS)

Chew, D.M; Urban, M.

1978-04-01

A partial-wave analysis was performed on elastic π + p data between 1400 and 2200 MeV, using principles of analyticity (to select and amalgamate data), causality and unitarity together with Barrelet zeros are the resonating waves between 1500 and 1800 MeV examined in detail, and it is shown how a new resolution of the discrete ambiguity gives, for the S31 and D33 resonances, different parameters than found in an earlier resolution using less accurate information. In either case, mass degeneracy of these resonances is observed in agreement with general considerations regarding smooth zero trajectories. 18 references

Robust H∞ Filtering for Uncertain Neutral Stochastic Systems with Markovian Jumping Parameters and Time Delay

Directory of Open Access Journals (Sweden)

Yajun Li

2015-01-01

Full Text Available This paper deals with the robust H∞ filter design problem for a class of uncertain neutral stochastic systems with Markovian jumping parameters and time delay. Based on the Lyapunov-Krasovskii theory and generalized Finsler Lemma, a delay-dependent stability condition is proposed to ensure not only that the filter error system is robustly stochastically stable but also that a prescribed H∞ performance level is satisfied for all admissible uncertainties. All obtained results are expressed in terms of linear matrix inequalities which can be easily solved by MATLAB LMI toolbox. Numerical examples are given to show that the results obtained are both less conservative and less complicated in computation.

The thermal neutron absorption cross-sections, resonance integrals and resonance parameters of silicon and its stable isotopes

International Nuclear Information System (INIS)

Story, J.S.

1969-09-01

The data available up to the end of November 1968 on the thermal neutron absorption cross-sections, resonance absorption integrals, and resonance parameters of silicon and its stable isotopes are collected and discussed. Estimates are given of the mean spacing of the energy levels of the compound nuclei near the neutron binding energy. It is concluded that the thermal neutron absorption cross-section and resonance absorption integral of natural silicon are not well established. The data on these two parameters are somewhat correlated, and three different assessments of the resonance integral are presented which differ over-all by a factor of 230. Many resonances have been detected by charged particle reactions which have not yet been observed in neutron cross-section measurements. One of these resonances of Si 2 8, at E n = 4 ± 5 keV might account for the large resonance integral which is derived, very uncertainly, from integral data. The principal source of the measured resonance integral of Si 3 0 has not yet been located. The thermal neutron absorption cross-section of Si 2 8 appears to result mainly from a negative energy resonance, possibly the resonance at E n = - 59 ± 5 keV detected by the Si 2 8 (d,p) reaction. (author)

Diffusion induced by cyclotron resonance heating

International Nuclear Information System (INIS)

Riyopoulos, S.; Tajima, T.; Hatori, T.; Pfirsch, D.

1985-09-01

The wave induced particle transport during the ion cyclotron resonance heating is studied in collisionless toroidal plasmas. It is shown that the previously neglected non-conservation of the toroidal angular momentum IP/sub phi/ caused by the toroidal wave component E/sub phi/ is necessary to allow particle diffusion and yields the leading diffusive contribution. While the induced ion transport for the rf power in contemporary experiments is of the order of the neoclassical value, that of fast alpha particles is quite large if resonance is present

On the Methodology to Calculate the Covariance of Estimated Resonance Parameters

International Nuclear Information System (INIS)

Becker, B.; Kopecky, S.; Schillebeeckx, P.

2015-01-01

Principles to determine resonance parameters and their covariance from experimental data are discussed. Different methods to propagate the covariance of experimental parameters are compared. A full Bayesian statistical analysis reveals that the level to which the initial uncertainty of the experimental parameters propagates, strongly depends on the experimental conditions. For high precision data the initial uncertainties of experimental parameters, like a normalization factor, has almost no impact on the covariance of the parameters in case of thick sample measurements and conventional uncertainty propagation or full Bayesian analysis. The covariances derived from a full Bayesian analysis and least-squares fit are derived under the condition that the model describing the experimental observables is perfect. When the quality of the model can not be verified a more conservative method based on a renormalization of the covariance matrix is recommended to propagate fully the uncertainty of experimental systematic effects. Finally, neutron resonance transmission analysis is proposed as an accurate method to validate evaluated data libraries in the resolved resonance region

Three dimensional nuclear magnetic resonance spectroscopic imaging of sodium ions using stochastic excitation and oscillating gradients

International Nuclear Information System (INIS)

Frederick, B.deB.

1994-12-01

Nuclear magnetic resonance (NMR) spectroscopic imaging of 23 Na holds promise as a non-invasive method of mapping Na + distributions, and for differentiating pools of Na + ions in biological tissues. However, due to NMR relaxation properties of 23 Na in vivo, a large fraction of Na + is not visible with conventional NMR imaging methods. An alternate imaging method, based on stochastic excitation and oscillating gradients, has been developed which is well adapted to measuring nuclei with short T 2 . Contemporary NMR imaging techniques have dead times of up to several hundred microseconds between excitation and sampling, comparable to the shortest in vivo 23 Na T 2 values, causing significant signal loss. An imaging strategy based on stochastic excitation has been developed which greatly reduces experiment dead time by reducing peak radiofrequency (RF) excitation power and using a novel RF circuit to speed probe recovery. Continuously oscillating gradients are used to eliminate transient eddy currents. Stochastic 1 H and 23 Na spectroscopic imaging experiments have been performed on a small animal system with dead times as low as 25μs, permitting spectroscopic imaging with 100% visibility in vivo. As an additional benefit, the encoding time for a 32x32x32 spectroscopic image is under 30 seconds. The development and analysis of stochastic NMR imaging has been hampered by limitations of the existing phase demodulation reconstruction technique. Three dimensional imaging was impractical due to reconstruction time, and design and analysis of proposed experiments was limited by the mathematical intractability of the reconstruction method. A new reconstruction method for stochastic NMR based on Fourier interpolation has been formulated combining the advantage of a several hundredfold reduction in reconstruction time with a straightforward mathematical form

Confinement-induced resonances in anharmonic waveguides

Energy Technology Data Exchange (ETDEWEB)

Peng Shiguo [Department of Physics, Tsinghua University, Beijing 100084 (China); Centre for Atom Optics and Ultrafast Spectroscopy, Swinburne University of Technology, Melbourne 3122 (Australia); Hu Hui; Liu Xiaji; Drummond, Peter D. [Centre for Atom Optics and Ultrafast Spectroscopy, Swinburne University of Technology, Melbourne 3122 (Australia)

2011-10-15

We develop the theory of anharmonic confinement-induced resonances (ACIRs). These are caused by anharmonic excitation of the transverse motion of the center of mass (c.m.) of two bound atoms in a waveguide. As the transverse confinement becomes anisotropic, we find that the c.m. resonant solutions split for a quasi-one-dimensional (1D) system, in agreement with recent experiments. This is not found in harmonic confinement theories. A new resonance appears for repulsive couplings (a{sub 3D}>0) for a quasi-two-dimensional (2D) system, which is also not seen with harmonic confinement. After inclusion of anharmonic energy corrections within perturbation theory, we find that these ACIRs agree extremely well with anomalous 1D and 2D confinement-induced resonance positions observed in recent experiments. Multiple even- and odd-order transverse ACIRs are identified in experimental data, including up to N=4 transverse c.m. quantum numbers.

Bayesian parameter estimation for stochastic models of biological cell migration

Science.gov (United States)

Dieterich, Peter; Preuss, Roland

2013-08-01

Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.

Stochastic resonance for signal-modulated pump noise in a single-mode laser

Institute of Scientific and Technical Information of China (English)

Liangying Zhang; Li Cao; Fahui Zhu

2006-01-01

By adopting the gain-noise model of the single-mode laser in which with bias and periodical signals serve as inputs, combining with the effect of coloured pump noise, we use the linear approximation method to calculate the power spectrum and signal-to-noise ratio (SNR) of the laser intensity under the condition of pump noise and quantum noise cross-related in the form of δ function. It is found that with the change of pump noise correlation time, both SNR and the output power will occur stochastic resonance (SR). If the bias signal α is very small, changing the intensities of pump noise and quantum noise respectively does not lead to the appearance of SR in the SNR; while α increases to a certain number, SR appears.

Measurements of time average series resonance effect in capacitively coupled radio frequency discharge plasma

International Nuclear Information System (INIS)

Bora, B.; Bhuyan, H.; Favre, M.; Wyndham, E.; Chuaqui, H.; Kakati, M.

2011-01-01

Self-excited plasma series resonance is observed in low pressure capacitvely coupled radio frequency discharges as high-frequency oscillations superimposed on the normal radio frequency current. This high-frequency contribution to the radio frequency current is generated by a series resonance between the capacitive sheath and the inductive and resistive bulk plasma. In this report, we present an experimental method to measure the plasma series resonance in a capacitively coupled radio frequency argon plasma by modifying the homogeneous discharge model. The homogeneous discharge model is modified by introducing a correction factor to the plasma resistance. Plasma parameters are also calculated by considering the plasma series resonances effect. Experimental measurements show that the self-excitation of the plasma series resonance, which arises in capacitive discharge due to the nonlinear interaction of plasma bulk and sheath, significantly enhances both the Ohmic and stochastic heating. The experimentally measured total dissipation, which is the sum of the Ohmic and stochastic heating, is found to increase significantly with decreasing pressure.

Analogy of electromagnetically induced transparency in plasmonic nanodisk with a square ring resonator

International Nuclear Information System (INIS)

Li, Xianping; Wei, Zhongchao; Liu, Yuebo; Zhong, Nianfa; Tan, Xiaopei; Shi, Songsong; Liu, Hongzhan; Liang, Ruisheng

2016-01-01

We have demonstrated the analogy of electromagnetically induced transparency in plasmonic nanodisk with a square ring resonator. A reasonable analysis of the transmission feature based on the temporal coupled-mode theory is given and shows good agreement with the Finit-Difference Time-Domain simulation. The transparency window can be easily tuned by changing the geometrical parameters and the insulator filled in the resonator. The transmission of the resonator system is close to 80% and the full width at half maximum is less than 46 nm. The sensitivity of the structure is about 812 nm/RIU. These characteristics make the new system with potential to apply for optical storage, ultrafast plasmonic switch and slow-light devices.

Analogy of electromagnetically induced transparency in plasmonic nanodisk with a square ring resonator

Energy Technology Data Exchange (ETDEWEB)

Li, Xianping; Wei, Zhongchao, E-mail: wzc@scnu.edu.cn; Liu, Yuebo; Zhong, Nianfa; Tan, Xiaopei; Shi, Songsong; Liu, Hongzhan; Liang, Ruisheng

2016-01-08

We have demonstrated the analogy of electromagnetically induced transparency in plasmonic nanodisk with a square ring resonator. A reasonable analysis of the transmission feature based on the temporal coupled-mode theory is given and shows good agreement with the Finit-Difference Time-Domain simulation. The transparency window can be easily tuned by changing the geometrical parameters and the insulator filled in the resonator. The transmission of the resonator system is close to 80% and the full width at half maximum is less than 46 nm. The sensitivity of the structure is about 812 nm/RIU. These characteristics make the new system with potential to apply for optical storage, ultrafast plasmonic switch and slow-light devices.

Global exponential stability of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays.

Science.gov (United States)

Huang, Haiying; Du, Qiaosheng; Kang, Xibing

2013-11-01

In this paper, a class of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays is investigated. The jumping parameters are modeled as a continuous-time finite-state Markov chain. At first, the existence of equilibrium point for the addressed neural networks is studied. By utilizing the Lyapunov stability theory, stochastic analysis theory and linear matrix inequality (LMI) technique, new delay-dependent stability criteria are presented in terms of linear matrix inequalities to guarantee the neural networks to be globally exponentially stable in the mean square. Numerical simulations are carried out to illustrate the main results. © 2013 ISA. Published by ISA. All rights reserved.

Hypothesized diprotomeric enzyme complex supported by stochastic modelling of palytoxin-induced Na/K pump channels.

Science.gov (United States)

Vilallonga, Gabriel D; de Almeida, Antônio-Carlos G; Ribeiro, Kelison T; Campos, Sergio V A; Rodrigues, Antônio M

2018-03-01

The sodium-potassium pump (Na + /K + pump) is crucial for cell physiology. Despite great advances in the understanding of this ionic pumping system, its mechanism is not completely understood. We propose the use of a statistical model checker to investigate palytoxin (PTX)-induced Na + /K + pump channels. We modelled a system of reactions representing transitions between the conformational substates of the channel with parameters, concentrations of the substates and reaction rates extracted from simulations reported in the literature, based on electrophysiological recordings in a whole-cell configuration. The model was implemented using the UPPAAL-SMC platform. Comparing simulations and probabilistic queries from stochastic system semantics with experimental data, it was possible to propose additional reactions to reproduce the single-channel dynamic. The probabilistic analyses and simulations suggest that the PTX-induced Na + /K + pump channel functions as a diprotomeric complex in which protein-protein interactions increase the affinity of the Na + /K + pump for PTX.

OPTIMIZATION OF HEMISPHERICAL RESONATOR GYROSCOPE STANDING WAVE PARAMETERS

Directory of Open Access Journals (Sweden)

Olga Sergeevna Khalyutina

2017-01-01

Full Text Available Traditionally, the problem of autonomous navigation is solved by dead reckoning navigation flight parameters (NFP of the aircraft (AC. With increasing requirements to accuracy of definition NFP improved the sensors of the prima- ry navigation information: gyroscopes and accelerometers. the gyroscopes of a new type, the so-called solid-state wave gyroscopes (SSVG are currently developed and put into practice. The work deals with the problem of increasing the accu- racy of measurements of angular velocity of the hemispherical resonator gyroscope (HRG. The reduction in the accuracy characteristics of HRG is caused by the presence of defects in the distribution of mass in the volume of its design. The syn- thesis of control system for optimal damping of the distortion parameters of the standing wave due to the influence of the mass defect resonator is adapted. The research challenge was: to examine and analytically offset the impact of the standing wave (amplitude and frequency parameters defect. Research was performed by mathematical modeling in the environment of SolidWorks Simulation for the case when the characteristics of the sensitive element of the HRG met the technological drawings of a particular type of resonator. The method of the inverse dynamics was chosen for synthesis. The research re- sults are presented in graphs the amplitude-frequency characteristics (AFC of the resonator output signal. Simulation was performed for the cases: the perfect distribution of weight; the presence of the mass defect; the presence of the mass defects are shown using the synthesized control action. Evaluating the effectiveness of the proposed control algorithm is deter- mined by the results of the resonator output signal simulation provided the perfect constructive and its performance in the presence of a mass defect in it. It is assumed that the excitation signals are standing waves in the two cases are identical in both amplitude and frequency. In this

Use of stochastic methods for robust parameter extraction from impedance spectra

International Nuclear Information System (INIS)

Bueschel, Paul; Troeltzsch, Uwe; Kanoun, Olfa

2011-01-01

The fitting of impedance models to measured data is an essential step in impedance spectroscopy (IS). Due to often complicated, nonlinear models, big number of parameters, large search spaces and presence of noise, an automated determination of the unknown parameters is a challenging task. The stronger the nonlinear behavior of a model, the weaker is the convergence of the corresponding regression and the probability to trap into local minima increases during parameter extraction. For fast measurements or automatic measurement systems these problems became the limiting factors of use. We compared the usability of stochastic algorithms, evolution, simulated annealing and particle filter with the widely used tool LEVM for parameter extraction for IS. The comparison is based on one reference model by J.R. Macdonald and a battery model used with noisy measurement data. The results show different performances of the algorithms for these two problems depending on the search space and the model used for optimization. The obtained results by particle filter were the best for both models. This method delivers the most reliable result for both cases even for the ill posed battery model.

Bridges for Pedestrians with Random Parameters using the Stochastic Finite Elements Analysis

Science.gov (United States)

Szafran, J.; Kamiński, M.

2017-02-01

The main aim of this paper is to present a Stochastic Finite Element Method analysis with reference to principal design parameters of bridges for pedestrians: eigenfrequency and deflection of bridge span. They are considered with respect to random thickness of plates in boxed-section bridge platform, Young modulus of structural steel and static load resulting from crowd of pedestrians. The influence of the quality of the numerical model in the context of traditional FEM is shown also on the example of a simple steel shield. Steel structures with random parameters are discretized in exactly the same way as for the needs of traditional Finite Element Method. Its probabilistic version is provided thanks to the Response Function Method, where several numerical tests with random parameter values varying around its mean value enable the determination of the structural response and, thanks to the Least Squares Method, its final probabilistic moments.

Bridges for Pedestrians with Random Parameters using the Stochastic Finite Elements Analysis

Directory of Open Access Journals (Sweden)

Szafran J.

2017-02-01

Full Text Available The main aim of this paper is to present a Stochastic Finite Element Method analysis with reference to principal design parameters of bridges for pedestrians: eigenfrequency and deflection of bridge span. They are considered with respect to random thickness of plates in boxed-section bridge platform, Young modulus of structural steel and static load resulting from crowd of pedestrians. The influence of the quality of the numerical model in the context of traditional FEM is shown also on the example of a simple steel shield. Steel structures with random parameters are discretized in exactly the same way as for the needs of traditional Finite Element Method. Its probabilistic version is provided thanks to the Response Function Method, where several numerical tests with random parameter values varying around its mean value enable the determination of the structural response and, thanks to the Least Squares Method, its final probabilistic moments.

Single-level resonance parameters fit nuclear cross-sections

Science.gov (United States)

Drawbaugh, D. W.; Gibson, G.; Miller, M.; Page, S. L.

1970-01-01

Least squares analyses of experimental differential cross-section data for the U-235 nucleus have yielded single level Breit-Wigner resonance parameters that fit, simultaneously, three nuclear cross sections of capture, fission, and total.

Stochastic chaos induced by diffusion processes with identical spectral density but different probability density functions.

Science.gov (United States)

Lei, Youming; Zheng, Fan

2016-12-01

Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.

Stochastic bifurcation and fractal and chaos control of a giant magnetostrictive film-shape memory alloy composite cantilever plate subjected to in-plane harmonic and stochastic excitation

International Nuclear Information System (INIS)

Zhu, Zhiwen; Zhang, Qingxin; Xu, Jia

2014-01-01

Stochastic bifurcation and fractal and chaos control of a giant magnetostrictive film–shape memory alloy (GMF–SMA) composite cantilever plate subjected to in-plane harmonic and stochastic excitation were studied. Van der Pol items were improved to interpret the hysteretic phenomena of both GMF and SMA, and the nonlinear dynamic model of a GMF–SMA composite cantilever plate subjected to in-plane harmonic and stochastic excitation was developed. The probability density function of the dynamic response of the system was obtained, and the conditions of stochastic Hopf bifurcation were analyzed. The conditions of noise-induced chaotic response were obtained in the stochastic Melnikov integral method, and the fractal boundary of the safe basin of the system was provided. Finally, the chaos control strategy was proposed in the stochastic dynamic programming method. Numerical simulation shows that stochastic Hopf bifurcation and chaos appear in the parameter variation process. The boundary of the safe basin of the system has fractal characteristics, and its area decreases when the noise intensifies. The system reliability was improved through stochastic optimal control, and the safe basin area of the system increased

Density-near-zero using the acoustically induced transparency of a Fano acoustic resonator

KAUST Repository

Elayouch, A.

2017-01-05

We report experimental results of near-zero mass density involving an acoustic metamaterial supporting Fano resonance. For this, we designed and fabricated an acoustic resonator with two closely coupled modes and measured its transmission properties. Our study reveals that the phenomenon of acoustically induced transparency is accompanied by an effect of near-zero density. Indeed, the dynamic effective parameters obtained from experimental data show the presence of a frequency band where the effective mass density is close to zero, with high transmission levels reaching 0.7. Furthermore, we demonstrate that such effective parameters lead to wave guiding in a 90-degrees-bent channel. This kind of acoustic metamaterial can, therefore, give rise to acoustic functions like controlling the wavefront, which may lead to very promising applications in acoustic cloacking or imaging.

Far-wing light absorption induced by resonant or near-resonant collisions

International Nuclear Information System (INIS)

Cavalieri, S.; Celli, M.

1996-01-01

The authors have studied the absorption of light induced by a resonant or near-resonant collision between two atoms. The calculations have been performed by taking into account also the magnetic sublevels, which makes their theoretical predictions more applicable to realistic cases. Analytical expressions for the far-wing absorption cross-section have been obtained

Parameter estimation and change-point detection from Dynamic Contrast Enhanced MRI data using stochastic differential equations.

Science.gov (United States)

Cuenod, Charles-André; Favetto, Benjamin; Genon-Catalot, Valentine; Rozenholc, Yves; Samson, Adeline

2011-09-01

Dynamic Contrast Enhanced imaging (DCE-imaging) following a contrast agent bolus allows the extraction of information on tissue micro-vascularization. The dynamic signals obtained from DCE-imaging are modeled by pharmacokinetic compartmental models which integrate the Arterial Input Function. These models use ordinary differential equations (ODEs) to describe the exchanges between the arterial and capillary plasma and the extravascular-extracellular space. Their least squares fitting takes into account measurement noises but fails to deal with unpredictable fluctuations due to external/internal sources of variations (patients' anxiety, time-varying parameters, measurement errors in the input function, etc.). Adding Brownian components to the ODEs leads to stochastic differential equations (SDEs). In DCE-imaging, SDEs are discretely observed with an additional measurement noise. We propose to estimate the parameters of these noisy SDEs by maximum likelihood, using the Kalman filter. In DCE-imaging, the contrast agent injected in vein arrives in plasma with an unknown time delay. The delay parameter induces a change-point in the drift of the SDE and ODE models, which is estimated also. Estimations based on the SDE and ODE pharmacokinetic models are compared to real DCE-MRI data. They show that the use of SDE provides robustness in the estimation results. A simulation study confirms these results. Copyright © 2011 Elsevier Inc. All rights reserved.

A Stochastic Proof of the Resonant Scattering Kernel and its Applications for Gen IV Reactors Type

International Nuclear Information System (INIS)

Becker, B.; Dagan, R.; Broeders, C.H.M.; Lohnert, G.

2008-01-01

Monte Carlo codes such as MCNP are widely accepted as almost-reference for reactor analysis. The Monte Carlo Code should therefore use as few as possible approximations in order to produce 'experimental-level' calculations. In this study we deal with one of the most problematic approximations done in MCNP in which the resonances are ignored for the secondary neutron energy distribution, namely the change of the energy and angular direction of the neutron after interaction with a heavy isotope with pronounced resonances. The endeavour of exploiting the influence of the resonances on the scattering kernel goes back to 1944 where E. Wigner and J. Wilkins developed the first temperature dependent scattering kernel. However only in 1998, the full analytical solution for the double differential resonant dependent scattering kernel was suggested by W. Rothenstein and R. Dagan. An independent stochastic approach is presented for the first time to confirm the above analytical kernel with a complete different methodology. Moreover, by manipulating in a subtle manner the scattering subroutine COLIDN of MCNP, it is proven that this very subroutine is, to some extent, inappropriate as well as the relevant explanation in the MCNP manual. The impact of this improved resonance dependent scattering kernel on diverse types of reactors, in particular for the Generation IV innovative core design HTR, is shown to be significant. (authors)

Nonlinear dynamics in micromechanical and nanomechanical resonators and oscillators

Science.gov (United States)

Dunn, Tyler

In recent years, the study of nonlinear dynamics in microelectromechanical and nanoelectromechanical systems (MEMS and NEMS) has attracted considerable attention, motivated by both fundamental and practical interests. One example is the phenomenon of stochastic resonance. Previous measurements have established the presence of this counterintuitive effect in NEMS, showing that certain amounts of white noise can effectively amplify weak switching signals in nanomechanical memory elements and switches. However, other types of noise, particularly noises with 1/falpha spectra, also bear relevance in these and many other systems. At a more fundamental level, the role which noise color plays in stochastic resonance remains an open question in the field. To these ends, this work presents systematic measurements of stochastic resonance in a nanomechanical resonator using 1/f alpha and Ornstein-Uhlenbeck noise types. All of the studied noise spectra induce stochastic resonance, proving that colored noise can also be beneficial; however, stronger noise correlations suppress the effect, decreasing the maximum signal-to-noise ratio and increasing the optimal noise intensity. Evidence suggests that 1/falpha noise spectra with increasing noise color lead to increasingly asymmetric switching, reducing the achievable amplification. Another manifestly nonlinear effect anticipated in these systems is modal coupling. Measurements presented here demonstrate interactions between various mode types on a wide scale, providing the first reported observations of coupling in bulk longitudinal modes of MEMS. As a result of anharmonic elastic effects, each mode shifts in frequency by an amount proportional to the squared displacement (or energy) of a coupled mode. Since all resonator modes couple in this manner, these effects enable nonlinear measurement of energy and mechanical nonlinear signal processing across a wide range of frequencies. Finally, while these experiments address nonlinear

Stochastic sawtooth reconnection in ASDEX Upgrade

International Nuclear Information System (INIS)

Igochine, V.; Dumbrajs, O.; Zohm, H.; Flaws, A.

2007-01-01

In this paper we investigate non-complete sawtooth reconnection in the ASDEX Upgrade tokamak. Such reconnection phenomena are associated with internal m/n = 1/1 kink mode which does not vanish after the crash phase (as would be the case for complete reconnection). It is shown that this sawtooth cannot be fully described by pure m/n = 1/1 mode and that higher harmonics play an important role during the sawtooth crash phase. We employ the Hamiltonian formalism and reconstructed perturbations to model incomplete sawtooth reconnection. It is demonstrated that stochastization appears due to the excitation of low-order resonances which are present in the corresponding q-profiles inside the q = 1 surface which reflects the key role of the q 0 value. Depending on this value two completely different situations are possible for one and the same mode perturbations: (i) the resonant surfaces are present in the q-profile leading to stochasticity and sawtooth crash (q 0 ∼ 0.7 ± 0.1); (ii) the resonant surfaces are not present, which means no stochasticity in the system and no crash event (q 0 ∼ 0.9 ± 0.05). Accordingly the central safety factor value is always less than unity in the case of a non-complete sawtooth reconnection. Our investigations show that the stochastic model agrees well with the experimental observations and can be proposed as a promising candidate for an explanation of the sawtooth reconnection

3D stochastic inversion and joint inversion of potential fields for multi scale parameters

Science.gov (United States)

Shamsipour, Pejman

In this thesis we present the development of new techniques for the interpretation of potential field (gravity and magnetic data), which are the most widespread economic geophysical methods used for oil and mineral exploration. These new techniques help to address the long-standing issue with the interpretation of potential fields, namely the intrinsic non-uniqueness inversion of these types of data. The thesis takes the form of three papers (four including Appendix), which have been published, or soon to be published, in respected international journals. The purpose of the thesis is to introduce new methods based on 3D stochastical approaches for: 1) Inversion of potential field data (magnetic), 2) Multiscale Inversion using surface and borehole data and 3) Joint inversion of geophysical potential field data. We first present a stochastic inversion method based on a geostatistical approach to recover 3D susceptibility models from magnetic data. The aim of applying geostatistics is to provide quantitative descriptions of natural variables distributed in space or in time and space. We evaluate the uncertainty on the parameter model by using geostatistical unconditional simulations. The realizations are post-conditioned by cokriging to observation data. In order to avoid the natural tendency of the estimated structure to lay near the surface, depth weighting is included in the cokriging system. Then, we introduce algorithm for multiscale inversion, the presented algorithm has the capability of inverting data on multiple supports. The method involves four main steps: i. upscaling of borehole parameters (It could be density or susceptibility) to block parameters, ii. selection of block to use as constraints based on a threshold on kriging variance, iii. inversion of observation data with selected block densities as constraints, and iv. downscaling of inverted parameters to small prisms. Two modes of application are presented: estimation and simulation. Finally, a novel

Electromagnetically induced transparency with large delay-bandwidth product induced by magnetic resonance near field coupling to electric resonance

Energy Technology Data Exchange (ETDEWEB)

Li, Hai-ming; Liu, Shao-bin, E-mail: lsb@nuaa.edu.cn; Liu, Si-yuan; Zhang, Hai-feng; Bian, Bo-rui; Kong, Xiang-kun [Key Laboratory of Radar Imaging and Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Wang, Shen-yun [Research Center of Applied Electromagnetics, Nanjing University of Information Science and Technology, Nanjing 210044 (China)

2015-03-16

In this paper, we numerically and experimentally demonstrate electromagnetically induced transparency (EIT)-like spectral response with magnetic resonance near field coupling to electric resonance. Six split-ring resonators and a cut wire are chosen as the bright and dark resonator, respectively. An EIT-like transmission peak located between two dips can be observed with incident magnetic field excitation. A large delay bandwidth product (0.39) is obtained, which has potential application in quantum optics and communications. The experimental results are in good agreement with simulated results.

Inverse Stochastic Resonance in Cerebellar Purkinje Cells.

Directory of Open Access Journals (Sweden)

Anatoly Buchin

2016-08-01

Full Text Available Purkinje neurons play an important role in cerebellar computation since their axons are the only projection from the cerebellar cortex to deeper cerebellar structures. They have complex internal dynamics, which allow them to fire spontaneously, display bistability, and also to be involved in network phenomena such as high frequency oscillations and travelling waves. Purkinje cells exhibit type II excitability, which can be revealed by a discontinuity in their f-I curves. We show that this excitability mechanism allows Purkinje cells to be efficiently inhibited by noise of a particular variance, a phenomenon known as inverse stochastic resonance (ISR. While ISR has been described in theoretical models of single neurons, here we provide the first experimental evidence for this effect. We find that an adaptive exponential integrate-and-fire model fitted to the basic Purkinje cell characteristics using a modified dynamic IV method displays ISR and bistability between the resting state and a repetitive activity limit cycle. ISR allows the Purkinje cell to operate in different functional regimes: the all-or-none toggle or the linear filter mode, depending on the variance of the synaptic input. We propose that synaptic noise allows Purkinje cells to quickly switch between these functional regimes. Using mutual information analysis, we demonstrate that ISR can lead to a locally optimal information transfer between the input and output spike train of the Purkinje cell. These results provide the first experimental evidence for ISR and suggest a functional role for ISR in cerebellar information processing.

Set up of a method for the adjustment of resonance parameters on integral experiments

International Nuclear Information System (INIS)

Blaise, P.

1996-01-01

Resonance parameters for actinides play a significant role in the neutronic characteristics of all reactor types. All the major integral parameters strongly depend on the nuclear data of the isotopes in the resonance-energy regions.The author sets up a method for the adjustment of resonance parameters taking into account the self-shielding effects and restricting the cross section deconvolution problem to a limited energy region. (N.T.)

Dynamics of bound vector solitons induced by stochastic perturbations: Soliton breakup and soliton switching

International Nuclear Information System (INIS)

Sun, Zhi-Yuan; Gao, Yi-Tian; Yu, Xin; Liu, Ying

2013-01-01

We respectively investigate breakup and switching of the Manakov-typed bound vector solitons (BVSs) induced by two types of stochastic perturbations: the homogenous and nonhomogenous. Symmetry-recovering is discovered for the asymmetrical homogenous case, while soliton switching is found to relate with the perturbation amplitude and soliton coherence. Simulations show that soliton switching in the circularly-polarized light system is much weaker than that in the Manakov and linearly-polarized systems. In addition, the homogenous perturbations can enhance the soliton switching in both of the Manakov and non-integrable (linearly- and circularly-polarized) systems. Our results might be helpful in interpreting dynamics of the BVSs with stochastic noises in nonlinear optics or with stochastic quantum fluctuations in Bose–Einstein condensates.

Stochastic optimization methods

CERN Document Server

Marti, Kurt

2005-01-01

Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.

Measurement of the Z Resonance Parameters at LEP

CERN Document Server

Barate, R; Ghez, P; Goy, C; Lees, J P; Lucotte, A; Merle, E; Minard, M N; Pietrzyk, B; Alemany, R; Casado, M P; Chmeissani, M; Comas, P; Crespo, J M; Fernández, E; Fernández-Bosman, M; Garrido, L; Graugès-Pous, E; Juste, A; Martínez, M; Merino, G; Miquel, R; Mir, L M; Orteu, S; Pacheco, A; Park, I C; Perlas, J A; Riu, I; Sánchez, F; Colaleo, A; Creanza, D; De Palma, M; Iaselli, Giuseppe; Maggi, G; Maggi, M; Nuzzo, S; Ranieri, A; Raso, G; Ruggieri, F; Selvaggi, G; Silvestris, L; Tempesta, P; Tricomi, A; Zito, G; Huang, X; Lin, J; Ouyang, Q; Wang, T; Xie, Y; Xu, R; Xue, S; Zhang, J; Zhang, L; Zhao, W; Abbaneo, D; Bazarko, A; Becker, U; Boix, G; Bird, F; Blucher, E; Bonvicini, G; Bright-Thomas, P G; Cattaneo, M; Cerutti, F; Ciulli, V; Dissertori, G; Drevermann, H; Forty, Roger W; Frank, M; Greening, T C; Hagelberg, R; Halley, A W; Hansen, J B; Harvey, J; Jacobsen, R; Janot, P; Jost, B; Knobloch, J; Lazeyras, Pierre; Lehraus, Ivan; Maley, P; Mato, P; May, J; Moutoussi, A; Ranjard, F; Rolandi, Luigi; Schlatter, W D; Schmitt, M; Schneider, O; Spagnolo, P; Tejessy, W; Teubert, F; Tomalin, I R; Tournefier, E; Veenhof, R; Wiedenmann, W; Wright, A E; Ajaltouni, Ziad J; Badaud, F; Chazelle, G; Deschamps, O; Falvard, A; Ferdi, C; Gay, P; Guicheney, C; Henrard, P; Jousset, J; Michel, B; Monteil, S; Montret, J C; Pallin, D; Perret, P; Podlyski, F; Bertelsen, H; Fernley, T; Hansen, F; Hansen, J D; Hansen, J R; Hansen, P H; Lindahl, A; Møllerud, R; Nilsson, B S; Rensch, B; Wäänänen, A; Daskalakis, G; Kyriakis, A; Markou, C; Simopoulou, Errietta; Siotis, I; Vayaki, Anna; Blondel, A; Bonneaud, G R; Brient, J C; Rougé, A; Rumpf, M; Swynghedauw, M; Tanaka, R; Verderi, M; Videau, H L; Focardi, E; Parrini, G; Zachariadou, K; Cavanaugh, R J; Corden, M; Georgiopoulos, C H; Antonelli, A; Bencivenni, G; Bologna, G; Bossi, F; Campana, P; Capon, G; Chiarella, V; Felici, G; Laurelli, P; Mannocchi, G; Murtas, F; Murtas, G P; Passalacqua, L; Pepé-Altarelli, M; Picchi, P; Colrain, P; ten Have, I; Hughes, I S; Knowles, I G; Lynch, J G; Morton, W T; Raine, C; Reeves, P; O'Shea, V; Scarr, J M; Smith, K; Thompson, A S; Turnbull, R M; Buchmüller, O L; Dhamotharan, S; Geweniger, C; Hanke, P; Hansper, G; Hepp, V; Kluge, E E; Putzer, A; Sommer, J; Tittel, K; Werner, S; Wunsch, M; Beuselinck, R; Binnie, David M; Cameron, W; Dornan, Peter J; Girone, M; Goodsir, S M; Martin, E B; Marinelli, N; Nash, J; Sciabà, A; Sedgbeer, J K; Thomson, E; Williams, M D; Ghete, V M; Girtler, P; Kneringer, E; Kuhn, D; Rudolph, G; Bowdery, C K; Buck, P G; Finch, A J; Foster, F; Hughes, G; Jones, R W L; Keemer, N R; Robertson, N A; Sloan, Terence; Snow, S W; Williams, M I; Bauerdick, L A T; Van Gemmeren, P; Giehl, I; Jakobs, K; Kasemann, M; Kleinknecht, K; Quast, G; Renk, B; Rohne, E; Sander, H G; Schmelling, M; Wachsmuth, H W; Wanke, R; Zeitnitz, C; Aubert, Jean-Jacques; Benchouk, C; Bonissent, A; Carr, J; Coyle, P; Etienne, F; Motsch, F; Payre, P; Rousseau, D; Talby, M; Thulasidas, M; Aleppo, M; Antonelli, M; Ragusa, F; Büscher, V; Dietl, H; Ganis, G; Hüttmann, K; Lütjens, G; Mannert, C; Männer, W; Moser, H G; Schael, S; Settles, Ronald; Seywerd, H C J; Stenzel, H; Wolf, G; Azzurri, P; Boucrot, J; Callot, O; Chen, S; Cordier, A; Davier, M; Duflot, L; Grivaz, J F; Heusse, P; Jacholkowska, A; Le Diberder, F R; Lefrançois, J; Lutz, A M; Schune, M H; Veillet, J J; Videau, I; Zerwas, D; Bagliesi, G; Bettarini, S; Boccali, T; Bozzi, C; Calderini, G; Dell'Orso, R; Fantechi, R; Ferrante, I; Fidecaro, F; Foà, L; Giassi, A; Gregorio, A; Ligabue, F; Lusiani, A; Marrocchesi, P S; Messineo, A; Palla, Fabrizio; Rizzo, G; Sanguinetti, G; Sguazzoni, G; Steinberger, Jack; Tenchini, Roberto; Vannini, C; Venturi, A; Verdini, P G; Blair, G A; Cowan, G D; Green, M G; Medcalf, T; Strong, J A; Von Wimmersperg-Töller, J H; Botterill, David R; Clifft, R W; Edgecock, T R; Edwards, M; Haywood, S J; Norton, P R; Thompson, J C; Bloch-Devaux, B; Colas, P; Emery, S; Kozanecki, Witold; Lançon, E; Lemaire, M C; Locci, E; Pérez, P; Rander, J; Renardy, J F; Roussarie, A; Schuller, J P; Schwindling, J; Vallage, B; Black, S N; Dann, J H; Kim, H Y; Konstantinidis, N P; Litke, A M; McNeil, M A; Taylor, G; Booth, C N; Cartwright, S L; Combley, F; Lehto, M H; Thompson, L F; Affholderbach, K; Barberio, E; Böhrer, A; Brandt, S; Burkhardt, H; Feigl, E; Grupen, Claus; Hess, J; Lutters, G; Meinhard, H; Minguet-Rodríguez, J A; Mirabito, L; Misiejuk, A; Neugebauer, E; Prange, G; Rivera, F; Saraiva, P; Schäfer, U; Sieler, U; Smolik, L; Stephan, F; Trier, H; Apollonio, M; Bosisio, L; Della Marina, R; Giannini, G; Gobbo, B; Musolino, G; Pitis, L; Kim, H; Rothberg, J E; Wasserbaech, S R; Armstrong, S R; Bellantoni, L; Cinabro, D; Conway, J S; Elmer, P; Feng, Z; Ferguson, D P S; Gao, Y; González, S; Grahl, J; Harton, J L; Hayes, O J; Hu, H; Jin, S; Johnson, R P; Kile, J; McNamara, P A; Nielsen, J; Orejudos, W; Pan, Y B; Saadi, Y; Scott, I J; Sharma, V; Walsh, A M; Walsh, J; Wear, J; Wu Sau Lan; Wu, X; Yamartino, J M; Zobernig, G

2000-01-01

The properties of the Z resonance are measured from the analysis of 4.5 million Z decays into fermion pairs collected with the \\Aleph\\ detector at L EP. The data are consistent with lepton universality. The resonance parameters are measured to be $\\MZ=(91.1885 \\pm 0.0031)~\\Gevcc$, $\\GZ= (2.4951 \\pm 0.0043)~\\GeV$, $\\spol=(41.559 \\pm 0.058)$~nb and, combining the three lepton flavours $\\Rl= 20.725\\pm 0.039$. The corresponding number of light neutrino species is $N_{\

Shifts and widths of p-wave confinement induced resonances in atomic waveguides

International Nuclear Information System (INIS)

Saeidian, Shahpoor; Melezhik, Vladimir S; Schmelcher, Peter

2015-01-01

We develop and analyze a theoretical model to study p-wave Feshbach resonances of identical fermions in atomic waveguides by extending the two-channel model of Lange et al (2009 Phys. Rev. A 79 013622) and Saeidian et al (2012 Phys. Rev. A 86 062713). The experimentally known parameters of Feshbach resonances in free space are used as input of the model. We calculate the shifts and widths of p-wave magnetic Feshbach resonance of 40 K atoms emerging in harmonic waveguides as p-wave confinement induced resonance (CIR). Particularly, we show a possibility to control the width and shift of the p-wave CIR by the trap frequency and the applied magnetic field which could be used in corresponding experiments. Our analysis also demonstrates the importance of the inclusion of the effective range in the computational schemes for the description of the p-wave CIRs contrary to the case of s-wave CIRs where the influence of this term is negligible. (paper)

Control of deterministic and stochastic systems with several small parameters - A survey

Directory of Open Access Journals (Sweden)

Vasile Dragan

2009-07-01

Full Text Available The past three decades of research on multiparametric singularly perturbed systems are reviewed, including recent results. Particular attention is paid to stability analysis, control, filtering problems and dynamic games. First, a parameter-independent design methodology is summarized, which employs a two-time-scale and descriptor system approach without information on the small parameters. Further, variational computational algorithms are included to avoid ill-conditioned systems : the exact slow-fast decomposition method, the recursive algorithm and Newton's method are considered in particular. Convergence results are presented and the existence and uniqueness of the solutions are discussed. Second, the new results obtained via the stochastic approach are presented. Finally, the results of a simulation of a practical power system are presented to validate the efficiency of the considered design methods.

Transport of radionuclides in stochastic media: 2. evaluation of the parameters

International Nuclear Information System (INIS)

Smidts, O.F.

1996-01-01

This paper shows how we may evaluate in a hydrogeological context (i.e. with hypotheses and parameters commonly encountered in hydrogeology) the different coefficients introduced in the three-dimensional quasi-asymptotic equation found previously (see this issue). The evaluation is based on stochastic models developed in hydrogeology and based on field experiments. An analytical evaluation is made for a simple model of the velocity autocorrelation tensor. Numerical values of the coefficients are given. Next, we applied the model in planar geometry. Exact solutions of the quasi-asymptotic equation are shown in this case. In particular, we examined the differences between our model and the model of Williams in fractured rocks. (Author)

Disordered resonant media: Self-induced transparency versus light localization

Science.gov (United States)

Novitsky, Denis V.

2018-01-01

We propose a concept of disordered resonant media, which are characterized by random variations of their parameters along the light propagation direction. In particular, a simple model of disorder considered in the paper implies random change of the density of active particles (two-level atoms). Within this model, the effect of disorder on self-induced transparency (SIT) is analyzed using numerical simulations of light pulse propagation through the medium. The transition from the SIT to localization regime is revealed as well as its dependence on the disorder level, atom density, medium thickness, and period of random variations.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter; Taká č, Martin

2017-01-01

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter

2017-06-04

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Rho resonance parameters from lattice QCD

Energy Technology Data Exchange (ETDEWEB)

Guo, Dehua; Alexandru, Andrei; Molina, Raquel; Döring, Michael

2016-08-01

We perform a high-precision calculation of the phase shifts for $\\pi$-$\\pi$ scattering in the I = 1, J = 1 channel in the elastic region using elongated lattices with two mass-degenerate quark favors ($N_f = 2$). We extract the $\\rho$ resonance parameters using a Breit-Wigner fit at two different quark masses, corresponding to $m_{\\pi} = 226$MeV and $m_{\\pi} = 315$MeV, and perform an extrapolation to the physical point. The extrapolation is based on a unitarized chiral perturbation theory model that describes well the phase-shifts around the resonance for both quark masses. We find that the extrapolated value, $m_{\\rho} = 720(1)(15)$MeV, is significantly lower that the physical rho mass and we argue that this shift could be due to the absence of the strange quark in our calculation.

Determination of the neutron resonance parameters for 206Pb and of the thermal neutron capture cross section for 206Pb and 209Bi

International Nuclear Information System (INIS)

Borella, A.

2005-01-01

Chapter 1 describes the motivation of the measurements (accelerator driven systems, stellar nucleosynthesis, neutron induced reactions on 206 Pb), the present status of the neutron capture data for 206 Pb and 209 Bi and the structure of this work. In Chapter 2 the basic reaction theory underlying this work is described. The neutron induced reaction mechanism and formalism are explained. The parameterisation of the cross section in terms of R-matrix theory is discussed and we put particular emphasis on the statistical behaviour of the resonance parameters and the impact of the angular distribution of gamma rays following neutron capture. The relation between experimental observables and the resonance parameters is discussed together with general comments related to resonance shape analysis. Chapter 3 is focused on the determination of resonance parameters for 206 Pb. We performed high-resolution transmission and capture measurements at the Time-Of-Flight (TOF) facility GELINA of the IRMM at Geel (B) and determined the resonance parameters. For nuclei like 206 Pb, where the total width is dominated by Γ n , the capture area allows to determine G . Transmission measurements were carried out to determine Γ n , and the statistical factor g of resonances. Before performing a Resonance Shape Analysis (RSA) on the transmission and capture data, we verified the neutron flux and resolution at GELINA. We also compared the characteristics of GELINA with those of the n-TOF facility at CERN. A special emphasis is placed on the total energy detection technique using C 6 D 6 detectors. This technique was applied for the determination of the capture cross section. To reduce systematic bias effects on the capture cross section, the response of the detectors was determined by Monte Carlo simulations, which has been validated by experiments. Using these response functions the partial capture cross sections for individual resonances of 206 Pb have been deduced, by unfolding the

The interpolation method of stochastic functions and the stochastic variational principle

International Nuclear Information System (INIS)

Liu Xianbin; Chen Qiu

1993-01-01

Uncertainties have been attaching more importance to increasingly in modern engineering structural design. Viewed on an appropriate scale, the inherent physical attributes (material properties) of many structural systems always exhibit some patterns of random variation in space and time, generally the random variation shows a small parameter fluctuation. For a linear mechanical system, the random variation is modeled as a random one of a linear partial differential operator and, in stochastic finite element method, a random variation of a stiffness matrix. Besides the stochasticity of the structural physical properties, the influences of random loads which always represent themselves as the random boundary conditions bring about much more complexities in structural analysis. Now the stochastic finite element method or the probabilistic finite element method is used to study the structural systems with random physical parameters, whether or not the loads are random. Differing from the general finite element theory, the main difficulty which the stochastic finite element method faces is the inverse operation of stochastic operators and stochastic matrices, since the inverse operators and the inverse matrices are statistically correlated to the random parameters and random loads. So far, many efforts have been made to obtain the reasonably approximate expressions of the inverse operators and inverse matrices, such as Perturbation Method, Neumann Expansion Method, Galerkin Method (in appropriate Hilbert Spaces defined for random functions), Orthogonal Expansion Method. Among these methods, Perturbation Method appear to be the most available. The advantage of these methods is that the fairly accurate response statistics can be obtained under the condition of the finite information of the input. However, the second-order statistics obtained by use of Perturbation Method and Neumann Expansion Method are not always the appropriate ones, because the relevant second

Seismic Parameters of Mining-Induced Aftershock Sequences for Re-entry Protocol Development

Science.gov (United States)

Vallejos, Javier A.; Estay, Rodrigo A.

2018-03-01

A common characteristic of deep mines in hard rock is induced seismicity. This results from stress changes and rock failure around mining excavations. Following large seismic events, there is an increase in the levels of seismicity, which gradually decay with time. Restricting access to areas of a mine for enough time to allow this decay of seismic events is the main approach in re-entry strategies. The statistical properties of aftershock sequences can be studied with three scaling relations: (1) Gutenberg-Richter frequency magnitude, (2) the modified Omori's law (MOL) for the temporal decay, and (3) Båth's law for the magnitude of the largest aftershock. In this paper, these three scaling relations, in addition to the stochastic Reasenberg-Jones model are applied to study the characteristic parameters of 11 large magnitude mining-induced aftershock sequences in four mines in Ontario, Canada. To provide guidelines for re-entry protocol development, the dependence of the scaling relation parameters on the magnitude of the main event are studied. Some relations between the parameters and the magnitude of the main event are found. Using these relationships and the scaling relations, a space-time-magnitude re-entry protocol is developed. These findings provide a first approximation to concise and well-justified guidelines for re-entry protocol development applicable to the range of mining conditions found in Ontario, Canada.

Do stochastic inhomogeneities affect dark-energy precision measurements?

Science.gov (United States)

Ben-Dayan, I; Gasperini, M; Marozzi, G; Nugier, F; Veneziano, G

2013-01-11

The effect of a stochastic background of cosmological perturbations on the luminosity-redshift relation is computed to second order through a recently proposed covariant and gauge-invariant light-cone averaging procedure. The resulting expressions are free from both ultraviolet and infrared divergences, implying that such perturbations cannot mimic a sizable fraction of dark energy. Different averages are estimated and depend on the particular function of the luminosity distance being averaged. The energy flux being minimally affected by perturbations at large z is proposed as the best choice for precision estimates of dark-energy parameters. Nonetheless, its irreducible (stochastic) variance induces statistical errors on Ω(Λ)(z) typically lying in the few-percent range.

Do stochastic inhomogeneities affect dark-energy precision measurements?

CERN Document Server

Ben-Dayan, Ido; Marozzi, Giovanni; Nugier, Fabien; Veneziano, Gabriele

2013-01-01

The effect of a stochastic background of cosmological perturbations on the luminosity-redshift relation is computed to second order through a recently proposed covariant and gauge-invariant light-cone averaging procedure. The resulting expressions are free from both ultraviolet and infrared divergences, implying that such perturbations cannot mimic a sizable fraction of dark energy. Different averages are estimated and depend on the particular function of the luminosity distance being averaged. The energy flux, being minimally affected by perturbations at large z, is proposed as the best choice for precision estimates of dark-energy parameters. Nonetheless, its irreducible (stochastic) variance induces statistical errors on \\Omega_{\\Lambda}(z) typically lying in the few-percent range.

Isoscalar giant resonances and Landau parameters with density-dependent effective interactions

International Nuclear Information System (INIS)

Kohno, Michio; Ando, Kazuhiko

1979-01-01

Discussion is given on the relations between the Landau parameters and the isoscalar giant (quadrupole- and monopole-) resonance energies by using general density-dependent interactions. In the limit of infinite nuclear matter, the isoscalar giant quadrupole energy is shown to depend not only on the effective mass but also on the Landau parameter F 2 . Collective energies of the isoscalar giant resonances are calculated for 16 O and 40 Ca with four different effective interactions, G-0, B1, SII and SV, by using the scaling- and constrained Hartree-Fock-methods. It is shown that the dependence of the collective energies on the effective interactions is essentially determined by the Landau parameters. The G-0 force is found to be most successful in reproducing the giant resonance energies. Validity of the RPA-moment theorems is examined for the case of local density-dependent interactions. (author)

Tunnel-induced Dipolar Resonances in a Double-well Potential.

Science.gov (United States)

Schulz, Bruno; Saenz, Alejandro

2016-11-18

A system of two dipolar particles that are confined in a double-well potential and interact via a realistic isotropic interaction potential is investigated as a protoype for ultracold atoms with a magnetic dipole moment or ultracold dipolar heteronuclear diatomic molecules in double-well traps or in optical lattices. The resulting energy spectrum is discussed as a function of the dipole-dipole interaction strength. The variation of the strength of the dipole-dipole interaction is found to lead to various resonance phenomena. Among those are the previously discussed inelastic confinement-induced resonances as well as the dipole-induced resonances. It is found that the double-well potential gives rise to a new type of resonances, tunnel-induced dipolar ones. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the theory of stochastic dynamics of magnetically confined plasma

Energy Technology Data Exchange (ETDEWEB)

El-Sharif, R.N.; El-Atoy, N.S. [Plasma and Nuclear Fusion Dept., N.R.C, Atomic Energy Authority, Cairo (Egypt)]|[Physics Dept., Girls Colleges, KSA (Saudi Arabia)

2004-07-01

This work is devoted to a study of the motion of plasma electrons in a system of two fields, a magnetic field along z-axis and wave-packet field, which propagates in the x-z plane. The strongest interaction between plasma electrons and both fields is due to their resonance with these fields. The motion of plasma electrons become stochastic when a set of resonance overlapping. Conditions for stochasticity are obtained. (orig.)

On the theory of stochastic dynamics of magnetically confined plasma

International Nuclear Information System (INIS)

El-Sharif, R.N.; El-Atoy, N.S.

2004-01-01

This work is devoted to a study of the motion of plasma electrons in a system of two fields, a magnetic field along z-axis and wave-packet field, which propagates in the x-z plane. The strongest interaction between plasma electrons and both fields is due to their resonance with these fields. The motion of plasma electrons become stochastic when a set of resonance overlapping. Conditions for stochasticity are obtained. (orig.)

Stochastic resonance is applied to quantitative analysis for weak chromatographic signal of glyburide in plasma

International Nuclear Information System (INIS)

Zhang Wei; Xiang Bingren; Wu Yanwei; Shang Erxin

2005-01-01

Based on the theory of stochastic resonance, a new method carried on the quantitive analysis to weak chromatographic signal of glyburide in plasma, which was embedded in the noise background and the signal-to-noise ratio (SNR) of HPLC-UV is enhanced remarkably. This method enhances the quantification limit to 1 ng ml -1 , which is the same as HPLC-MS, and makes it possible to detect the weak signal accurately by HPLC-UV, which was not suitable before. The results showed good recovery and linear range from 1 to 50 ng ml -1 of glyburide in plasma and the method can be used for quantitative analysis of glyburide

Delay-enhanced stability and stochastic resonance in perception bistability under non-Gaussian noise

International Nuclear Information System (INIS)

Yang, Tao; Zeng, Chunhua; Liu, Ruifen; Wang, Hua; Mei, Dongcheng

2015-01-01

In this paper we investigate the effect of time delay in an attractor network model of perception bistability driven by non-Gaussian noise. Using delay Langevin and Fokker–Planck approaches, the theoretical analysis of the model is presented. It is found that the mean first-passage time (MFPT) as a function of the time delay exhibits a maximum, which is identified as the characteristic of the delay-enhanced stability of the system. This is different to the case of noise-enhanced stability. The non-Gaussian noise-enhanced stability of the system is also analyzed. The signal-to-noise ratio (SNR) as a function of the noise intensity exhibits a maximum. This maximum implies the identifying characteristic of stochastic resonance (SR), and the time delay and non-Gaussian noise can enhance the SR phenomenon. (paper)

Numerical analysis of the resonance mechanism of the lumped parameter system model for acoustic mine detection

International Nuclear Information System (INIS)

Wang Chi; Zhou Yu-Qiu; Shen Gao-Wei; Wu Wen-Wen; Ding Wei

2013-01-01

The method of numerical analysis is employed to study the resonance mechanism of the lumped parameter system model for acoustic mine detection. Based on the basic principle of the acoustic resonance technique for mine detection and the characteristics of low-frequency acoustics, the ''soil-mine'' system could be equivalent to a damping ''mass-spring'' resonance model with a lumped parameter analysis method. The dynamic simulation software, Adams, is adopted to analyze the lumped parameter system model numerically. The simulated resonance frequency and anti-resonance frequency are 151 Hz and 512 Hz respectively, basically in agreement with the published resonance frequency of 155 Hz and anti-resonance frequency of 513 Hz, which were measured in the experiment. Therefore, the technique of numerical simulation is validated to have the potential for analyzing the acoustic mine detection model quantitatively. The influences of the soil and mine parameters on the resonance characteristics of the soil—mine system could be investigated by changing the parameter setup in a flexible manner. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

Parameters optimization for magnetic resonance coupling wireless power transmission.

Science.gov (United States)

Li, Changsheng; Zhang, He; Jiang, Xiaohua

2014-01-01

Taking maximum power transmission and power stable transmission as research objectives, optimal design for the wireless power transmission system based on magnetic resonance coupling is carried out in this paper. Firstly, based on the mutual coupling model, mathematical expressions of optimal coupling coefficients for the maximum power transmission target are deduced. Whereafter, methods of enhancing power transmission stability based on parameters optimal design are investigated. It is found that the sensitivity of the load power to the transmission parameters can be reduced and the power transmission stability can be enhanced by improving the system resonance frequency or coupling coefficient between the driving/pick-up coil and the transmission/receiving coil. Experiment results are well conformed to the theoretical analysis conclusions.

Noise in nonlinear nanoelectromechanical resonators

Science.gov (United States)

Guerra Vidal, Diego N.

Nano-Electro-Mechanical Systems (NEMS), due to their nanometer scale size, possess a number of desirable attributes: high sensitivity to applied forces, fast response times, high resonance frequencies and low power consumption. However, ultra small size and low power handling result in unwanted consequences: smaller signal size and higher dissipation, making the NEMS devices more susceptible to external and intrinsic noise. The simplest version of a NEMS, a suspended nanomechanical structure with two distinct excitation states, can be used as an archetypal two state system to study a plethora of fundamental phenomena such as Duffing nonlinearity, stochastic resonance, and macroscopic quantum tunneling at low temperatures. From a technical perspective, there are numerous applications such nanomechanical memory elements, microwave switches and nanomechanical computation. The control and manipulation of the mechanical response of these two state systems can be realized by exploiting a (seemingly) counterintuitive physical phenomenon, Stochastic Resonance: in a noisy nonlinear mechanical system, the presence of noise can enhance the system response to an external stimulus. This Thesis is mainly dedicated to study possible applications of Stochastic Resonance in two-state nanomechanical systems. First, on chip signal amplification by 1/falpha is observed. The effectiveness of the noise assisted amplification is observed to decrease with increasing a. Experimental evidence shows an increase in asymmetry between the two states with increasing noise color. Considering the prevalence of 1/f alpha noise in the materials in integrated circuits, the signal enhancement demonstrated here, suggests beneficial use of the otherwise detrimental noise. Finally, a nanomechanical device, operating as a reprogrammable logic gate, and performing fundamental logic functions such as AND/OR and NAND/NOR is presented. The logic function can be programmed (from AND to OR) dynamically, by

Enhancement of information transmission with stochastic resonance in hippocampal CA1 neuron models: effects of noise input location.

Science.gov (United States)

Kawaguchi, Minato; Mino, Hiroyuki; Durand, Dominique M

2007-01-01

Stochastic resonance (SR) has been shown to enhance the signal to noise ratio or detection of signals in neurons. It is not yet clear how this effect of SR on the signal to noise ratio affects signal processing in neural networks. In this paper, we investigate the effects of the location of background noise input on information transmission in a hippocampal CA1 neuron model. In the computer simulation, random sub-threshold spike trains (signal) generated by a filtered homogeneous Poisson process were presented repeatedly to the middle point of the main apical branch, while the homogeneous Poisson shot noise (background noise) was applied to a location of the dendrite in the hippocampal CA1 model consisting of the soma with a sodium, a calcium, and five potassium channels. The location of the background noise input was varied along the dendrites to investigate the effects of background noise input location on information transmission. The computer simulation results show that the information rate reached a maximum value for an optimal amplitude of the background noise amplitude. It is also shown that this optimal amplitude of the background noise is independent of the distance between the soma and the noise input location. The results also show that the location of the background noise input does not significantly affect the maximum values of the information rates generated by stochastic resonance.

Buffer-gas-induced absorption resonances in Rb vapor

International Nuclear Information System (INIS)

Mikhailov, Eugeniy E.; Novikova, Irina; Rostovtsev, Yuri V.; Welch, George R.

2004-01-01

We observe transformation of the electromagnetically induced transparency (EIT) resonance into an absorption resonance in a Λ interaction configuration in a cell filled with 87 Rb and a buffer gas. This transformation occurs as one-photon detuning of the coupling fields is varied from the atomic transition. No such absorption resonance is found in the absence of a buffer gas. The width of the absorption resonance is several times smaller than the width of the EIT resonance, and the changes of absorption near these resonances are about the same. Similar absorption resonances are detected in the Hanle configuration in a buffered cell

Development of Vestibular Stochastic Resonance as a Sensorimotor Countermeasure: Improving Otolith Ocular and Motor Task Responses

Science.gov (United States)

Mulavara, Ajitkumar; Fiedler, Matthew; DeDios,Yiri E.; Galvan, Raquel; Bloomberg, Jacob; Wood, Scott

2011-01-01

Astronauts experience disturbances in sensorimotor function after spaceflight during the initial introduction to a gravitational environment, especially after long-duration missions. Stochastic resonance (SR) is a mechanism by which noise can assist and enhance the response of neural systems to relevant, imperceptible sensory signals. We have previously shown that imperceptible electrical stimulation of the vestibular system enhances balance performance while standing on an unstable surface. The goal of our present study is to develop a countermeasure based on vestibular SR that could improve central interpretation of vestibular input and improve motor task responses to mitigate associated risks.

Infinite stochastic acceleration of charged particles from non-relativistic initial energies

International Nuclear Information System (INIS)

Buts, V.A.; Manujlenko, O.V.; Turkin, Yu.A.

1997-01-01

Stochastic charged particle acceleration by electro-magnetic field due to overlapping of non-linear cyclotron resonances is considered. It was shown that non-relativistic charged particles are involved in infinitive stochastic acceleration regime. This effect can be used for stochastic acceleration or for plasma heating by regular electro-magnetic fields

Sequential stochastic optimization

CERN Document Server

Cairoli, Renzo

1996-01-01

Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet

Chaos-induced resonant effects and its control

International Nuclear Information System (INIS)

Zambrano, Samuel; Casado, Jose M.; Sanjuan, Miguel A.F.

2007-01-01

This Letter shows that a suitable chaotic signal can induce resonant effects analogous to those observed in presence of noise in a bistable system under periodic forcing. By constructing groups of chaotic and random perturbations with similar one-time statistics we show that in some cases chaos and noise induce indistinguishable resonant effects. This reinforces the conjecture by which in some situations where noise is supposed to play a key role maybe chaos is the key ingredient. Here we also show that the presence of a chaotic signal as the perturbation leading to a resonance opens new control perspectives based on our ability to stabilize chaos in different periodic orbits. A discussion of the possible implications of these facts is also presented at the end of the Letter

Theoretical approach for plasma series resonance effect in geometrically symmetric dual radio frequency plasma

International Nuclear Information System (INIS)

Bora, B.; Bhuyan, H.; Favre, M.; Wyndham, E.; Chuaqui, H.

2012-01-01

Plasma series resonance (PSR) effect is well known in geometrically asymmetric capacitively couple radio frequency plasma. However, plasma series resonance effect in geometrically symmetric plasma has not been properly investigated. In this work, a theoretical approach is made to investigate the plasma series resonance effect and its influence on Ohmic and stochastic heating in geometrically symmetric discharge. Electrical asymmetry effect by means of dual frequency voltage waveform is applied to excite the plasma series resonance. The results show considerable variation in heating with phase difference between the voltage waveforms, which may be applicable in controlling the plasma parameters in such plasma.

Time-ordered product expansions for computational stochastic system biology

International Nuclear Information System (INIS)

Mjolsness, Eric

2013-01-01

The time-ordered product framework of quantum field theory can also be used to understand salient phenomena in stochastic biochemical networks. It is used here to derive Gillespie’s stochastic simulation algorithm (SSA) for chemical reaction networks; consequently, the SSA can be interpreted in terms of Feynman diagrams. It is also used here to derive other, more general simulation and parameter-learning algorithms including simulation algorithms for networks of stochastic reaction-like processes operating on parameterized objects, and also hybrid stochastic reaction/differential equation models in which systems of ordinary differential equations evolve the parameters of objects that can also undergo stochastic reactions. Thus, the time-ordered product expansion can be used systematically to derive simulation and parameter-fitting algorithms for stochastic systems. (paper)

Mean square stabilization and mean square exponential stabilization of stochastic BAM neural networks with Markovian jumping parameters

International Nuclear Information System (INIS)

Ye, Zhiyong; Zhang, He; Zhang, Hongyu; Zhang, Hua; Lu, Guichen

2015-01-01

Highlights: •This paper introduces a non-conservative Lyapunov functional. •The achieved results impose non-conservative and can be widely used. •The conditions are easily checked by the Matlab LMI Tool Box. The desired state feedback controller can be well represented by the conditions. -- Abstract: This paper addresses the mean square exponential stabilization problem of stochastic bidirectional associative memory (BAM) neural networks with Markovian jumping parameters and time-varying delays. By establishing a proper Lyapunov–Krasovskii functional and combining with LMIs technique, several sufficient conditions are derived for ensuring exponential stabilization in the mean square sense of such stochastic BAM neural networks. In addition, the achieved results are not difficult to verify for determining the mean square exponential stabilization of delayed BAM neural networks with Markovian jumping parameters and impose less restrictive and less conservative than the ones in previous papers. Finally, numerical results are given to show the effectiveness and applicability of the achieved results

Topologically determined optimal stochastic resonance responses of spatially embedded networks

International Nuclear Information System (INIS)

Gosak, Marko; Marhl, Marko; Korosak, Dean

2011-01-01

We have analyzed the stochastic resonance phenomenon on spatial networks of bistable and excitable oscillators, which are connected according to their location and the amplitude of external forcing. By smoothly altering the network topology from a scale-free (SF) network with dominating long-range connections to a network where principally only adjacent oscillators are connected, we reveal that besides an optimal noise intensity, there is also a most favorable interaction topology at which the best correlation between the response of the network and the imposed weak external forcing is achieved. For various distributions of the amplitudes of external forcing, the optimal topology is always found in the intermediate regime between the highly heterogeneous SF network and the strong geometric regime. Our findings thus indicate that a suitable number of hubs and with that an optimal ratio between short- and long-range connections is necessary in order to obtain the best global response of a spatial network. Furthermore, we link the existence of the optimal interaction topology to a critical point indicating the transition from a long-range interactions-dominated network to a more lattice-like network structure.

Chemisorption-Induced Resonance Frequency Shift of a Microcantilever

International Nuclear Information System (INIS)

Zhang Ji-Qiao; Feng Xi-Qiao; Yu Shou-Wen; Huang Gan-Yun

2012-01-01

The autonomy and property of atoms/molecules adsorbed on the surface of a microcantilever can be probed by measuring its resonance frequency shift due to adsorption. The resonance frequency change of a cantilever induced by chemisorption is theoretically studied. Oxygen chemisorbed on the Si(100) surface is taken as a representative example. We demonstrate that the resonant response of the cantilever is mainly determined by the chemisorption-induced bending stiffness variation, which depends on the bond configurations formed by the adsorbed atoms and substrate atoms. This study is helpful for optimal design of microcantilever-based sensors for various applications. (condensed matter: structure, mechanical and thermal properties)

Impact of wave phase jumps on stochastic heating

International Nuclear Information System (INIS)

Zasenko, V.I.; Zagorodny, A.G.; Cherniak, O.M.

2016-01-01

Interaction of charged particles with fields of random waves brings about known effects of stochastic acceleration and heating. Jumps of wave phases can increase the intensity of these processes substantially. Numerical simulation of particle heating and acceleration by waves with regular phases, waves with jumping phase and stochastic electric field impulses is performed. Comparison of the results shows that to some extent an impact of phase jumps is similar to the action of separate field impulses. Jumps of phase not only increase the intensity of resonant particle heating but involves in this process non-resonant particles from a wide range of initial velocities

Stochastic resonance of ensemble neurons for transient spike trains: Wavelet analysis

International Nuclear Information System (INIS)

Hasegawa, Hideo

2002-01-01

By using the wavelet transformation (WT), I have analyzed the response of an ensemble of N (=1, 10, 100, and 500) Hodgkin-Huxley neurons to transient M-pulse spike trains (M=1 to 3) with independent Gaussian noises. The cross correlation between the input and output signals is expressed in terms of the WT expansion coefficients. The signal-to-noise ratio (SNR) is evaluated by using the denoising method within the WT, by which the noise contribution is extracted from the output signals. Although the response of a single (N=1) neuron to subthreshold transient signals with noises is quite unreliable, the transmission fidelity assessed by the cross correlation and SNR is shown to be much improved by increasing the value of N: a population of neurons plays an indispensable role in the stochastic resonance (SR) for transient spike inputs. It is also shown that in a large-scale ensemble, the transmission fidelity for suprathreshold transient spikes is not significantly degraded by a weak noise which is responsible to SR for subthreshold inputs

Optically levitated nanoparticle as a model system for stochastic bistable dynamics.

Science.gov (United States)

Ricci, F; Rica, R A; Spasenović, M; Gieseler, J; Rondin, L; Novotny, L; Quidant, R

2017-05-09

Nano-mechanical resonators have gained an increasing importance in nanotechnology owing to their contributions to both fundamental and applied science. Yet, their small dimensions and mass raises some challenges as their dynamics gets dominated by nonlinearities that degrade their performance, for instance in sensing applications. Here, we report on the precise control of the nonlinear and stochastic bistable dynamics of a levitated nanoparticle in high vacuum. We demonstrate how it can lead to efficient signal amplification schemes, including stochastic resonance. This work contributes to showing the use of levitated nanoparticles as a model system for stochastic bistable dynamics, with applications to a wide variety of fields.

Noise transmission and delay-induced stochasticoscillations in biochemical network motifs

Institute of Scientific and Technical Information of China (English)

Liu Sheng-Jun; Wang Qi; Liu Bo; Yan Shi-Wei; Fumihiko Sakata

2011-01-01

With the aid of stochastic delayed-feedback differential equations,we derive an analytic expression for the power spectra of reacting molecules included in a generic biological network motif that is incorporated with a feedback mechanism and time delays in gene regulation.We systematically analyse the effects of time delays,the feedback mechanism,and biological stochasticity on the power spectra.It has been clarified that the time delays together with the feedback mechanism can induce stochastic oscillations at the molecular level and invalidate the noise addition rule for a modular description of the noise propagator.Delay-induced stochastic resonance can be expected,which is related to the stability loss of the reaction systems and Hopf bifurcation occurring for solutions of the corresponding deterministic reaction equations.Through the analysis of the power spectrum,a new approach is proposed to estimate the oscillation period.

Geotechnical parameter spatial distribution stochastic analysis based on multi-precision information assimilation

Science.gov (United States)

Wang, C.; Rubin, Y.

2014-12-01

Spatial distribution of important geotechnical parameter named compression modulus Es contributes considerably to the understanding of the underlying geological processes and the adequate assessment of the Es mechanics effects for differential settlement of large continuous structure foundation. These analyses should be derived using an assimilating approach that combines in-situ static cone penetration test (CPT) with borehole experiments. To achieve such a task, the Es distribution of stratum of silty clay in region A of China Expo Center (Shanghai) is studied using the Bayesian-maximum entropy method. This method integrates rigorously and efficiently multi-precision of different geotechnical investigations and sources of uncertainty. Single CPT samplings were modeled as a rational probability density curve by maximum entropy theory. Spatial prior multivariate probability density function (PDF) and likelihood PDF of the CPT positions were built by borehole experiments and the potential value of the prediction point, then, preceding numerical integration on the CPT probability density curves, the posterior probability density curve of the prediction point would be calculated by the Bayesian reverse interpolation framework. The results were compared between Gaussian Sequential Stochastic Simulation and Bayesian methods. The differences were also discussed between single CPT samplings of normal distribution and simulated probability density curve based on maximum entropy theory. It is shown that the study of Es spatial distributions can be improved by properly incorporating CPT sampling variation into interpolation process, whereas more informative estimations are generated by considering CPT Uncertainty for the estimation points. Calculation illustrates the significance of stochastic Es characterization in a stratum, and identifies limitations associated with inadequate geostatistical interpolation techniques. This characterization results will provide a multi

Stochastic Pi-calculus Revisited

DEFF Research Database (Denmark)

Cardelli, Luca; Mardare, Radu Iulian

2013-01-01

We develop a version of stochastic Pi-calculus with a semantics based on measure theory. We dene the behaviour of a process in a rate environment using measures over the measurable space of processes induced by structural congruence. We extend the stochastic bisimulation to include the concept of...

Wayside Bearing Fault Diagnosis Based on Envelope Analysis Paved with Time-Domain Interpolation Resampling and Weighted-Correlation-Coefficient-Guided Stochastic Resonance

Directory of Open Access Journals (Sweden)

Yongbin Liu

2017-01-01

Full Text Available Envelope spectrum analysis is a simple, effective, and classic method for bearing fault identification. However, in the wayside acoustic health monitoring system, owing to the high relative moving speed between the railway vehicle and the wayside mounted microphone, the recorded signal is embedded with Doppler effect, which brings in shift and expansion of the bearing fault characteristic frequency (FCF. What is more, the background noise is relatively heavy, which makes it difficult to identify the FCF. To solve the two problems, this study introduces solutions for the wayside acoustic fault diagnosis of train bearing based on Doppler effect reduction using the improved time-domain interpolation resampling (TIR method and diagnosis-relevant information enhancement using Weighted-Correlation-Coefficient-Guided Stochastic Resonance (WCCSR method. First, the traditional TIR method is improved by incorporating the original method with kinematic parameter estimation based on time-frequency analysis and curve fitting. Based on the estimated parameters, the Doppler effect is removed using the TIR easily. Second, WCCSR is employed to enhance the diagnosis-relevant period signal component in the obtained Doppler-free signal. Finally, paved with the above two procedures, the local fault is identified using envelope spectrum analysis. Simulated and experimental cases have verified the effectiveness of the proposed method.

Doubly stochastic radial basis function methods

Science.gov (United States)

Yang, Fenglian; Yan, Liang; Ling, Leevan

2018-06-01

We propose a doubly stochastic radial basis function (DSRBF) method for function recoveries. Instead of a constant, we treat the RBF shape parameters as stochastic variables whose distribution were determined by a stochastic leave-one-out cross validation (LOOCV) estimation. A careful operation count is provided in order to determine the ranges of all the parameters in our methods. The overhead cost for setting up the proposed DSRBF method is O (n2) for function recovery problems with n basis. Numerical experiments confirm that the proposed method not only outperforms constant shape parameter formulation (in terms of accuracy with comparable computational cost) but also the optimal LOOCV formulation (in terms of both accuracy and computational cost).

Phenomenology of stochastic exponential growth

Science.gov (United States)

Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya

2017-06-01

Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.

Detuned-resonator induced transparency in dielectric-loaded plasmonic waveguides

DEFF Research Database (Denmark)

Han, Zhanghua; García Ortíz, César Eduardo; Radko, Ilya P.

2013-01-01

We report on the experimental demonstration of detuned-resonator induced transparency in the near-infrared (∼800  nm) using two detuned racetrack resonators side-coupled to a bus waveguide. Both resonators and the bus waveguide are in the form of dielectric-loaded surface plasmon polariton...

Laser resonant ionization spectroscopy and laser-induced resonant fluorescence spectra of samarium atom

International Nuclear Information System (INIS)

Jin, Changtai

1995-01-01

We have measured new high-lying levels of Sm atom by two-colour resonant photoionisation spectroscopy; we have observed the isotope shifts of Sm atom by laser-induced resonant fluorescence spectroscopy; the lifetime of eight low-lying levels of Sm atom were measured by using pulsed laser-Boxcar technique in atomic beam.

Extending Stochastic Network Calculus to Loss Analysis

Directory of Open Access Journals (Sweden)

Chao Luo

2013-01-01

Full Text Available Loss is an important parameter of Quality of Service (QoS. Though stochastic network calculus is a very useful tool for performance evaluation of computer networks, existing studies on stochastic service guarantees mainly focused on the delay and backlog. Some efforts have been made to analyse loss by deterministic network calculus, but there are few results to extend stochastic network calculus for loss analysis. In this paper, we introduce a new parameter named loss factor into stochastic network calculus and then derive the loss bound through the existing arrival curve and service curve via this parameter. We then prove that our result is suitable for the networks with multiple input flows. Simulations show the impact of buffer size, arrival traffic, and service on the loss factor.

Parameter dependence of resonant spin torque magnetization reversal

International Nuclear Information System (INIS)

Fricke, L.; Serrano-Guisan, S.; Schumacher, H.W.

2012-01-01

We numerically study ultra fast resonant spin torque (ST) magnetization reversal in magnetic tunneling junctions (MTJ) driven by current pulses having a direct current (DC) and a resonant alternating current (AC) component. The precessional ST dynamics of the single domain MTJ free layer cell are modeled in the macro spin approximation. The energy efficiency, reversal time, and reversal reliability are investigated under variation of pulse parameters like direct and AC current amplitude, AC frequency and AC phase. We find a range of AC and direct current amplitudes where robust resonant ST reversal is obtained with faster switching time and reduced energy consumption per pulse compared to purely direct current ST reversal. However, for a certain range of AC and direct current amplitudes a strong dependence of the reversal properties on AC frequency and phase is found. Such regions of unreliable reversal must be avoided for ST memory applications.

Parameter dependence of resonant spin torque magnetization reversal

Science.gov (United States)

Fricke, L.; Serrano-Guisan, S.; Schumacher, H. W.

2012-04-01

We numerically study ultra fast resonant spin torque (ST) magnetization reversal in magnetic tunneling junctions (MTJ) driven by current pulses having a direct current (DC) and a resonant alternating current (AC) component. The precessional ST dynamics of the single domain MTJ free layer cell are modeled in the macro spin approximation. The energy efficiency, reversal time, and reversal reliability are investigated under variation of pulse parameters like direct and AC current amplitude, AC frequency and AC phase. We find a range of AC and direct current amplitudes where robust resonant ST reversal is obtained with faster switching time and reduced energy consumption per pulse compared to purely direct current ST reversal. However, for a certain range of AC and direct current amplitudes a strong dependence of the reversal properties on AC frequency and phase is found. Such regions of unreliable reversal must be avoided for ST memory applications.

QB1 - Stochastic Gene Regulation

Energy Technology Data Exchange (ETDEWEB)

Munsky, Brian [Los Alamos National Laboratory

2012-07-23

Summaries of this presentation are: (1) Stochastic fluctuations or 'noise' is present in the cell - Random motion and competition between reactants, Low copy, quantization of reactants, Upstream processes; (2) Fluctuations may be very important - Cell-to-cell variability, Cell fate decisions (switches), Signal amplification or damping, stochastic resonances; and (3) Some tools are available to mode these - Kinetic Monte Carlo simulations (SSA and variants), Moment approximation methods, Finite State Projection. We will see how modeling these reactions can tell us more about the underlying processes of gene regulation.

Stark-shift induced resonances in multiphoton ionization

International Nuclear Information System (INIS)

Potvliege, R M; Vuci, Svetlana

2006-01-01

The resonance enhancements marking the ATI spectrum of argon are discussed in the light of a recently compiled map of the quasienergies of this atom. Many of the dressed excited states of interest shift nonponderomotively in complicated ways, but keep an ionization width narrow enough to produce sharp substructures of both low and high ATI peaks through Stark-shift induced resonances. The most prominent enhancement observed in the high-order ATI peaks originates from ionization from the dressed ground state perturbed by the influence of neighbouring resonant dressed states

Dynamic analysis and reliability assessment of structures with uncertain-but-bounded parameters under stochastic process excitations

International Nuclear Information System (INIS)

Do, Duy Minh; Gao, Wei; Song, Chongmin; Tangaramvong, Sawekchai

2014-01-01

This paper presents the non-deterministic dynamic analysis and reliability assessment of structures with uncertain-but-bounded parameters under stochastic process excitations. Random ground acceleration from earthquake motion is adopted to illustrate the stochastic process force. The exact change ranges of natural frequencies, random vibration displacement and stress responses of structures are investigated under the interval analysis framework. Formulations for structural reliability are developed considering the safe boundary and structural random vibration responses as interval parameters. An improved particle swarm optimization algorithm, namely randomised lower sequence initialized high-order nonlinear particle swarm optimization algorithm, is employed to capture the better bounds of structural dynamic characteristics, random vibration responses and reliability. Three numerical examples are used to demonstrate the presented method for interval random vibration analysis and reliability assessment of structures. The accuracy of the results obtained by the presented method is verified by the randomised Quasi-Monte Carlo simulation method (QMCSM) and direct Monte Carlo simulation method (MCSM). - Highlights: • Interval uncertainty is introduced into structural random vibration responses. • Interval dynamic reliability assessments of structures are implemented. • Boundaries of structural dynamic response and reliability are achieved

Review of the different methods to derive average spacing from resolved resonance parameters sets

International Nuclear Information System (INIS)

Fort, E.; Derrien, H.; Lafond, D.

1979-12-01

The average spacing of resonances is an important parameter for statistical model calculations, especially concerning non fissile nuclei. The different methods to derive this average value from resonance parameters sets have been reviewed and analyzed in order to tentatively detect their respective weaknesses and propose recommendations. Possible improvements are suggested

Stochastic Analysis with Financial Applications

CERN Document Server

Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi

2011-01-01

Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li

Can intrinsic noise induce various resonant peaks?

Energy Technology Data Exchange (ETDEWEB)

Torres, J J; Marro, J; Mejias, J F, E-mail: jtorres@ugr.es [Institute Carlos I for Theoretical and Computational Physics and Departamento de Electromagnetismo y Fisica de la Materia, University of Granada, Granada (Spain)

2011-05-15

We theoretically describe how weak signals may be efficiently transmitted throughout more than one frequency range in noisy excitable media by a sort of stochastic multiresonance. This helps us to reinterpret recent experiments in neuroscience and to suggest that many other systems in nature might be able to exhibit several resonances. In fact, the observed behavior happens in our model as a result of competition between (i) changes in the transmitted signals as if the units were varying their activation threshold, and (ii) adaptive noise realized in the model as rapid activity-dependent fluctuations of the connection intensities. These two conditions are indeed known to characterize heterogeneously networked systems of excitable units, e.g. sets of neurons and synapses in the brain. Our results may find application also in the design of detector devices.

Can intrinsic noise induce various resonant peaks?

International Nuclear Information System (INIS)

Torres, J J; Marro, J; Mejias, J F

2011-01-01

We theoretically describe how weak signals may be efficiently transmitted throughout more than one frequency range in noisy excitable media by a sort of stochastic multiresonance. This helps us to reinterpret recent experiments in neuroscience and to suggest that many other systems in nature might be able to exhibit several resonances. In fact, the observed behavior happens in our model as a result of competition between (i) changes in the transmitted signals as if the units were varying their activation threshold, and (ii) adaptive noise realized in the model as rapid activity-dependent fluctuations of the connection intensities. These two conditions are indeed known to characterize heterogeneously networked systems of excitable units, e.g. sets of neurons and synapses in the brain. Our results may find application also in the design of detector devices.

Hafnium Resonance Parameter Analysis Using Neutron Capture and Transmission Experiments

International Nuclear Information System (INIS)

MJ Trbovich; DP Barry; RE Slovacck; Y Danon; RC Block; JA Burke; NJ Drindak; G Leinweber; RV Ballad

2004-01-01

The focus of this work is to determine resonance parameters for stable hafnium isotopes in the 0.005-200 eV region, with special emphasis on the overlapping 176 Hf and 178 Hf resonances near 8 eV. The large neutron cross section of hafnium, combined with its corrosion resistance and excellent mechanical properties, make it a useful material for controlling nuclear reactions. Experiments measuring neutron capture and transmission were performed at the Rensselaer Polytechnic Institute (RPI) electron linear accelerator (LINAC) using the time of flight method. 6 Li glass scintillation detectors were used for transmission experiments at flight path lengths of 15 and 25 m. Capture experiments were done using a sixteen section NaI(Tl) multiplicity detector at a flight path length of 25 m. These experiments utilized various thicknesses of metallic and isotopically-enriched liquid samples. The liquid samples were designed to provide information on the 176 Hf and 178 Hf contributions to the 8 eV doublet without saturation. Data analysis was done using the R-matrix Bayesian code SAMMY version M6 beta. SAMMY is able to account for experimental resolution effects for each of the experimental setups at the RPI LINAC, and also can correct for multiple scattering effects in neutron capture yield data. The combined capture and transmission data analysis yielded resonance parameters for all hafnium isotopes from 0.005-200 eV. Resonance integrals were calculated along with errors for each hafnium isotope using the NJOY [1] and INTER [2] codes. The isotopic resonance integrals calculated were significantly different than previously published values; however the calculated elemental hafnium resonance integral changed very little

Event-Based Variance-Constrained ${\\mathcal {H}}_{\\infty }$ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

Science.gov (United States)

Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

2018-03-01

This paper is concerned with the distributed filtering problem for a class of discrete time-varying stochastic parameter systems with error variance constraints over a sensor network where the sensor outputs are subject to successive missing measurements. The phenomenon of the successive missing measurements for each sensor is modeled via a sequence of mutually independent random variables obeying the Bernoulli binary distribution law. To reduce the frequency of unnecessary data transmission and alleviate the communication burden, an event-triggered mechanism is introduced for the sensor node such that only some vitally important data is transmitted to its neighboring sensors when specific events occur. The objective of the problem addressed is to design a time-varying filter such that both the requirements and the variance constraints are guaranteed over a given finite-horizon against the random parameter matrices, successive missing measurements, and stochastic noises. By recurring to stochastic analysis techniques, sufficient conditions are established to ensure the existence of the time-varying filters whose gain matrices are then explicitly characterized in term of the solutions to a series of recursive matrix inequalities. A numerical simulation example is provided to illustrate the effectiveness of the developed event-triggered distributed filter design strategy.

Remarks on stochastic acceleration

International Nuclear Information System (INIS)

Graeff, P.

1982-12-01

Stochastic acceleration and turbulent diffusion are strong turbulence problems since no expansion parameter exists. Hence the problem of finding rigorous results is of major interest both for checking approximations and for reference models. Since we have found a way of constructing such models in the turbulent diffusion case the question of the extension to stochastic acceleration now arises. The paper offers some possibilities illustrated by the case of 'stochastic free fall' which may be particularly interesting in the context of linear response theory. (orig.)

Stochasticity of phase trajectory of a charged particle in a plasma wave

International Nuclear Information System (INIS)

Murakami, Akihiko; Nomura, Yasuyuki; Momota, Hiromu.

1980-06-01

Stochastic behavior of charged particles in finite amplitude plasma waves is examined by means of particle simulations under the condition that Chirikov's criterion is broken down. The process of growint the stochastic region is clarified and accordingly the width of the stochastic region is discussed. Discussions on the effects of higher order resonances are also presented. (author)

Single spin stochastic optical reconstruction microscopy

OpenAIRE

Pfender, Matthias; Aslam, Nabeel; Waldherr, Gerald; Wrachtrup, Jörg

2014-01-01

We experimentally demonstrate precision addressing of single quantum emitters by combined optical microscopy and spin resonance techniques. To this end we utilize nitrogen-vacancy (NV) color centers in diamond confined within a few ten nanometers as individually resolvable quantum systems. By developing a stochastic optical reconstruction microscopy (STORM) technique for NV centers we are able to simultaneously perform sub diffraction-limit imaging and optically detected spin resonance (ODMR)...

Capture cross section and resonance parameters of thulium-169

International Nuclear Information System (INIS)

Arbo, J.C.; Felvinci, J.P.; Melkonian, E.; Havens, W.W. Jr.

1975-01-01

The previously analyzed energy range for thulium capture resonance parameters is extended from 1 keV to 2 keV. In addition, point and group averaged thulium cross section curves are extended to above 2 keV and 181 Ta impurity levels are discussed. (SDF)

Stochastic chaos in a Duffing oscillator and its control

International Nuclear Information System (INIS)

Wu Cunli; Lei Youming; Fang Tong

2006-01-01

Stochastic chaos discussed here means a kind of chaotic responses in a Duffing oscillator with bounded random parameters under harmonic excitations. A system with random parameters is usually called a stochastic system. The modifier 'stochastic' here implies dependent on some random parameter. As the system itself is stochastic, so is the response, even under harmonic excitations alone. In this paper stochastic chaos and its control are verified by the top Lyapunov exponent of the system. A non-feedback control strategy is adopted here by adding an adjustable noisy phase to the harmonic excitation, so that the control can be realized by adjusting the noise level. It is found that by this control strategy stochastic chaos can be tamed down to the small neighborhood of a periodic trajectory or an equilibrium state. In the analysis the stochastic Duffing oscillator is first transformed into an equivalent deterministic nonlinear system by the Gegenbauer polynomial approximation, so that the problem of controlling stochastic chaos can be reduced into the problem of controlling deterministic chaos in the equivalent system. Then the top Lyapunov exponent of the equivalent system is obtained by Wolf's method to examine the chaotic behavior of the response. Numerical simulations show that the random phase control strategy is an effective way to control stochastic chaos

Rolling bearing fault diagnosis based on time-delayed feedback monostable stochastic resonance and adaptive minimum entropy deconvolution

Science.gov (United States)

Li, Jimeng; Li, Ming; Zhang, Jinfeng

2017-08-01

Rolling bearings are the key components in the modern machinery, and tough operation environments often make them prone to failure. However, due to the influence of the transmission path and background noise, the useful feature information relevant to the bearing fault contained in the vibration signals is weak, which makes it difficult to identify the fault symptom of rolling bearings in time. Therefore, the paper proposes a novel weak signal detection method based on time-delayed feedback monostable stochastic resonance (TFMSR) system and adaptive minimum entropy deconvolution (MED) to realize the fault diagnosis of rolling bearings. The MED method is employed to preprocess the vibration signals, which can deconvolve the effect of transmission path and clarify the defect-induced impulses. And a modified power spectrum kurtosis (MPSK) index is constructed to realize the adaptive selection of filter length in the MED algorithm. By introducing the time-delayed feedback item in to an over-damped monostable system, the TFMSR method can effectively utilize the historical information of input signal to enhance the periodicity of SR output, which is beneficial to the detection of periodic signal. Furthermore, the influence of time delay and feedback intensity on the SR phenomenon is analyzed, and by selecting appropriate time delay, feedback intensity and re-scaling ratio with genetic algorithm, the SR can be produced to realize the resonance detection of weak signal. The combination of the adaptive MED (AMED) method and TFMSR method is conducive to extracting the feature information from strong background noise and realizing the fault diagnosis of rolling bearings. Finally, some experiments and engineering application are performed to evaluate the effectiveness of the proposed AMED-TFMSR method in comparison with a traditional bistable SR method.

Stochastic development regression using method of moments

DEFF Research Database (Denmark)

Kühnel, Line; Sommer, Stefan Horst

2017-01-01

This paper considers the estimation problem arising when inferring parameters in the stochastic development regression model for manifold valued non-linear data. Stochastic development regression captures the relation between manifold-valued response and Euclidean covariate variables using...... the stochastic development construction. It is thereby able to incorporate several covariate variables and random effects. The model is intrinsically defined using the connection of the manifold, and the use of stochastic development avoids linearizing the geometry. We propose to infer parameters using...... the Method of Moments procedure that matches known constraints on moments of the observations conditional on the latent variables. The performance of the model is investigated in a simulation example using data on finite dimensional landmark manifolds....

Stochastic fluctuation induced the competition between extinction and recurrence in a model of tumor growth

International Nuclear Information System (INIS)

Li, Dongxi; Xu, Wei; Sun, Chunyan; Wang, Liang

2012-01-01

We investigate the phenomenon that stochastic fluctuation induced the competition between tumor extinction and recurrence in the model of tumor growth derived from the catalytic Michaelis–Menten reaction. We analyze the probability transitions between the extinction state and the state of the stable tumor by the Mean First Extinction Time (MFET) and Mean First Return Time (MFRT). It is found that the positional fluctuations hinder the transition, but the environmental fluctuations, to a certain level, facilitate the tumor extinction. The observed behavior could be used as prior information for the treatment of cancer. -- Highlights: ► Stochastic fluctuation induced the competition between extinction and recurrence. ► The probability transitions are investigated. ► The positional fluctuations hinder the transition. ► The environmental fluctuations, to a certain level, facilitate the tumor extinction. ► The observed behavior can be used as prior information for the treatment of cancer.

Stochastic programming with integer recourse

NARCIS (Netherlands)

van der Vlerk, Maarten Hendrikus

1995-01-01

In this thesis we consider two-stage stochastic linear programming models with integer recourse. Such models are at the intersection of two different branches of mathematical programming. On the one hand some of the model parameters are random, which places the problem in the field of stochastic

Impact of the depth of the wells and multifractal analysis on stochastic resonance in a triple-well system

International Nuclear Information System (INIS)

Arathi, S; Rajasekar, S

2011-01-01

We analyze the stochastic resonance in a symmetric triple-well system with the depths of the wells being different. The system is subjected to a weak periodic force and Gaussian white noise with strength D. We show that the optimum value of noise intensity (D MAX ) is minimum, while the signal-to-noise ratio is maximum when the ratio (R) of the depths of the middle and side wells is 1. At D MAX , the particle enters the middle well twice during every period of the external periodic force. When the depths of the three wells are equal (R=1), the mean residence time (T MR ) in each well is T/4, where T is the period of the driving force. T MR varies with parameter R; however, periodicity in switching is observed at D MAX for any value of R. The generalized dimensions D q decrease with an increase in noise intensity D, reach a minimum at D=D MAX and then increase for all values of R. The α-f(α) spectrum is always of incomplete concave shape with f(α min )=0, while f(α max )≠0 at any value of D and, moreover, the maximum value of α is minimum at D=D MAX .

A Dynamical System Exhibits High Signal-to-noise Ratio Gain by Stochastic Resonance

Science.gov (United States)

Makra, Peter; Gingl, Zoltan

2003-05-01

On the basis of mixed-signal simulations, we demonstrate that signal-to-noise ratio (SNR) gains much greater than unity can be obtained in the double-well potential through stochastic resonance (SR) with a symmetric periodic pulse train as deterministic and Gaussian white noise as random excitation. We also show that significant SNR improvement is possible in this system even for a sub-threshold sinusoid input if, instead of the commonly used narrow-band SNR, we apply an equally simple but much more realistic wide-band SNR definition. Using the latter result as an argument, we draw attention to the fact that the choice of the measure to reflect signal quality is critical with regard to the extent of signal improvement observed, and urge reconsideration of the practice prevalent in SR studies that most often the narrow-band SNR is used to characterise SR. Finally, we pose some questions concerning the possibilities of applying SNR improvement in practical set-ups.

A Proposed Stochastic Finite Difference Approach Based on Homogenous Chaos Expansion

Directory of Open Access Journals (Sweden)

O. H. Galal

2013-01-01

Full Text Available This paper proposes a stochastic finite difference approach, based on homogenous chaos expansion (SFDHC. The said approach can handle time dependent nonlinear as well as linear systems with deterministic or stochastic initial and boundary conditions. In this approach, included stochastic parameters are modeled as second-order stochastic processes and are expanded using Karhunen-Loève expansion, while the response function is approximated using homogenous chaos expansion. Galerkin projection is used in converting the original stochastic partial differential equation (PDE into a set of coupled deterministic partial differential equations and then solved using finite difference method. Two well-known equations were used for efficiency validation of the method proposed. First one being the linear diffusion equation with stochastic parameter and the second is the nonlinear Burger's equation with stochastic parameter and stochastic initial and boundary conditions. In both of these examples, the probability distribution function of the response manifested close conformity to the results obtained from Monte Carlo simulation with optimized computational cost.

Acoustically induced transparency using Fano resonant periodic arrays

KAUST Repository

El-Amin, Mohamed

2015-10-22

A three-dimensional acoustic device, which supports Fano resonance and induced transparency in its response to an incident sound wave, is designed and fabricated. These effects are generated from the destructive interference of closely coupled one broad- and one narrow-band acoustic modes. The proposed design ensures excitation and interference of two spectrally close modes by locating a small pipe inside a wider and longer one. Indeed, numerical simulations and experiments demonstrate that this simple-to-fabricate structure can be used to generate Fano resonance as well as acoustically induced transparency with promising applications in sensing, cloaking, and imaging.

Acoustically induced transparency using Fano resonant periodic arrays

KAUST Repository

El-Amin, Mohamed; Elayouch, A.; Farhat, Mohamed; Addouche, M.; Khelif, A.; Bagci, Hakan

2015-01-01

A three-dimensional acoustic device, which supports Fano resonance and induced transparency in its response to an incident sound wave, is designed and fabricated. These effects are generated from the destructive interference of closely coupled one broad- and one narrow-band acoustic modes. The proposed design ensures excitation and interference of two spectrally close modes by locating a small pipe inside a wider and longer one. Indeed, numerical simulations and experiments demonstrate that this simple-to-fabricate structure can be used to generate Fano resonance as well as acoustically induced transparency with promising applications in sensing, cloaking, and imaging.

Relativistic effects in the intermolecular interaction-induced nuclear magnetic resonance parameters of xenon dimer

DEFF Research Database (Denmark)

Hanni, Matti; Lantto, Perttu; Ilias, Miroslav

2007-01-01

Relativistic effects on the 129Xe nuclear magnetic resonance shielding and 131Xe nuclear quadrupole coupling (NQC) tensors are examined in the weakly bound Xe2 system at different levels of theory including the relativistic four-component Dirac-Hartree-Fock (DHF) method. The intermolecular...... interaction-induced binary chemical shift d, the anisotropy of the shielding tensor ?s, and the NQC constant along the internuclear axis ?ll are calculated as a function of the internuclear distance. DHF shielding calculations are carried out using gauge-including atomic orbitals. For comparison, the full...... is obtained for d and ?s in Xe2. For these properties, the currently most complete theoretical description is obtained by a piecewise approximation where the uncorrelated relativistic DHF results obtained close to the basis-set limit are corrected, on the one hand, for NR correlation effects and, on the other...

Stochastic mass-reconstruction: a new technique to reconstruct resonance masses of heavy particles decaying into tau lepton pairs

Energy Technology Data Exchange (ETDEWEB)

Maruyama, Sho [Fermilab

2015-12-15

The invariant mass of tau lepton pairs turns out to be smaller than the resonant mass of their mother particle and the invariant mass distribution is stretched wider than the width of the resonant mass as significant fraction of tau lepton momenta are carried away by neutrinos escaping undetected at collider experiments. This paper describes a new approach to reconstruct resonant masses of heavy particles decaying to tau leptons at such experiments. A typical example is a Z or Higgs boson decaying to a tau pair. Although the new technique can be used for each tau lepton separately, I combine two tau leptons to improve mass resolution by requiring the two tau leptons are lined up in a transverse plane. The method is simple to implement and complementary to the collinear approximation technique that works well when tau leptons are not lined up in a transverse plane. The reconstructed mass can be used as another variable in analyses that already use a visible tau pair mass and missing transverse momentum as these variables are not explicitly used in the stochastic mass-reconstruction to select signal-like events.

Stochastic aspects of two-dimensional vibration diagnostics

International Nuclear Information System (INIS)

Pazsit, I.; Antonopoulos-Domis, M.; Gloeckler, O.

1985-01-01

The aim of this paper is to investigate the stochastic features of two-dimensional lateral damped oscillations of PWR core internals, that are induced by random force components. It is also investigated how these vibrating components, or the forces giving rise to the vibrations could be diagnosed through the analysis of displacement or neutron noise signals. The approach pursued here is to select a realisation of the random force components, then the equations of the motion are integrated and the time history of displacement components is obtained. From here various statistical descriptors of the motion, such as trajectory pattern, spectra and PDF functions, etc. can be calculated. It was investigated how these statistical descriptors depend on the characteristics of the driving force for both stationary and non-stationary cases. A conclusion of possible diagnostical relevance is that, under certain circumstances, the PDF functions could be an indicator of whether a particular peak in the corresponding power spectra belongs to a resonance in system transfer or rather a resonance in the external driving force. (author)

Stochastic aspects of two-dimensional vibration diagnostics

International Nuclear Information System (INIS)

Pazsit, I.; Antonopoulos-Domis, M.; Glockler, O.

1984-01-01

The aim of this paper is to investigate the stochastic features of two-dimensional lateral damped oscillations of PWR core internals that are induced by random force components. It is also investigated how these vibrating components, or the forces giving rise to the vibrations, could be diagnosed through the analysis of displacement or neutron noise signals. The approach pursued here is to select a realisation of the random force components, then the equations of the motion are integrated and the time history of displacement components is obtained. From here various statistical descriptors of the motion, such as trajectory pattern, spectra and PDF functions etc., can be calculated. It was investigated how these statistical descriptors depend on the characteristics of the driving force for both stationary and non-stationary cases. A conclusion of possible diagnostical relevance is that, under certain circumstances, the PDF functions could be an indicator of whether a particular peak in the corresponding power spectra belongs to a resonance in system transfer or rather a resonance in the external driving force

Stochastic aspects of two-dimensional vibration diagnostics

International Nuclear Information System (INIS)

Pazsit, I.; Gloeckler, O.

1984-01-01

The aim of this paper is to investigate the stochastic features of two-dimensional lateral damped oscillations of PWR core internals that are induced by random force components. It is also investigated how these vibrating components, or the forces giving rise to the vibrations, could be diagnosed through the analysis of displacement or neutron noise signals. The approach pursued here is to select a realisation of the random force components, then the equations of the motion ar integrated and the time history of displacement components is obtained. From here various statistical descriptors of the motion, such as trajectory pattern, spectra and PDF functions etc., can be calculated. It was investigated how these statistical descriptors depend on the characteristics of the driving force for both stationary and non-stationary cases. A conclusion of possible diagnostical relevance is that, under certain circumstances, the PDF functions could be an indicator of whether a particular peak in the corresponding power spectra belongs to a resonance in system transfer or rather a resonance in the external driving force. (author)

Measurements of the Z boson resonance parameters at SLC [SLAC Linear Collider

International Nuclear Information System (INIS)

Hearty, C.

1989-07-01

This paper presents the measurement by the Mark II experiment at the SLAC Linear Collider of the parameters of the Z boson resonance. The results are updated from those presented at the SLAC Summer Institute to include all data presented in the most recent Mark II publication, consisting of 19 nb -1 of data at ten different center-of-mass energies between 89.2 and 93.0 GeV. The resonance parameters are extracted by measuring the Z production cross section at a series of center-of-mass energies (scan points) near the Z peak, then fitting these data with the theoretical cross section. The four major aspects of the analysis are the determination at each scan point of the center-of-mass energy (E), the integrated luminosity, the number of Z decays and the expected cross section as a function of the resonance parameters, such as mass and width. I will discuss each of these steps in turn, after a brief description of the Mark II detector, then conclude with the results of the analysis. 7 refs., 9 figs., 3 tabs

Dynamics of stochastic systems

CERN Document Server

Klyatskin, Valery I

2005-01-01

Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''''oil slicks''''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere.Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields.The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of ...

Simulation Research of Magnetically-coupled Resonant Wireless Power Transfer System with Single Intermediate Coil Resonator Based on S Parameters Using ANSYS

Directory of Open Access Journals (Sweden)

Liu Cheng

2016-01-01

Full Text Available ANSYS can be a powerful tool to simulate the process of energy exchange in magnetically-coupled resonant wireless power transfer system. In this work, the MCR-WPT system with single intermediate coil resonator is simulated and researched based on scattering parameters using ANSYS Electromagnetics. The change rule of power transfer efficiency is reflected intuitively through the scattering parameters. A new method of calculating the coupling coefficient is proposed. A cascaded 2-port network model using scattering parameters is adopted to research the efficiency of transmission. By changing the relative position and the number of turns of the intermediate coil, we find some factors affecting the efficiency of transmission. Methods and principles of designing the MCR-WPT system with single intermediate coil resonator are obtained. And these methods have practical value with design and optimization of system efficiency.

Stochastic acceleration by a single wave in a magnetized plasma

International Nuclear Information System (INIS)

Smith, R.

1977-01-01

A particularly simple problem exhibiting stochasticity is the motion of a charged particle in a uniform magnetic field and a single wave. Detailed studies of this wave-particle interaction show the following features. An electrostatic wave propagating obliquely to the magnetic field causes stochastic motion if the wave amplitude exceeds a certain threshold. The overlap of cyclotron resonances then destroys a constant of the motion, allowing strong particle acceleration. A wave of large enough amplitude would thus suffer severe damping and lead to rapid heating of a particle distribution. The stochastic motion resembles a diffusion process even though the wave spectrum contains only a single wave. The motion of ions in a nonuniform magnetic field and a single electrostatic wave is treated in our study of a possible saturation mechanism of the dissipative trapped-ion instability in a tokamak. A theory involving the overlap of bounce resonances predicts the main features found in the numerical integration of the equations of motion. Ions in a layer near the trapped-circulating boundary move stochastically. This motion leads to nonlinear stabilization mechanisms which are described qualitatively

HOMOCLINIC TANGLE BIFURCATIONS AND EDGE STOCHASTICITY IN DIVERTED TOKAMAKS

International Nuclear Information System (INIS)

EVANS, T.E.; ROEDER, R.K.W.; CARTER, J.A.; RAPOPORT, B.I.

2003-01-01

OAK-B135 The boundary and pedestal region of a poloidally diverted tokamak is particularly susceptible to the onset of vacuum magnetic field stochasticity due to small non-axisymmetric resonant perturbations. Recent calculations of the separatrix topology in diverted tokamaks, when subjected to small magnetic perturbations, show the existence of complex invariant manifold structures known as homoclinic tangles. These structures appear above a relatively low perturbation threshold that depends on certain equilibrium shape parameters. Homoclinic tangles represent a splitting of the unperturbed separatrix into stable and unstable invariant manifolds associated with each X-point (hyperbolic point). The manifolds that make up homoclinic tangles set the boundaries that prescribe how stochastic field line trajectories are organized i.e., how field lines from the inner domain of the unperturbed separatrix mix and are transported to plasma facing surfaces such as divertor target plates and protruding baffle structures. Thus, the topology of these tangles determines which plasma facing components are most likely to interact with escaping magnetic field lines and the parallel heat and particle flux they carry

A low free-parameter stochastic model of daily Forbush decrease indices

Science.gov (United States)

Patra, Sankar Narayan; Bhattacharya, Gautam; Panja, Subhash Chandra; Ghosh, Koushik

2014-01-01

Forbush decrease is a rapid decrease in the observed galactic cosmic ray intensity pattern occurring after a coronal mass ejection. In the present paper we have analyzed the daily Forbush decrease indices from January, 1967 to December, 2003 generated in IZMIRAN, Russia. First the entire indices have been smoothened and next we have made an attempt to fit a suitable stochastic model for the present time series by means of a necessary number of process parameters. The study reveals that the present time series is governed by a stationary autoregressive process of order 2 with a trace of white noise. Under the consideration of the present model we have shown that chaos is not expected in the present time series which opens up the possibility of validation of its forecasting (both short-term and long-term) as well as its multi-periodic behavior.

Predicting Footbridge Response using Stochastic Load Models

DEFF Research Database (Denmark)

Pedersen, Lars; Frier, Christian

2013-01-01

Walking parameters such as step frequency, pedestrian mass, dynamic load factor, etc. are basically stochastic, although it is quite common to adapt deterministic models for these parameters. The present paper considers a stochastic approach to modeling the action of pedestrians, but when doing so...... decisions need to be made in terms of statistical distributions of walking parameters and in terms of the parameters describing the statistical distributions. The paper explores how sensitive computations of bridge response are to some of the decisions to be made in this respect. This is useful...

A method for generating subgroup parameters from resonance tables and the SPART code

International Nuclear Information System (INIS)

Devan, K.; Mohanakrishnan, P.

1995-01-01

A method for generating subgroup or band parameters from resonance tables is described. A computer code SPART was written using this method. This code generates the subgroup parameters for any number of bands within the specified broad groups at different temperatures by reading the required input data from the binary cross section library in the Cadarache format. The results obtained with SPART code for two bands were compared with that obtained from GROUPIE code and a good agreement was obtained. Results of the generation of subgroup parameters in four bands for sample case of 239 Pu from resonance tables of Cadarache Ver.2 library is also presented. 6 refs, 2 tabs

The appreciation of stochastic motion in particle accelerators

International Nuclear Information System (INIS)

Symon, Keith; Sessler, Andrew

2003-01-01

A description is given of the analytic and numerical work, performed from July 1955 through August 1956, so as to develop, and then study, the process of making intense proton beams, suitable for colliding beams. It is shown how this investigation led, in a most natural way, to the realization that stochasticity can arise in a simple Hamiltonian system. Furthermore, the criterion for the onset of stochasticity was understood, and carefully studied, in two different situations. The first situation was the proposed (and subsequently used) ''stacking process'' for developing an intense beam, where stochasticity occurs as additional particles are added to the intense circulating beam. The second situation occurs when one seeks to develop ''stochastic accelerators'' in which particles are accelerated (continuously) by a collection of radio frequency systems. It was in the last connection that the well-known criterion for stochasticity, resonance overlap, was obtained

Parameter Identification for Nonlinear Circuit Models of Power BAW Resonator

Directory of Open Access Journals (Sweden)

CONSTANTINESCU, F.

2011-02-01

Full Text Available The large signal operation of the bulk acoustic wave (BAW resonators is characterized by the amplitude-frequency effect and the intermodulation effect. The measurement of these effects, together with that of the small signal frequency characteristic, are used in this paper for the parameter identification of the nonlinear circuit models developed previously by authors. As the resonator has been connected to the measurement bench by wire bonding, the parasitic elements of this connection have been taken into account, being estimated solving some electrical and magnetic field problems.

Stochastic synaptic plasticity with memristor crossbar arrays

KAUST Repository

Naous, Rawan

2016-11-01

Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

Stochastic synaptic plasticity with memristor crossbar arrays

KAUST Repository

Naous, Rawan; Al-Shedivat, Maruan; Neftci, Emre; Cauwenberghs, Gert; Salama, Khaled N.

2016-01-01

Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

Baryon resonances in pion- and photon-induced hadronic reactions

International Nuclear Information System (INIS)

Roenchen, Deborah

2014-01-01

The aim of the present work is the analysis of the baryon spectrum in the medium-energy regime. At those energies, a perturbative treatment of Quantum Chromodynamics, that is feasible in the high-energy regime, is not possible. Chiral perturbation theory, the low-energy effective theory of the strong interaction, is limited to the lowest excited states and does not allow to analyze the complete resonance region. For the latter purpose, dynamical coupled-channel approaches provide an especially suited framework. In the present study, we apply the Juelich model, a dynamical coupled-channel model developed over the years, to analyze pion- and photon-induced hadronic reactions in a combined approach. In the Juelich model, the interaction of the mesons and baryons is built of t- and u-channel exchange diagrams based on an effective Lagrangian. Genuine resonances are included as s-channel states. The scattering potential is unitarized in a Lippmann-Schwinger-type equation. Analyticity is preserved, which is a prerequisite for a reliable extraction of resonance parameters in terms of pole positions and residues in the complex energy plane. Upon giving an introduction to the subject in Chap. 1 and showing selected results in Chap. 2, we will describe the simultaneous analysis of elastic πN scattering and the reactions π - p → ηn, K 0 Λ, K + Σ - , K 0 Σ 0 and π + p→K + Σ + within the Juelich framework in Chap. 3. The free parameters of the model are adjusted to the GWU/SAID analysis of elastic πN scattering and, in case of the inelastic reactions, to experimental data. Partial waves up to J=9/2 are included and we consider the world data set from threshold up to E∝2.3 GeV. We show our fit results compared to differential and total cross sections, to polarizations and to measurements of the spin-rotation parameter. Finally, we present the results of a pole search in the complex energy plane of the scattering amplitude and discuss the extracted resonance

Adaptive Multiscale Noise Control Enhanced Stochastic Resonance Method Based on Modified EEMD with Its Application in Bearing Fault Diagnosis

Directory of Open Access Journals (Sweden)

Jimeng Li

2016-01-01

Full Text Available The structure of mechanical equipment becomes increasingly complex, and tough environments under which it works often make bearings and gears subject to failure. However, effective extraction of useful feature information submerged in strong noise that is indicative of structural defects has remained a major challenge. Therefore, an adaptive multiscale noise control enhanced stochastic resonance (SR method based on modified ensemble empirical mode decomposition (EEMD for mechanical fault diagnosis is proposed in the paper. According to the oscillation characteristics of signal itself, the algorithm of modified EEMD can adaptively decompose the fault signals into different scales and it reduces the decomposition levels to improve calculation efficiency of the proposed method. Through filter processing with the constructed filters, the orthogonality of adjacent intrinsic mode functions (IMFs can be improved, which is conducive to enhancing the extraction of weak features from strong noise. The constructed signal obtained by using IMFs is inputted into the SR system, and the noise control parameter of different scales is optimized and selected with the help of the genetic algorithm, thus achieving the enhancement extraction of weak features. Finally, simulation experiments and engineering application of bearing fault diagnosis demonstrate the effectiveness and feasibility of the proposed method.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas

2017-12-27

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas; Richtarik, Peter

2017-01-01

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Testing the new stochastic neutronic code ANET in simulating safety important parameters

International Nuclear Information System (INIS)

Xenofontos, T.; Delipei, G.-K.; Savva, P.; Varvayanni, M.; Maillard, J.; Silva, J.; Catsaros, N.

2017-01-01

Highlights: • ANET is a new neutronics stochastic code. • Criticality calculations in both subcritical and critical nuclear systems of conventional design were conducted. • Simulations of thermal, lower epithermal and fast neutron fluence rates were performed. • Axial fission rate distributions in standard and MOX fuel pins were computed. - Abstract: ANET (Advanced Neutronics with Evolution and Thermal hydraulic feedback) is an under development Monte Carlo code for simulating both GEN II/III reactors as well as innovative nuclear reactor designs, based on the high energy physics code GEANT3.21 of CERN. ANET is built through continuous GEANT3.21 applicability amplifications, comprising the simulation of particles’ transport and interaction in low energy along with the accessibility of user-provided libraries and tracking algorithms for energies below 20 MeV, as well as the simulation of elastic and inelastic collision, capture and fission. Successive testing applications performed throughout the ANET development have been utilized to verify the new code capabilities. In this context the ANET reliability in simulating certain reactor parameters important to safety is here examined. More specifically the reactor criticality as well as the neutron fluence and fission rates are benchmarked and validated. The Portuguese Research Reactor (RPI) after its conversion to low enrichment in U-235 and the OECD/NEA VENUS-2 MOX international benchmark were considered appropriate for the present study, the former providing criticality and neutron flux data and the latter reaction rates. Concerning criticality benchmarking, the subcritical, Training Nuclear Reactor of the Aristotle University of Thessaloniki (TNR-AUTh) was also analyzed. The obtained results are compared with experimental data from the critical infrastructures and with computations performed by two different, well established stochastic neutronics codes, i.e. TRIPOLI-4.8 and MCNP5. Satisfactory agreement

Coherence resonance and stochastic resonance in directionally coupled rings

Science.gov (United States)

Werner, Johannes Peter; Benner, Hartmut; Florio, Brendan James; Stemler, Thomas

2011-11-01

In coupled systems, symmetry plays an important role for the collective dynamics. We investigate the dynamical response to noise with and without weak periodic modulation for two classes of ring systems. Each ring system consists of unidirectionally coupled bistable elements but in one class, the number of elements is even while in the other class the number is odd. Consequently, the rings without forcing show at a certain coupling strength, either ordering (similar to anti-ferromagnetic chains) or auto-oscillations. Analysing the bifurcations and fixed points of the two ring classes enables us to explain the dynamical response measured to noise and weak modulation. Moreover, by analysing a simplified model, we demonstrate that the response is universal for systems having a directional component in their stochastic dynamics in phase space around the origin.

Memory-induced resonancelike suppression of spike generation in a resonate-and-fire neuron model

Science.gov (United States)

Mankin, Romi; Paekivi, Sander

2018-01-01

The behavior of a stochastic resonate-and-fire neuron model based on a reduction of a fractional noise-driven generalized Langevin equation (GLE) with a power-law memory kernel is considered. The effect of temporally correlated random activity of synaptic inputs, which arise from other neurons forming local and distant networks, is modeled as an additive fractional Gaussian noise in the GLE. Using a first-passage-time formulation, in certain system parameter domains exact expressions for the output interspike interval (ISI) density and for the survival probability (the probability that a spike is not generated) are derived and their dependence on input parameters, especially on the memory exponent, is analyzed. In the case of external white noise, it is shown that at intermediate values of the memory exponent the survival probability is significantly enhanced in comparison with the cases of strong and weak memory, which causes a resonancelike suppression of the probability of spike generation as a function of the memory exponent. Moreover, an examination of the dependence of multimodality in the ISI distribution on input parameters shows that there exists a critical memory exponent αc≈0.402 , which marks a dynamical transition in the behavior of the system. That phenomenon is illustrated by a phase diagram describing the emergence of three qualitatively different structures of the ISI distribution. Similarities and differences between the behavior of the model at internal and external noises are also discussed.

Stochasticity in the Josephson map

International Nuclear Information System (INIS)

Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.

1996-04-01

The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)

Stochastic estimation approach for the evaluation of thermal-hydraulic parameters in pressurized water reactors

International Nuclear Information System (INIS)

Shieh, D.J.; Upadhyaya, M.G.

1986-01-01

A method based on the extended Kalman filter is developed for the estimation of the core coolant mass flow rate in pressurized water reactors. The need for flow calibration can be avoided by a direct estimation of this parameter. A reduced-order neutronic and thermal-hydraulic model is developed for the Loss-of-Fluid Test (LOFT) reactor. The neutron detector and core-exit coolant temperature signals from the LOFT reactor are used as measurements in the parameter estimation algorithm. The estimation sensitivity to model uncertainties was evaluated using the ambiguity function analysis. This also provides a lower bound on the measurement sample size necessary to achieve a certain estimation accuracy. A sequential technique was developed to minimize the computational effort needed to discretize the continuous time equations, and thus achieve faster convergence to the true parameter value. The performance of the stochastic approximation method was first evaluated using simulated random data, and then applied to the estimation of coolant flow rate using the operational data from the LOFT reactor at 100 and 65% flow rate conditions

Quantum stochastic calculus associated with quadratic quantum noises

International Nuclear Information System (INIS)

Ji, Un Cig; Sinha, Kalyan B.

2016-01-01

We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus

Quantum stochastic calculus associated with quadratic quantum noises

Energy Technology Data Exchange (ETDEWEB)

Ji, Un Cig, E-mail: uncigji@chungbuk.ac.kr [Department of Mathematics, Research Institute of Mathematical Finance, Chungbuk National University, Cheongju, Chungbuk 28644 (Korea, Republic of); Sinha, Kalyan B., E-mail: kbs-jaya@yahoo.co.in [Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bangalore-64, India and Department of Mathematics, Indian Institute of Science, Bangalore-12 (India)

2016-02-15

We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus.

Numerical analysis of resonances induced by s wave neutrons in transmission time-of-flight experiments with a computer IBM 7094 II

International Nuclear Information System (INIS)

Corge, Ch.

1969-01-01

Numerical analysis of transmission resonances induced by s wave neutrons in time-of-flight experiments can be achieved in a fairly automatic way on an IBM 7094/II computer. The involved computations are carried out following a four step scheme: 1 - experimental raw data are processed to obtain the resonant transmissions, 2 - values of experimental quantities for each resonance are derived from the above transmissions, 3 - resonance parameters are determined using a least square method to solve the over determined system obtained by equalling theoretical functions to the correspondent experimental values. Four analysis methods are gathered in the same code, 4 - graphical control of the results is performed. (author) [fr

Complexity, rate of energy exchanges and stochasticity

International Nuclear Information System (INIS)

Casartelli, M.; Sello, S.

1987-01-01

The complexity of trajectories in the phase of anharmonic crystal (mostly a Lennard-Jones chain) is analysed by the variance of microcanonical density and by new parameters P and chi defined, respectively, as the mean value of the time averages and the relative variance of the absolute exchange rate of energies among the normal modes. Evidence is given to the trapping action of residual invariant surfaces in low stochastic regime of motion. The parameter chi, moreover, proves efficient in exploring the border of stochasticity. A simple power law for P vs. the specific energy is obtained and proved to be independent of stochasticity and of the type of anharmonic potential

Optimum Parameters of a Tuned Liquid Column Damper in a Wind Turbine Subject to Stochastic Load

Science.gov (United States)

Alkmim, M. H.; de Morais, M. V. G.; Fabro, A. T.

2017-12-01

Parameter optimization for tuned liquid column dampers (TLCD), a class of passive structural control, have been previously proposed in the literature for reducing vibration in wind turbines, and several other applications. However, most of the available work consider the wind excitation as either a deterministic harmonic load or random load with white noise spectra. In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of undamped primary system under white noise excitation by comparing with result from the literature. Finally, it is shown that different wind profiles can significantly affect the optimum TLCD parameters.

Automated Flight Routing Using Stochastic Dynamic Programming

Science.gov (United States)

Ng, Hok K.; Morando, Alex; Grabbe, Shon

2010-01-01

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

Experimental estimations of the kinetics parameters of the IBR-2M reactor by stochastic noises

International Nuclear Information System (INIS)

Pepelyshev, Yu.N.; Tajybov, L.A.; Garibov, A.A.; Mekhtieva, R.N.

2012-01-01

Experimental investigations of stochastic fluctuations of pulse energy of the IBR-2M reactor have been carried out which allowed us to obtain some of the parameters of the reactor kinetics. At different levels of average power a sequence of values of pulse energy was recorded with the calculation of the distribution parameters. An ionization chamber with boron installed near the active zone was used as a neutron detector. The research results allowed us to estimate the average lifetime of prompt neutrons τ = (6.53±0.2)·10 -8 s, absolute power of the reactor and intensity of the source of spontaneous neutrons S sp ≤(6.72±0.12)·10 6 s -1 . It was shown that the experimental results are close to the calculated ones

Planning under uncertainty solving large-scale stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G. [Stanford Univ., CA (United States). Dept. of Operations Research]|[Technische Univ., Vienna (Austria). Inst. fuer Energiewirtschaft

1992-12-01

For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.

Stochastic resonances in a distributed genetic broadcasting system: the NFκB/IκB paradigm.

Science.gov (United States)

Wang, Zhipeng; Potoyan, Davit A; Wolynes, Peter G

2018-01-01

Gene regulatory networks must relay information from extracellular signals to downstream genes in an efficient, timely and coherent manner. Many complex functional tasks such as the immune response require system-wide broadcasting of information not to one but to many genes carrying out distinct functions whose dynamical binding and unbinding characteristics are widely distributed. In such broadcasting networks, the intended target sites are also often dwarfed in number by the even more numerous non-functional binding sites. Taking the genetic regulatory network of NF κ B as an exemplary system we explore the impact of having numerous distributed sites on the stochastic dynamics of oscillatory broadcasting genetic networks pointing out how resonances in binding cycles control the network's specificity and performance. We also show that active kinetic regulation of binding and unbinding through molecular stripping of DNA bound transcription factors can lead to a higher coherence of gene-co-expression and synchronous clearance. © 2018 The Author(s).

Stochastic deformation of a thermodynamic symplectic structure

OpenAIRE

Kazinski, P. O.

2008-01-01

A stochastic deformation of a thermodynamic symplectic structure is studied. The stochastic deformation procedure is analogous to the deformation of an algebra of observables like deformation quantization, but for an imaginary deformation parameter (the Planck constant). Gauge symmetries of thermodynamics and corresponding stochastic mechanics, which describes fluctuations of a thermodynamic system, are revealed and gauge fields are introduced. A physical interpretation to the gauge transform...

Collisionally induced stochastic dynamics of fast ions in solids

International Nuclear Information System (INIS)

Burgdoerfer, J.

1989-01-01

Recent developments in the theory of excited state formation in collisions of fast highly charged ions with solids are reviewed. We discuss a classical transport theory employing Monte-Carlo sampling of solutions of a microscopic Langevin equation. Dynamical screening by the dielectric medium as well as multiple collisions are incorporated through the drift and stochastic forces in the Langevin equation. The close relationship between the extrinsically stochastic dynamics described by the Langevin and the intrinsic stochasticity in chaotic nonlinear dynamical systems is stressed. Comparison with experimental data and possible modification by quantum corrections are discussed. 49 refs., 11 figs

Manipulation of resonant tunneling by substrate-induced inhomogeneous energy band gaps in graphene with square superlattice potentials

International Nuclear Information System (INIS)

Li, Guanqiang; Chen, Guangde; Peng, Ping; Cao, Zhenzhou; Ye, Honggang

2013-01-01

We investigate the resonant transmission of Dirac electrons through inhomogeneous band gap graphene with square superlattice potentials by transfer matrix method. The effects of the incident angle of the electrons, Fermi energy and substrate-induced Dirac gaps on the transmission are considered. It is found that the Dirac gap of graphene adds another degree of freedom with respect to the incident angle, the Fermi energy and the parameters of periodic superlattice potentials (i.e., the number, width and height of the barriers) for the transmission. In particular, the inhomogeneous Dirac gap induced by staggered substrates can be used to manipulate the transmission. The properties of the conductance and Fano factor at the resonant peaks are found to be affected by the gaps significantly. The results may be helpful for the practical application of graphene-based electronic devices

To what extent are stochastic the arithmetical progressions of the fractional parts?

International Nuclear Information System (INIS)

Arnold, V.

2008-01-01

For the residues of the division of the n members of an arithmetical progression by a real number N is proved the tending to 0 of the Kolmogorov's stochasticity parameter λ n , when n tends to infinity, providing that the progression step is commensurable with N. On the contrary, when the step is incommensurable with N, the paper describes some examples, where the stochasticity parameter λ n does not tend to zero, and even attains (infrequently) some arbitrary large values. Both the too small and the too large values of the stochasticity parameter show the small probability of the randomness of the sequence, for which they have been counted. Thus, the long arithmetical progressions' stochasticity degree is much smaller than that of the geometrical progressions (which provide temperate values of the stochasticity parameter, similarly to its value for the genuinely random sequences). (author)

Investment timing under hybrid stochastic and local volatility

International Nuclear Information System (INIS)

Kim, Jeong-Hoon; Lee, Min-Ku; Sohn, So Young

2014-01-01

Highlights: • The effects of hybrid stochastic volatility on real option prices are studied. • The stochastic volatility consists of a fast mean-reverting component and a CEV type one. • A fast mean-reverting factor lowers real option prices and investment thresholds. • The increase of elasticity raises real option prices and investment thresholds. • The effects of the addition of a slowly varying factor depend upon the project value. - Abstract: We consider an investment timing problem under a real option model where the instantaneous volatility of the project value is given by a combination of a hidden stochastic process and the project value itself. The stochastic volatility part is given by a function of a fast mean-reverting process as well as a slowly varying process and the local volatility part is a power (the elasticity parameter) of the project value itself. The elasticity parameter controls directly the correlation between the project value and the volatility. Knowing that the project value represents the market price of a real asset in many applications and the value of the elasticity parameter depends on the asset, the elasticity parameter should be treated with caution for investment decision problems. Based on the hybrid structure of volatility, we investigate the simultaneous impact of the elasticity and the stochastic volatility on the real option value as well as the investment threshold

Stochastic systems with cross-correlated Gaussian white noises

International Nuclear Information System (INIS)

Wang Cheng-Yu; Song Yu-Min; Zhou Peng; Yang Hai; Gao Yun

2010-01-01

This paper theoretically investigates three stochastic systems with cross-correlation Gaussian white noises. Both steady state properties of the stochastic nonlinear systems and the nonequilibrium transitions induced by the cross-correlated noises are studied. The stationary solutions of the Fokker—Planck equation for three specific examples are analysed. It is shown explicitly that the cross-correlation of white noises can induce nonequilibrium transitions

Wpływ rezonansu stochastycznego na równowagę dziecka z Mózgowym Porażeniem Dziecięcym = Influence of stochastic resonance on body balance of children with Cerebral Palsy

Directory of Open Access Journals (Sweden)

Grzegorz Srokowski

2015-12-01

• Dzięki zastosowanej terapii polepszył się wynik końcowy w teście równowagi Tinetti, co oznacza zmniejszenie ryzyka upadku u dzieci z MPD.   Słowa klucze: fizjoterapia MPD, rezonans stochastyczny, chód, równowaga.     Abstract Introduction: Cerebral Palsy (CP is an disease with different nonprogressive disorders of Central Nervous System (CNS. They manifest themselves through impairment of motor function and posture. As a result a child by the inability to control in this activities and lack of creation of appropriate postural responses turns them into defensive reactions. It was assumed, that therapy by providing the body with destabilizing stimuli by SRT - Zeptoring have positive impact on equivalent reactions and coordination during walking. The aim of the study was to examine and evaluate the effectiveness of the therapy on the SRT - Zeptoring device called Stochastic Resonance in a group of school children with diagnosed CP. Methods: The study was conducted at the Rehabilitation Center "Neuron" in Małe Gacno during the stationary rehabilitation. The study has covered 15 people, were children and young people with different types of MPD could move alone or with an additional orthopedic. The study included different functional tests, equivalent and an assessment of body postural control. 10 therapies were carried on Stochastic Resonance in accordance with the rules of conduct training on the machine. Results of the study: The detailed results of the study are presented in tables and illustrated on the graphs Conclusions: • Therapy using the stochastic resonance positively affects body posture control. The result is improvement of balance function and gait control in children with CP. • Thanks to the therapy patients has improved the end result of Tinetti balance test, which means a reduction in the risk of falling in children with CP.   Key words: physiotherapy CP, stochastic resonance, gait, balance.

A benchmark test of computer codes for calculating average resonance parameters

International Nuclear Information System (INIS)

Ribon, P.; Thompson, A.

1983-01-01

A set of resonance parameters has been generated from known, but secret, average values; the parameters have then been adjusted to mimic experimental data by including the effects of Doppler broadening, resolution broadening and statistical fluctuations. Average parameters calculated from the dataset by various computer codes are compared with each other, and also with the true values. The benchmark test is fully described in the report NEANDC160-U (NEA Data Bank Newsletter No. 27 July 1982); the present paper is a summary of this document. (Auth.)

Frequency adaptation in controlled stochastic resonance utilizing delayed feedback method: two-pole approximation for response function.

Science.gov (United States)

Tutu, Hiroki

2011-06-01

Stochastic resonance (SR) enhanced by time-delayed feedback control is studied. The system in the absence of control is described by a Langevin equation for a bistable system, and possesses a usual SR response. The control with the feedback loop, the delay time of which equals to one-half of the period (2π/Ω) of the input signal, gives rise to a noise-induced oscillatory switching cycle between two states in the output time series, while its average frequency is just smaller than Ω in a small noise regime. As the noise intensity D approaches an appropriate level, the noise constructively works to adapt the frequency of the switching cycle to Ω, and this changes the dynamics into a state wherein the phase of the output signal is entrained to that of the input signal from its phase slipped state. The behavior is characterized by power loss of the external signal or response function. This paper deals with the response function based on a dichotomic model. A method of delay-coordinate series expansion, which reduces a non-Markovian transition probability flux to a series of memory fluxes on a discrete delay-coordinate system, is proposed. Its primitive implementation suggests that the method can be a potential tool for a systematic analysis of SR phenomenon with delayed feedback loop. We show that a D-dependent behavior of poles of a finite Laplace transform of the response function qualitatively characterizes the structure of the power loss, and we also show analytical results for the correlation function and the power spectral density.

Neutron Transmission and Capture Measurements and Resonance Parameter Analysis of Neodymium from 1eV to 500 eV

International Nuclear Information System (INIS)

DP Barry; MJ Trbovich; Y Danon; RC Block; RE Slovacek

2005-01-01

Neodymium is a 235 U fission product and is important for reactor neutronic calculations. The aim of the present work is to improve upon the existing neutron cross section data of neodymium. Neutron capture and transmission measurements were performed by the time-off-light technique at the Rensselaer Polytechnic Institute LINAC laboratory using metallic neodymium samples. The capture measurements were made at the 25-m flight station with a 16-segment NaI multiplicity detector, and the transmission measurements were performed at 15-m and 25-m flight stations, respectively, with 6 Li glass scintillation detectors. After the data were collected and reduced, resonance parameters were determined by combined fitting of the transmission and capture data with the multilevel R-matrix Bayesian code SAMMY. The resonance parameters for all naturally occurring neodymium isotopes were deduced within the energy range of 1 eV to 500 eV. The resulting resonance parameters were used to calculate the capture resonance integrals from this energy. The RPI parameters gave a resonance integral value of 32 ± 1 barns that is approximately 7% lower than that obtained with the ENDF-B/VI parameters. The current measurements significantly reduce the uncertainties on the resonance parameters when compared with previously published parameters

Resonance analysis and evaluation of the 235U neutron induced cross sections

International Nuclear Information System (INIS)

Leal, L.C.

1990-06-01

Neutron cross sections of fissile nuclei are of considerable interest for the understanding of parameters such as resonance absorption, resonance escape probability, resonance self-shielding,and the dependence of the reactivity on temperature. In the present study, new techniques for the evaluation of the 235 U neutron cross sections are described. The Reich-Moore formalism of the Bayesian computer code SAMMY was used to perform consistent R-matrix multilevel analyses of the selected neutron cross-section data. The Δ 3 -statistics of Dyson and Mehta, along with high-resolution data and the spin-separated fission cross-section data, have provided the possibility of developing a new methodology for the analysis and evaluation of neutron-nucleus cross sections. The results of the analysis consists of a set of resonance parameters which describe the 235 U neutron cross sections up to 500 eV. The set of resonance parameters obtained through a R-matrix analysis are expected to satisfy statistical properties which lead to information on the nuclear structure. The resonance parameters were tested and showed good agreement with the theory. It is expected that the parametrization of the 235 U neutron cross sections obtained in this dissertation represents the current state of art in data as well as in theory and, therefore, can be of direct use in reactor calculations. 44 refs., 21 figs., 8 tabs

Kalman filter parameter estimation for a nonlinear diffusion model of epithelial cell migration using stochastic collocation and the Karhunen-Loeve expansion.

Science.gov (United States)

Barber, Jared; Tanase, Roxana; Yotov, Ivan

2016-06-01

Several Kalman filter algorithms are presented for data assimilation and parameter estimation for a nonlinear diffusion model of epithelial cell migration. These include the ensemble Kalman filter with Monte Carlo sampling and a stochastic collocation (SC) Kalman filter with structured sampling. Further, two types of noise are considered -uncorrelated noise resulting in one stochastic dimension for each element of the spatial grid and correlated noise parameterized by the Karhunen-Loeve (KL) expansion resulting in one stochastic dimension for each KL term. The efficiency and accuracy of the four methods are investigated for two cases with synthetic data with and without noise, as well as data from a laboratory experiment. While it is observed that all algorithms perform reasonably well in matching the target solution and estimating the diffusion coefficient and the growth rate, it is illustrated that the algorithms that employ SC and KL expansion are computationally more efficient, as they require fewer ensemble members for comparable accuracy. In the case of SC methods, this is due to improved approximation in stochastic space compared to Monte Carlo sampling. In the case of KL methods, the parameterization of the noise results in a stochastic space of smaller dimension. The most efficient method is the one combining SC and KL expansion. Copyright © 2016 Elsevier Inc. All rights reserved.

PC analysis of stochastic differential equations driven by Wiener noise

KAUST Repository

Le Maitre, Olivier

2015-03-01

A polynomial chaos (PC) analysis with stochastic expansion coefficients is proposed for stochastic differential equations driven by additive or multiplicative Wiener noise. It is shown that for this setting, a Galerkin formalism naturally leads to the definition of a hierarchy of stochastic differential equations governing the evolution of the PC modes. Under the mild assumption that the Wiener and uncertain parameters can be treated as independent random variables, it is also shown that the Galerkin formalism naturally separates parametric uncertainty and stochastic forcing dependences. This enables us to perform an orthogonal decomposition of the process variance, and consequently identify contributions arising from the uncertainty in parameters, the stochastic forcing, and a coupled term. Insight gained from this decomposition is illustrated in light of implementation to simplified linear and non-linear problems; the case of a stochastic bifurcation is also considered.

Orbital resonances around black holes.

Science.gov (United States)

Brink, Jeandrew; Geyer, Marisa; Hinderer, Tanja

2015-02-27

We compute the length and time scales associated with resonant orbits around Kerr black holes for all orbital and spin parameters. Resonance-induced effects are potentially observable when the Event Horizon Telescope resolves the inner structure of Sgr A*, when space-based gravitational wave detectors record phase shifts in the waveform during the resonant passage of a compact object spiraling into the black hole, or in the frequencies of quasiperiodic oscillations for accreting black holes. The onset of geodesic chaos for non-Kerr spacetimes should occur at the resonance locations quantified here.

Stochastic resonance in a bistable system subject to multi-time-delayed feedback and aperiodic signal

International Nuclear Information System (INIS)

Li Jianlong; Zeng Lingzao

2010-01-01

We discuss in detail the effects of the multi-time-delayed feedback driven by an aperiodic signal on the output of a stochastic resonance (SR) system. The effective potential function and dynamical probability density function (PDF) are derived. To measure the performance of the SR system in the presence of a binary random signal, the bit error rate (BER) defined by the dynamical PDF is employed, as is commonly used in digital communications. We find that the delay time, strength of the feedback, and number of time-delayed terms can change the effective potential function and the effective amplitude of the signal, and then affect the BER of the SR system. The numerical simulations strongly support the theoretical results. The goal of this investigation is to explore the effects of the multi-time-delayed feedback on SR and give a guidance to nonlinear systems in the application of information processing.

Numerical solution of second-order stochastic differential equations with Gaussian random parameters

Directory of Open Access Journals (Sweden)

Rahman Farnoosh

2014-07-01

Full Text Available In this paper, we present the numerical solution of ordinary differential equations (or SDEs, from each orderespecially second-order with time-varying and Gaussian random coefficients. We indicate a complete analysisfor second-order equations in specially case of scalar linear second-order equations (damped harmonicoscillators with additive or multiplicative noises. Making stochastic differential equations system from thisequation, it could be approximated or solved numerically by different numerical methods. In the case oflinear stochastic differential equations system by Computing fundamental matrix of this system, it could becalculated based on the exact solution of this system. Finally, this stochastic equation is solved by numericallymethod like E.M. and Milstein. Also its Asymptotic stability and statistical concepts like expectationand variance of solutions are discussed.

American option pricing with stochastic volatility processes

Directory of Open Access Journals (Sweden)

Ping LI

2017-12-01

Full Text Available In order to solve the problem of option pricing more perfectly, the option pricing problem with Heston stochastic volatility model is considered. The optimal implementation boundary of American option and the conditions for its early execution are analyzed and discussed. In view of the fact that there is no analytical American option pricing formula, through the space discretization parameters, the stochastic partial differential equation satisfied by American options with Heston stochastic volatility is transformed into the corresponding differential equations, and then using high order compact finite difference method, numerical solutions are obtained for the option price. The numerical experiments are carried out to verify the theoretical results and simulation. The two kinds of optimal exercise boundaries under the conditions of the constant volatility and the stochastic volatility are compared, and the results show that the optimal exercise boundary also has stochastic volatility. Under the setting of parameters, the behavior and the nature of volatility are analyzed, the volatility curve is simulated, the calculation results of high order compact difference method are compared, and the numerical option solution is obtained, so that the method is verified. The research result provides reference for solving the problems of option pricing under stochastic volatility such as multiple underlying asset option pricing and barrier option pricing.

Evaluation of covariances for resolved resonance parameters of 235U, 238U, and 239Pu in JENDL-3.2

International Nuclear Information System (INIS)

Kawano, Toshihiko; Shibata, Keiichi

2003-02-01

Evaluation of covariances for resolved resonance parameters of 235 U, 238 U, and 239 Pu was carried out. Although a large number of resolved resonances are observed for major actinides, uncertainties in averaged cross sections are more important than those in resonance parameters in reactor calculations. We developed a simple method which derives a covariance matrix for the resolved resonance parameters from uncertainties in the averaged cross sections. The method was adopted to evaluate the covariance data for some important actinides, and the results were compiled in the JENDL-3.2 covariance file. (author)

Estimation of an Optimal Stimulus Amplitude for Using Vestibular Stochastic Stimulation to Improve Balance Function

Science.gov (United States)

Goel, R.; Kofman, I.; DeDios, Y. E.; Jeevarajan, J.; Stepanyan, V.; Nair, M.; Congdon, S.; Fregia, M.; Peters, B.; Cohen, H.;

Neutron total cross-sections and resonance parameters of Mo and Ta

Indian Academy of Sciences (India)

Linear accelerator; total cross-sections; resonance parameters; SAMMY code. ... Centre for Atomic Research, Kalpakkam 603 102, India; Pohang Accelerator Laboratory, Pohang University of Science and Technology, Pohang 790-784, Korea; Department of Physics, Kyungpook National University, Daegu 702-701, Korea ...

Divergence of relative difference in Gaussian distribution function and stochastic resonance in a bistable system with frictionless state transition

Science.gov (United States)

Kasai, Seiya; Ichiki, Akihisa; Tadokoro, Yukihiro

2018-03-01

A bistable system efficiently detects a weak signal by adding noise, which is referred to as stochastic resonance. A previous theory deals with friction in state transition; however, this hypothesis is inadequate when friction force is negligible such as in nano- and molecular-scale systems. We show that, when the transition occurs without friction, the sensitivity of the bistable system to a Gaussian-noise-imposed weak signal becomes significantly high. The sensitivity is determined by the relative difference in noise distribution function. We find that the relative difference in Gaussian distribution function diverges in its tail edge, resulting in a high sensitivity in the present system.

Importance of resonance parameters of fertile nuclei and of 239Pu isotope for fast power reactors

International Nuclear Information System (INIS)

Barre, J.Y.; Khairallah, A.

1975-01-01

The importance of resonance parameters of fertile nuclei and of 239 Pu isotope for fast power reactors will be restricted, in this presentation, to mixed oxide-uranium-plutonium fuelled sodium-cooled and uranium-oxide-sodium reflected fast reactors. The power range lies between 200 and 2000 MWe. Among the topics of this specialist meeting, the isotopes to be considered are, primarly 239 Pu then 238 U and 240 Pu. Resonance parameters are mainly used in fast power reactor calculations through the well-known concept of self shielding factors. After a short description of the determination and the use of these self-shielding factors, their sensitivities to resonance parameters are characterized from some specific examples: those sensitivities are small. Then, the main design parameters sensitive to the amplitude of self-shielding factors are considered: critical enrichment, global breeding gain. The relative importance of isotope, reaction rate and energy range are mentionned. In a third part, the Doppler effect, sensitive to the temperature variation of self-shielding factors, is considered in the same way. Finally, it is concluded that the present knowledge of resonance parameters for 238 U, 239 Pu and 240 Pu is sufficient for fast power reactors from a designer point of view [fr

Stochastic resonance in an asymmetric bistable system driven by multiplicative colored noise and additive white noise

International Nuclear Information System (INIS)

Zhou Bingchang; Xu Wei

2008-01-01

The phenomenon of stochastic resonance (SR) in a bistable system driven by multiplicative colored and additive white noises and a periodic rectangular signal with a constant component is studied by using the unified colored noise approximation and the theory of signal-to-noise (SNR) in the adiabatic limit. The analytic expression of the SNR is obtained for arbitrary signal amplitude without being restricted to small amplitudes. The SNR is a non-monotonic function of intensities of multiplicative colored and additive white noises and correlation time of multiplicative colored noise, so SR exhibits in the bistable system. The effects of potential asymmetry r and correlation time τ of multiplicative colored noise on SNR are opposite. Moreover, It is more sensitive to control SR through adjusting the additive white noise intensity D than adjusting the multiplicative colored noise intensity Q

RESEND, Infinitely Dilute Point Cross-Sections Calculation from ENDF/B Resonance Parameter. ADLER, ENDF/B Adler-Adler Resonance Parameter to Point Cross-Sections with Doppler Broadening

International Nuclear Information System (INIS)

Bhat, M.R.; Ozer, O.

1982-01-01

1 - Description of problem or function: RESEND generates infinitely- dilute, un-broadened, point cross sections in the ENDF format by combining ENDF File 3 background cross sections with points calculated from ENDF File 2 resonance parameter data. ADLER calculates total, capture, and fission cross sections from the corresponding Adler-Adler parameters in the ENDF/B File 2 Version II data and also Doppler-broadens cross sections. 2 - Method of solution: RESEND calculations are done in two steps by two separate sections of the program. The first section does the resonance calculation and stores the results on a scratch file. The second section combines the data from the scratch file with background cross sections and prints the results. ADLER uses the Adler-Adler formalism. 3 - Restrictions on the complexity of the problem: RESEND expects its input to be a standard mode BCD ENDF file (Version II/III). Since the output is also a standard mode BCD ENDF file, the program is limited by the six significant figure accuracy inherent in the ENDF formats. (If the cross section has been calculated at two points so close in energy that only their least significant figures differ, that interval is assumed to have converged, even if other convergence criteria may not be satisfied.) In the unresolved range the cross sections have been averaged over a Porter-Thomas distribution. In some regions the calculated resonance cross sections may be negative. In such cases the standard convergence criterion would cause an unnecessarily large number of points to be produced in the region where the cross section becomes zero. For this reason an additional input convergence criterion (AVERR) may be used. If the absolute value of the cross section at both ends of an interval is determined to be less than AVERR then the interval is assumed to have converged. There are no limitations on the total number of points generated. The present ENDF (Version II/III) formats restrict the total number of

Soliton-induced nonlocal resonances observed through high-intensity tunable spectrally compressed second-harmonic peaks

DEFF Research Database (Denmark)

Zhou, Binbin; Guo, Hairun; Bache, Morten

2014-01-01

Experimental data of femtosecond thick-crystal second-harmonic generation show that when tuning away from phase matching, a dominating narrow spectral peak appears in the second harmonic that can be tuned over hundreds of nanometers by changing the phase-mismatch parameter. Traditional theory...... and the nonlocal theory indirectly proves that we have observed a soliton-induced nonlocal resonance. The soliton exists in the self-defocusing regime of the cascaded nonlinear interaction and in the normal dispersion regime of the crystal, and needs high input intensities to become excited....

Interference of laser-induced resonances in the continuous structures of a helium atom

International Nuclear Information System (INIS)

Magunov, A I; Strakhova, S I

2003-01-01

Coherent effects in the interference of overlapping laser-induced resonances in helium atoms are considered. The simultaneous action of single-mode radiation of the 294-nm second harmonic of a cw dye laser and a 1064-nm Nd:YAG laser on helium atoms provides the overlap of two resonances induced by transitions from the 1s2s 1 S and 1s4s 1 S helium levels. The shape of the overlapping laser-induced resonances in the rotating-wave approximation is described by analytic expressions, which depend on the laser radiation intensities and the ratio of laser frequencies. (nonlinear optical phenomena)

Enhancement of four-wave mixing induced by interacting dark resonances

International Nuclear Information System (INIS)

Yang Weifeng; Gong Shangqing; Niu Yueping; Jin Shiqi; Xu Zhizhan

2005-01-01

We analyse a four-wave mixing (FWM) scheme in a five-level atomic system in which double-dark resonances are present. It is found that the enhancement of FWM in both electromagnetically induced transparency (EIT) windows can be obtained even without the condition of multiphoton resonance. Moreover, the conversion efficiency of FWM in one EIT window can be much larger than that in the other due to the presence of interacting dark resonances

Multiscale Hy3S: Hybrid stochastic simulation for supercomputers

Directory of Open Access Journals (Sweden)

Kaznessis Yiannis N

2006-02-01

Full Text Available Abstract Background Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuations of "small" systems, these simulations produce a more accurate picture of single cell dynamics, including interesting phenomena missed by deterministic methods, such as noise-induced oscillations and transitions between stable states. However, the computational cost of the original stochastic simulation algorithm can be high, motivating the use of hybrid stochastic methods. Hybrid stochastic methods partition the system into multiple subsets and describe each subset as a different representation, such as a jump Markov, Poisson, continuous Markov, or deterministic process. By applying valid approximations and self-consistently merging disparate descriptions, a method can be considerably faster, while retaining accuracy. In this paper, we describe Hy3S, a collection of multiscale simulation programs. Results Building on our previous work on developing novel hybrid stochastic algorithms, we have created the Hy3S software package to enable scientists and engineers to both study and design extremely large well-mixed biological systems with many thousands of reactions and chemical species. We have added adaptive stochastic numerical integrators to permit the robust simulation of dynamically stiff biological systems. In addition, Hy3S has many useful features, including embarrassingly parallelized simulations with MPI; special discrete events, such as transcriptional and translation elongation and cell division; mid-simulation perturbations in both the number of molecules of species and reaction kinetic parameters; combinatorial variation of both initial conditions and kinetic parameters to enable sensitivity analysis; use of NetCDF optimized binary format to quickly read and write large datasets; and a simple graphical user interface, written in Matlab, to help users

Resonance-induced deviations of β from 2.0 for rare gas s-subshell photoionization

International Nuclear Information System (INIS)

Whitfield, S B; Wehlitz, R; Varma, H R; Banerjee, T; Deshmukh, P C; Manson, S T

2006-01-01

We investigate the case of resonance-induced deviations of the angular distribution anisotropy parameter, β, from its nominal value of 2.0 for the Kr 4s-subshell at the 3d → mp(m ≥ 5) excitations and the Xe 5s-subshell in the region of the 4d → mp(m ≥ 6) excitations. We observe small but unmistakable variations of β from 2.0 at these resonances. In the case of Kr the largest deviation from 2.0 is a mere -0.030(6), β 4s = 1.970(6), while in Xe it is definitively larger at -0.080(6), β 5s 1.920(6). To understand these results in more detail, we have carried out relativistic random phase and relativistic multi-channel quantum defect calculations. Our theoretical results clearly indicate deviations of β from 2.0 for these photolines in these resonance regions, although the degree of variation is predicted to be larger than what is observed. (letter to the editor)

Linear stochastic neutron transport theory

International Nuclear Information System (INIS)

Lewins, J.

1978-01-01

A new and direct derivation of the Bell-Pal fundamental equation for (low power) neutron stochastic behaviour in the Boltzmann continuum model is given. The development includes correlation of particle emission direction in induced and spontaneous fission. This leads to generalizations of the backward and forward equations for the mean and variance of neutron behaviour. The stochastic importance for neutron transport theory is introduced and related to the conventional deterministic importance. Defining equations and moment equations are derived and shown to be related to the backward fundamental equation with the detector distribution of the operational definition of stochastic importance playing the role of an adjoint source. (author)

Set up of a method for the adjustment of resonance parameters on integral experiments; Mise au point d`une methode d`ajustement des parametres de resonance sur des experiences integrales

Energy Technology Data Exchange (ETDEWEB)

Blaise, P.

1996-12-18

Resonance parameters for actinides play a significant role in the neutronic characteristics of all reactor types. All the major integral parameters strongly depend on the nuclear data of the isotopes in the resonance-energy regions.The author sets up a method for the adjustment of resonance parameters taking into account the self-shielding effects and restricting the cross section deconvolution problem to a limited energy region. (N.T.).

Exponential stability of uncertain stochastic neural networks with mixed time-delays

International Nuclear Information System (INIS)

Wang Zidong; Lauria, Stanislao; Fang Jian'an; Liu Xiaohui

2007-01-01

This paper is concerned with the global exponential stability analysis problem for a class of stochastic neural networks with mixed time-delays and parameter uncertainties. The mixed delays comprise discrete and distributed time-delays, the parameter uncertainties are norm-bounded, and the neural networks are subjected to stochastic disturbances described in terms of a Brownian motion. The purpose of the stability analysis problem is to derive easy-to-test criteria under which the delayed stochastic neural network is globally, robustly, exponentially stable in the mean square for all admissible parameter uncertainties. By resorting to the Lyapunov-Krasovskii stability theory and the stochastic analysis tools, sufficient stability conditions are established by using an efficient linear matrix inequality (LMI) approach. The proposed criteria can be checked readily by using recently developed numerical packages, where no tuning of parameters is required. An example is provided to demonstrate the usefulness of the proposed criteria

Radiation-induced electron paramagnetic resonance signal and soybean isoflavones content

International Nuclear Information System (INIS)

Oliveira, Marcos R.R. de; Mandarino, José M.G.; Mastro, Nelida L. del

2012-01-01

Electron Paramagnetic Resonance (EPR) is a well-known spectroscopic technique that detects paramagnetic centers and can detect free radicals with high sensitivity. In food, free radicals can be generated by several commonly used industrial processes, such as radiosterilization or heat treatment. EPR spectroscopy is used to detect radioinduced free radicals in food. In this work the relation between EPR signal induced by gamma irradiation treatment and soybean isoflavones content was investigated. Present results did not show correlation between total isoflavones content and the EPR signal. Nevertheless, some isoflavone contents had a negative correlation with the radiation-induced EPR signal. - Highlights: ► Electron Paramagnetic Resonance (EPR) detects free radicals. ► Ionizing radiation as free radicals inducer. ► Total soybean isoflvones do not correlate with radiation-induced EPR intensity but a soybean glucosyl glucoside isoflavone does.

Hopf Bifurcation of Compound Stochastic van der Pol System

Directory of Open Access Journals (Sweden)

Shaojuan Ma

2016-01-01

Full Text Available Hopf bifurcation analysis for compound stochastic van der Pol system with a bound random parameter and Gaussian white noise is investigated in this paper. By the Karhunen-Loeve (K-L expansion and the orthogonal polynomial approximation, the equivalent deterministic van der Pol system can be deduced. Based on the bifurcation theory of nonlinear deterministic system, the critical value of bifurcation parameter is obtained and the influence of random strength δ and noise intensity σ on stochastic Hopf bifurcation in compound stochastic system is discussed. At last we found that increased δ can relocate the critical value of bifurcation parameter forward while increased σ makes it backward and the influence of δ is more sensitive than σ. The results are verified by numerical simulations.

Stochastic models and reliability parameter estimation applicable to nuclear power plant safety

International Nuclear Information System (INIS)

Mitra, S.P.

1979-01-01

A set of stochastic models and related estimation schemes for reliability parameters are developed. The models are applicable for evaluating reliability of nuclear power plant systems. Reliability information is extracted from model parameters which are estimated from the type and nature of failure data that is generally available or could be compiled in nuclear power plants. Principally, two aspects of nuclear power plant reliability have been investigated: (1) The statistical treatment of inplant component and system failure data; (2) The analysis and evaluation of common mode failures. The model inputs are failure data which have been classified as either the time type of failure data or the demand type of failure data. Failures of components and systems in nuclear power plant are, in general, rare events.This gives rise to sparse failure data. Estimation schemes for treating sparse data, whenever necessary, have been considered. The following five problems have been studied: 1) Distribution of sparse failure rate component data. 2) Failure rate inference and reliability prediction from time type of failure data. 3) Analyses of demand type of failure data. 4) Common mode failure model applicable to time type of failure data. 5) Estimation of common mode failures from 'near-miss' demand type of failure data

Feasibility Study Evaluating Four Weeks Stochastic Resonance Whole-Body Vibration Training with Healthy Female Students

Directory of Open Access Journals (Sweden)

Slavko Rogan

2013-07-01

Full Text Available This study assessed the feasibility of stochastic resonance whole-body vibration (SR-WBV training and its impact on isometric maximal voluntary contraction (IMVC, isometric rate of force development (IRFD and a drop jump test (DJ in healthy female students. Twelve participants were randomised to static squats during SR-WBV 6 Hz, noise level 4, over 4 weeks or to a control group (no training. Feasibility outcomes included the number of students agreeing to participate, the number of drop-outs, the adherence to the SR-WBV and the evaluation of the protocol. Secondary outcomes were IMVC, IRFD and DJ. Results: Among 35 eligible students, 12 agreed to participate and two dropped out. The adherence was 41 of 60 possible sessions. There were moderate to large, but statistically non-significant, gains in the secondary outcomes. Conclusion: These results suggest that such a study would be feasible although with some modifications such as a better familiarisation to the DJ.

Radiation induced leakage due to stochastic charge trapping in isolation layers of nanoscale MOSFETs

Science.gov (United States)

Zebrev, G. I.; Gorbunov, M. S.; Pershenkov, V. S.

2008-03-01

The sensitivity of sub-100 nm devices to microdose effects, which can be considered as intermediate case between cumulative total dose and single event errors, is investigated. A detailed study of radiation-induced leakage due to stochastic charge trapping in irradiated planar and nonplanar devices is developed. The influence of High-K insulators on nanoscale ICs reliability is discussed. Low critical values of trapped charge demonstrate a high sensitivity to single event effect.

Self-induced parametric amplification arising from nonlinear elastic coupling in a micromechanical resonating disk gyroscope.

Science.gov (United States)

Nitzan, Sarah H; Zega, Valentina; Li, Mo; Ahn, Chae H; Corigliano, Alberto; Kenny, Thomas W; Horsley, David A

2015-03-12

Parametric amplification, resulting from intentionally varying a parameter in a resonator at twice its resonant frequency, has been successfully employed to increase the sensitivity of many micro- and nano-scale sensors. Here, we introduce the concept of self-induced parametric amplification, which arises naturally from nonlinear elastic coupling between the degenerate vibration modes in a micromechanical disk-resonator, and is not externally applied. The device functions as a gyroscope wherein angular rotation is detected from Coriolis coupling of elastic vibration energy from a driven vibration mode into a second degenerate sensing mode. While nonlinear elasticity in silicon resonators is extremely weak, in this high quality-factor device, ppm-level nonlinear elastic effects result in an order-of-magnitude increase in the observed sensitivity to Coriolis force relative to linear theory. Perfect degeneracy of the primary and secondary vibration modes is achieved through electrostatic frequency tuning, which also enables the phase and frequency of the parametric coupling to be varied, and we show that the resulting phase and frequency dependence of the amplification follow the theory of parametric resonance. We expect that this phenomenon will be useful for both fundamental studies of dynamic systems with low dissipation and for increasing signal-to-noise ratio in practical applications such as gyroscopes.

Radiation-induced frequency transients in AT, BT, and SC cut quartz resonators

International Nuclear Information System (INIS)

Koehler, D.R.

1979-01-01

Earlier studies of transient frequency changes in high-purity swept AT quartz resonators led to the conclusion that impurity-induced effects were small, while the observed changes were qualitatively and quantitatively well characterized in terms of the time changing temperature of the vibrating quartz and its effect on frequency. 5 MHz, AT cut fifth overtone, and BT and SC cut third overtone resonators were prepared from a single stone of Sawyer swept Premium-Q quartz. The resonators were operated in precision ovenized oscillators at or near their turnover temperatures. Pulsed irradiation, at dose levels of the order of 10 4 rads (Si) per pulse, was accomplished at Sandia. The experimental data display negative frequency transients for the AT cut resonators, positive frequency transients for the BT cut resonators, and very small transient effects for the SC cut resonators. From these experimental results, it is concluded that no measurable impurity-induced frequency changes are observed in this high-purity swept-quartz and that the frequency transients are accurately modelled in terms of transient temperature effects stemming from the thermal characteristics of the resonator structure

Ion stochastic heating by obliquely propagating magnetosonic waves

International Nuclear Information System (INIS)

Gao Xinliang; Lu Quanming; Wu Mingyu; Wang Shui

2012-01-01

The ion motions in obliquely propagating Alfven waves with sufficiently large amplitudes have already been studied by Chen et al.[Phys. Plasmas 8, 4713 (2001)], and it was found that the ion motions are stochastic when the wave frequency is at a fraction of the ion gyro-frequency. In this paper, with test particle simulations, we investigate the ion motions in obliquely propagating magnetosonic waves and find that the ion motions also become stochastic when the amplitude of the magnetosonic waves is sufficiently large due to the resonance at sub-cyclotron frequencies. Similar to the Alfven wave, the increase of the propagating angle, wave frequency, and the number of the wave modes can lower the stochastic threshold of the ion motions. However, because the magnetosonic waves become more and more compressive with the increase of the propagating angle, the decrease of the stochastic threshold with the increase of the propagating angle is more obvious in the magnetosonic waves than that in the Alfven waves.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

Energy Technology Data Exchange (ETDEWEB)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc [Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003 (United States)

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Resonance parameters for measured keV neutron capture cross sections

Energy Technology Data Exchange (ETDEWEB)

Musgrove, A.R. de L

1969-05-01

All available neutron capture cross sections in the keV region ({approx} to 100 keV) have been fitted with resonance parameters. Capture cross sections for nuclides with reasonably well known average s-wave parameters, but no measured cross section, have been calculated and tabulated using p-and d- wave strength functions interpolated between fitted values. Several of these nuclides are of interest in the theory of slow nucleosynthesis of heavy elements in stars, and the product of cosmic abundance (due to the s-process) and capture cross section at 30 keV has been plotted versus mass number. (author)

Phase transitions in trajectories of a superconducting single-electron transistor coupled to a resonator.

Science.gov (United States)

Genway, Sam; Garrahan, Juan P; Lesanovsky, Igor; Armour, Andrew D

2012-05-01

Recent progress in the study of dynamical phase transitions has been made with a large-deviation approach to study trajectories of stochastic jumps using a thermodynamic formalism. We study this method applied to an open quantum system consisting of a superconducting single-electron transistor, near the Josephson quasiparticle resonance, coupled to a resonator. We find that the dynamical behavior shown in rare trajectories can be rich even when the mean dynamical activity is small, and thus the formalism gives insights into the form of fluctuations. The structure of the dynamical phase diagram found from the quantum-jump trajectories of the resonator is studied, and we see that sharp transitions in the dynamical activity may be related to the appearance and disappearance of bistabilities in the state of the resonator as system parameters are changed. We also demonstrate that for a fast resonator, the trajectories of quasiparticles are similar to the resonator trajectories.

Total and fission cross-sections of 239Pu - statistical study of resonance parameters

International Nuclear Information System (INIS)

Derrien, H.; Blons, J.; Eggermann, C.; Michaudon, A.; Paya, D.; Ribon, P.

1967-01-01

The authors measured the total and fission cross-sections of 239 Pu with the linear accelerator at Saclay as a pulsed source of neutrons. The total cross-section was measured in the range from 4 to 700 eV and the best resolution used was 1.5 ns/m; the fission cross-section was measured between 4 eV and 6 keV, the best resolution having been 6 ns/m. The transmission measurements on five samples were made at the temperature of liquid nitrogen, and comparisons made with supplementary experiments at ambient temperature made it possible to determine the Doppler broadening factor (Δ = η√E). The resonances were identified from 4 to 500 eV in the total cross-section; the average level spacing was of the order of 2.4 eV. It would appear that, in this energy range, nearly all the levels were identified. The resonance parameters were determined by analysis of shape in conjunction with a least-squares programme on an IBM-7094 computer. The existence of a large number of broad resonances corresponding to very large fission widths has been shown to exist. Statistical study of the fission widths actually shows the existence of two families of resonances, one corresponding to a mean Γ f of the order of 45 meV and the other to a mean Γ/f of about 750 meV. The authors were therefore able to postulate a classification of resonances in terms of two spin states, the level population ratio in each family being: (2J 1 +1)/(2J 2 +1) = 1/3; J 1 = 0 corresponds to the broad resonances and J 2 = 1 to the narrow ones. The partial widths for radiative capture fluctuate slightly around a mean value of 40 meV. By using a multilevel programme, the authors were able to investigate the extent to which the existence of large fission widths might give rise to fictitious resonances (quasi-resonances) and perturbations and also to make a statistical study of the resonance parameters. (author) [fr

Electromagnetically induced transparency resonances inverted in magnetic field

Energy Technology Data Exchange (ETDEWEB)

Sargsyan, A.; Sarkisyan, D., E-mail: davsark@yahoo.com, E-mail: david@ipr.sci.am [National Academy of Sciences of Armenia, Institute for Physical Research (Armenia); Pashayan-Leroy, Y.; Leroy, C. [Université de Bourgogne-Dijon, Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR CNRS (France); Cartaleva, S. [Bulgarian Academy of Sciences, Institute of Electronics (Bulgaria); Wilson-Gordon, A. D. [Bar-Ilan University Ramat Gan, Department of Chemistry (Israel); Auzinsh, M. [University of Latvia, Department of Physics (Latvia)

2015-12-15

The phenomenon of electromagnetically induced transparency (EIT) is investigated in a Λ-system of the {sup 87}Rb D{sub 1} line in an external transverse magnetic field. Two spectroscopic cells having strongly different values of the relaxation rates γ{sub rel} are used: an Rb cell with antirelaxation coating (L ∼ 1 cm) and an Rb nanometric- thin cell (nanocell) with a thickness of the atomic vapor column L = 795 nm. For the EIT in the nanocell, we have the usual EIT resonances characterized by a reduction in the absorption (dark resonance (DR)), whereas for the EIT in the Rb cell with an antirelaxation coating, the resonances demonstrate an increase in the absorption (bright resonances (BR)). We suppose that such an unusual behavior of the EIT resonances (i.e., the reversal of the sign from DR to BR) is caused by the influence of an alignment process. The influence of alignment strongly depends on the configuration of the coupling and probe frequencies as well as on the configuration of the magnetic field.

Resonant behavior of the generalized Langevin system with tempered Mittag–Leffler memory kernel

Science.gov (United States)

Chen, Yao; Wang, Xudong; Deng, Weihua

2018-05-01

The generalized Langevin equation describes anomalous dynamics. Noise is not only the origin of uncertainty but also plays a positive role in helping to detect signals with information, termed stochastic resonance (SR). This paper analyzes the anomalous resonant behaviors of the generalized Langevin system with a multiplicative dichotomous noise and an internal tempered Mittag–Leffler noise. For a system with a fluctuating harmonic potential, we obtain the exact expressions of several types of SR such as the first moment, the amplitude and autocorrelation function for the output signal as well as the signal–noise ratio. We analyze the influence of the tempering parameter and memory exponent on the bona fide SR and the general SR. Moreover, it is detected that the critical memory exponent changes regularly with the increase of the tempering parameter. Almost all the theoretical results are validated by numerical simulations.

Determination of neutron resonance parameters of Neptunium 237 between 0 and 500 eV. The covariance matrices of statistical and of systematic origin, relating the resonance parameters, are also given

International Nuclear Information System (INIS)

Lepretre, A.; Herault, N.; Brusegan, A.; Noguere, G.; Siegler, P.

2002-12-01

This report is a follow up of the report CEA DAPNIA/SPHN-99-04T of Vincent Gressier. In the frame of a collaboration between the 'Commissariat a l'Energie Atomique (CEA)' and the Institute for Reference Materials and Measurement (IRMM, Geel, Belgique), the resonance parameters of neptunium 237 have been determined in the energy interval between 0 and 500 eV. These parameters have been obtained by using the Refit code in analysing simultaneously three transmission experiments. The covariance matrix of statistical origin is provided. A new method, based on various sensitivity studies is proposed for determining also the covariance matrix of systematic origin, relating the resonance parameters. From an experimental viewpoint, the study indicated that, with a large probability, the background spectrum has structure. A two dimensional profiler for the neutron density has been proved feasible. Such a profiler could, among others, demonstrate the existence of the structured background. (authors)

Uncertainty of Doppler reactivity worth due to uncertainties of JENDL-3.2 resonance parameters

Energy Technology Data Exchange (ETDEWEB)

Zukeran, Atsushi [Hitachi Ltd., Hitachi, Ibaraki (Japan). Power and Industrial System R and D Div.; Hanaki, Hiroshi; Nakagawa, Tuneo; Shibata, Keiichi; Ishikawa, Makoto

1998-03-01

Analytical formula of Resonance Self-shielding Factor (f-factor) is derived from the resonance integral (J-function) based on NR approximation and the analytical expression for Doppler reactivity worth ({rho}) is also obtained by using the result. Uncertainties of the f-factor and Doppler reactivity worth are evaluated on the basis of sensitivity coefficients to the resonance parameters. The uncertainty of the Doppler reactivity worth at 487{sup 0}K is about 4 % for the PNC Large Fast Breeder Reactor. (author)

Photon induced resonant Raman scattering in CdS

International Nuclear Information System (INIS)

Muzart, J.; Lluesma, E.G.; Arguello, C.A.; Leite, R.C.C.

1975-01-01

A novel aspect of resonant Raman scattering is observed in CdS by means of the ratio of Stokes to anti-Stokes intensities. With increasing temperature, as the forbidden band energy approaches a value that is twice the incident photon energy, (from a Nd-Yag-laser) a large enhancement of the above ratio is observed for both the LO and the 2LO phonon Raman intensities. The results indicate a resonance with the scattered photon. Resonance is only observed for high incident photon intensities. A possible explanation for the above observations is that flooding of the crystal with photons of energy hν induces states of energy hν displaced from the electronic bands by mixing of electronic and photon states

Enhancement of positron emission tomography-computed tomography image quality using the principle of stochastic resonance

International Nuclear Information System (INIS)

Pandey, Anil Kumar; Sharma, Sanjay Kumar; Sharma, Punit; Singh, Harmandeep; Patel, Chetan; Sarkar, Kaushik; Kumar, Rakesh; Bal, Chandra Sekhar

2014-01-01

Acquisition of higher counts improves visual perception of positron emission tomography-computed tomography (PET-CT) image. Larger radiopharmaceutical doses (implies more radiation dose) are administered to acquire this count in a short time period. However, diagnostic information does not increase after a certain threshold of counts. This study was conducted to develop a post processing method based on principle of “stochastic resonance” to improve visual perception of the PET-CT image having a required threshold counts. PET-CT images (JPEG file format) with low, medium, and high counts in the image were included in this study. The image was corrupted with the addition of Poisson noise. The amplitude of the Poisson noise was adjusted by dividing each pixel by a constant 1, 2, 4, 8, 16, and 32. The best amplitude of the noise that gave best images quality was selected based on high value of entropy of the output image, high value of structural similarity index and feature similarity index. Visual perception of the image was evaluated by two nuclear medicine physicians. The variation in structural and feature similarity of the image was not appreciable visually, but statistically images deteriorated as the noise amplitude increases although maintaining structural (above 70%) and feature (above 80%) similarity of input images in all cases. We obtained the best image quality at noise amplitude “4” in which 88% structural and 95% feature similarity of the input images was retained. This method of stochastic resonance can be used to improve the visual perception of the PET-CT image. This can indirectly lead to reduction of radiation dose

Features of the effect of the parameters of resonance systems with different configurations on the current-voltage characteristics of resonant-tunneling nanostructures in a subterahertz frequency range

International Nuclear Information System (INIS)

Aleksanyan, A.A.; Volchkov, N.A.; Dravin, V.A.; Kazakov, I.P.; Karuzskij, A.L.; Murzin, V.N.; Perestoronin, A.V.; Tskhovrebov, A.M.; Shmelev, S.S.

2014-01-01

Features of the effect of a subterahertz microwave field on the current characteristics of a resonant-tunneling diode in resonance systems with different configurations have been studied. Changes in the current characteristics of the resonant-tunneling diode under variation of the electrophysical parameters of dielectric and microstrip resonators, in particular high-Q-factor superconducting microstrip resonators, have been experimentally studied and analyzed [ru

Stochastic Still Water Response Model

DEFF Research Database (Denmark)

Friis-Hansen, Peter; Ditlevsen, Ove Dalager

2002-01-01

In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model is...... out that an important parameter of the stochastic cargo field model is the mean number of containers delivered by each customer.......In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...

Extended Gersgorin Theorem-Based Parameter Feasible Domain to Prevent Harmonic Resonance in Power Grid

Directory of Open Access Journals (Sweden)

Tao Lin

2017-10-01

Full Text Available Harmonic resonance may cause abnormal operation and even damage of power facilities, further threatening normal and safe operation of power systems. For renewable energy generations, controlled loads and parallel reactive power compensating equipment, their operating statuses can vary frequently. Therefore, the parameters of equivalent fundamental and harmonic admittance/impedance of these components exist in uncertainty, which will change the elements and eigenvalues of harmonic network admittance matrix. Consequently, harmonic resonance in power grid is becoming increasingly more complex. Hence, intense research about prevention and suppression of harmonic resonance, particularly the parameter feasible domain (PFD which can keep away from harmonic resonance, are needed. For rapid online evaluation of PFD, a novel method without time-consuming pointwise precise eigenvalue computations is proposed. By analyzing the singularity of harmonic network admittance matrix, the explicit sufficient condition that the matrix elements should meet to prevent harmonic resonance is derived by the extended Gersgorin theorem. Further, via the non-uniqueness of similar transformation matrix (STM, a strategy to determine the appropriate STM is proposed to minimize the conservation of the obtained PFD. Eventually, the availability and advantages in computation efficiency and conservation of the method, are demonstrated through four different scale benchmarks.

Stochastic Parameter Estimation of Non-Linear Systems Using Only Higher Order Spectra of the Measured Response

Science.gov (United States)

Vasta, M.; Roberts, J. B.

1998-06-01

Methods for using fourth order spectral quantities to estimate the unknown parameters in non-linear, randomly excited dynamic systems are developed. Attention is focused on the case where only the response is measurable and the excitation is unmeasurable and known only in terms of a stochastic process model. The approach is illustrated through application to a non-linear oscillator with both non-linear damping and stiffness and with excitation modelled as a stationary Gaussian white noise process. The methods have applications in studies of the response of structures to random environmental loads, such as wind and ocean wave forces.

Geomechanics-Based Stochastic Analysis of Injection- Induced Seismicity

Energy Technology Data Exchange (ETDEWEB)

Ghassemi, Ahmad [Univ. of Oklahoma, Norman, OK (United States)

2017-08-21

-thermo-poro-mechanical mechanisms associated with injection and utilizing a state-of-the-art stochastic inversion procedure. The approach proposed herein is innovative and significantly improves the existing SBCR technology (e.g., Shapiro et al. 2003) for geothermal reservoirs in several ways. First, the current scope of the SBRC is limited with respect to the physical processes considered and the rock properties used. Usually, the geomechanics analyses within SBRC is limited to the pore pressure diffusion in the rock mass, which is modeled using a time-dependent parabolic equation and solved using a finite element algorithm with either a line or a point source. However, water injection induces both poroelastic and thermoelastic stresses in the rock mass which affect the stress state. In fact, it has been suggested that thermoelastic stresses can play a dominant role in reservoir seismicity (Ghassemi et al., 2007). We include these important effects by using a fully-coupled poro-thermoelastic constitutive equations for the rock mass which will be solved using a 3D finite element model with more realistic injection geometries such as multiple injection/extraction sources (and in fractures), uncertainty in the material parameters and the in-situ stress distribution to better reflect the pore pressure and stress distributions. In addition, we developed a 3D stochastic fracture network model to study MEQ generation in fracture rocks. The model was verified using laboratory experiments, and calibrated and applied to Newberry EGS stimulation. In previous SBRC approaches, the triggering of micro-seismicity is modeled base on the assumption that the prior stochastic criticality model of the rock mass is a valid and adequate description. However, this assumption often does not hold in the field. Thus, we improved upon the current SBRC approach by using the micro-seismic responses to estimate the hydraulic diffusivity as well as the criticality distribution itself within the field. In this way, instead of

POLLA-NESC, Resonance Parameter R-Matrix to S-Matrix Conversion by Reich-Moore Method

International Nuclear Information System (INIS)

Saussure, G. de; Perez, R.B.

1975-01-01

1 - Description of problem or function: The program transforms a set of r-matrix nuclear resonance parameters into a set of equivalent s-matrix (or Kapur-Peierls) resonance parameters. 2 - Method of solution: The program utilizes the multilevel formalism of Reich and Moore and avoids diagonalization of the level matrix. The parameters are obtained by a direct partial fraction expansion of the Reich-Moore expression of the collision matrix. This approach appears simpler and faster when the number of fission channels is known and small. The method is particularly useful when a large number of levels must be considered because it does not require diagonalization of a large level matrix. 3 - Restrictions on the complexity of the problem: By DIMENSION statements, the program is limited to maxima of 100 levels and 5 channels

Nonlinear dynamics and bifurcation characteristics of shape memory alloy thin films subjected to in-plane stochastic excitation

International Nuclear Information System (INIS)

Zhu, Zhi-Wen; Zhang, Qing-Xin; Xu, Jia

2014-01-01

A kind of shape memory alloy (SMA) hysteretic nonlinear model was developed, and the nonlinear dynamics and bifurcation characteristics of the SMA thin film subjected to in-plane stochastic excitation were investigated. Van der Pol difference item was introduced to describe the hysteretic phenomena of the SMA strain–stress curves, and the nonlinear dynamic model of the SMA thin film subjected to in-plane stochastic excitation was developed. The conditions of global stochastic stability of the system were determined in singular boundary theory, and the probability density function of the system response was obtained. Finally, the conditions of stochastic Hopf bifurcation were analyzed. The results of theoretical analysis and numerical simulation indicate that self-excited vibration is induced by the hysteretic nonlinear characteristics of SMA, and stochastic Hopf bifurcation appears when the bifurcation parameter was changed; there are two limit cycles in the stationary probability density of the dynamic response of the system in some cases, which means that there are two vibration amplitudes whose probabilities are both very high, and jumping phenomena between the two vibration amplitudes appear with the change in conditions. The results obtained in this current paper are helpful for the application of the SMA thin film in stochastic vibration fields. - Highlights: • Hysteretic nonlinear model of shape memory alloy was developed. • Van der Pol item was introduced to interpret hysteretic strain–stress curves. • Nonlinear dynamic characteristics of the shape memory alloy film were analyzed. • Jumping phenomena were observed in the change of the parameters

Reconstructing the hidden states in time course data of stochastic models.

Science.gov (United States)

Zimmer, Christoph

2015-11-01

Parameter estimation is central for analyzing models in Systems Biology. The relevance of stochastic modeling in the field is increasing. Therefore, the need for tailored parameter estimation techniques is increasing as well. Challenges for parameter estimation are partial observability, measurement noise, and the computational complexity arising from the dimension of the parameter space. This article extends the multiple shooting for stochastic systems' method, developed for inference in intrinsic stochastic systems. The treatment of extrinsic noise and the estimation of the unobserved states is improved, by taking into account the correlation between unobserved and observed species. This article demonstrates the power of the method on different scenarios of a Lotka-Volterra model, including cases in which the prey population dies out or explodes, and a Calcium oscillation system. Besides showing how the new extension improves the accuracy of the parameter estimates, this article analyzes the accuracy of the state estimates. In contrast to previous approaches, the new approach is well able to estimate states and parameters for all the scenarios. As it does not need stochastic simulations, it is of the same order of speed as conventional least squares parameter estimation methods with respect to computational time. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Analysis of stochastic effects in Kaldor-type business cycle discrete model

Science.gov (United States)

Bashkirtseva, Irina; Ryashko, Lev; Sysolyatina, Anna

2016-07-01

We study nonlinear stochastic phenomena in the discrete Kaldor model of business cycles. A numerical parametric analysis of stochastically forced attractors (equilibria, closed invariant curves, discrete cycles) of this model is performed using the stochastic sensitivity functions technique. A spatial arrangement of random states in stochastic attractors is modeled by confidence domains. The phenomenon of noise-induced transitions ;chaos-order; is discussed.

Neutron Capture and Transmission Measurements and Resonance Parameter Analysis of Niobium

International Nuclear Information System (INIS)

NJ Drindak; JA Burke; G Leinweber; JA Helm; JG Hoole; RC Block; Y Danon; RE Slovacek; BE Moretti; CJ Werner; ME Overberg; SA Kolda; MJ Trbovich; DP Barry

2005-01-01

Epithermal neutron capture and transmission measurements were performed using the time-of-flight method at the RPI linac using metallic Nb samples. The capture measurements were made at the 25-meter flight station with a 16-section sodium iodide multiplicity detector and the transmission measurements at the 25-meter flight station with a Li-6 glass scintillation detector. Resonance parameters were determined for all resonances up to 500eV with a combined analysis of capture and transmission data using the multi-level R-matrix Bayesian code SAMMY. The present results are compared to those presented in ENDF/B-VI, updated through Release 3