Aperiodic signals processing via parameter-tuning stochastic resonance in a photorefractive ring cavity

Directory of Open Access Journals (Sweden)

Xuefeng Li

2014-04-01

Full Text Available Based on solving numerically the generalized nonlinear Langevin equation describing the nonlinear dynamics of stochastic resonance by Fourth-order Runge-Kutta method, an aperiodic stochastic resonance based on an optical bistable system is numerically investigated. The numerical results show that a parameter-tuning stochastic resonance system can be realized by choosing the appropriate optical bistable parameters, which performs well in reconstructing aperiodic signals from a very high level of noise background. The influences of optical bistable parameters on the stochastic resonance effect are numerically analyzed via cross-correlation, and a maximum cross-correlation gain of 8 is obtained by optimizing optical bistable parameters. This provides a prospective method for reconstructing noise-hidden weak signals in all-optical signal processing systems.

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.

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.

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 and superharmonic stochastic resonances of a confined overdamped harmonic oscillator

Science.gov (United States)

Zhang, Lu; Lai, Li; Peng, Hao; Tu, Zhe; Zhong, Suchuan

2018-01-01

The dynamics of many soft condensed matter and biological systems is affected by space limitations, which produce some peculiar effects on the systems' stochastic resonance (SR) behavior. In this study, we propose a model where SR can be observed: a confined overdamped harmonic oscillator that is subjected to a sinusoidal driving force and is under the influence of a multiplicative white noise. The output response of the system is a periodic signal with harmonic frequencies that are odd multiples of the driving frequency. We verify the amplitude resonances at the driving frequencies and superharmonic frequencies that are equal to three, five, and seven times the driving frequency, using a numerical method based on the stochastic Taylor expansion. The synergistic effect of the multiplicative white noise, constant boundaries, and periodic driving force that can induce a SR in the output amplitude at the driving and superharmonic frequencies is found. The SR phenomenon found in this paper is sensitive to the driving amplitude and frequency, inherent potential parameter, and boundary width, thus leading to various resonance conditions. Therefore, the mechanism found could be beneficial for the characterization of these confined systems and could constitute an important tool for controlling their basic properties.

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)

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

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

Causal interpretation of stochastic differential equations

DEFF Research Database (Denmark)

Sokol, Alexander; Hansen, Niels Richard

2014-01-01

We give a causal interpretation of stochastic differential equations (SDEs) by defining the postintervention SDE resulting from an intervention in an SDE. We show that under Lipschitz conditions, the solution to the postintervention SDE is equal to a uniform limit in probability of postintervention...... structural equation models based on the Euler scheme of the original SDE, thus relating our definition to mainstream causal concepts. We prove that when the driving noise in the SDE is a Lévy process, the postintervention distribution is identifiable from the generator of the SDE....

The Role of Stochastic Models in Interpreting the Origins of Biological Chirality

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Gábor Lente

2010-04-01

Full Text Available This review summarizes recent stochastic modeling efforts in the theoretical research aimed at interpreting the origins of biological chirality. Stochastic kinetic models, especially those based on the continuous time discrete state approach, have great potential in modeling absolute asymmetric reactions, experimental examples of which have been reported in the past decade. An overview of the relevant mathematical background is given and several examples are presented to show how the significant numerical problems characteristic of the use of stochastic models can be overcome by non-trivial, but elementary algebra. In these stochastic models, a particulate view of matter is used rather than the concentration-based view of traditional chemical kinetics using continuous functions to describe the properties system. This has the advantage of giving adequate description of single-molecule events, which were probably important in the origin of biological chirality. The presented models can interpret and predict the random distribution of enantiomeric excess among repetitive experiments, which is the most striking feature of absolute asymmetric reactions. It is argued that the use of the stochastic kinetic approach should be much more widespread in the relevant literature.

Endogenous fields enhanced stochastic resonance in a randomly coupled neuronal network

International Nuclear Information System (INIS)

Deng, Bin; Wang, Lin; Wang, Jiang; Wei, Xi-le; Yu, Hai-tao

2014-01-01

Highlights: • We study effects of endogenous fields on stochastic resonance in a neural network. • Stochastic resonance can be notably enhanced by endogenous field feedback. • Endogenous field feedback delay plays a vital role in stochastic resonance. • The parameters of low-passed filter play a subtle role in SR. - Abstract: Endogenous field, evoked by structured neuronal network activity in vivo, is correlated with many vital neuronal processes. In this paper, the effects of endogenous fields on stochastic resonance (SR) in a randomly connected neuronal network are investigated. The network consists of excitatory and inhibitory neurons and the axonal conduction delays between neurons are also considered. Numerical results elucidate that endogenous field feedback results in more rhythmic macroscope activation of the network for proper time delay and feedback coefficient. The response of the network to the weak periodic stimulation can be notably enhanced by endogenous field feedback. Moreover, the endogenous field feedback delay plays a vital role in SR. We reveal that appropriately tuned delays of the feedback can either induce the enhancement of SR, appearing at every integer multiple of the weak input signal’s oscillation period, or the depression of SR, appearing at every integer multiple of half the weak input signal’s oscillation period for the same feedback coefficient. Interestingly, the parameters of low-passed filter which is used in obtaining the endogenous field feedback signal play a subtle role in SR

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...

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 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 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)

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.

Two Stochastic Resonances Induced by Two Different Multiplicative Telegraphic Noises for an Electric System

International Nuclear Information System (INIS)

Li Jinghui

2008-01-01

In this paper, an electric system with two dichotomous resistors is investigated. It is shown that this system can display two stochastic resonances, which are the amplitude of the periodic response as the functions of the two dichotomous resistors strengthes respectively. In the limits of Gaussian white noise and shot white noise (i.e., the two noises are both Gaussian white noise or shot white noise), no phenomena of resonance appear. By further study, we find that when the system is with three or more multiplicative telegraphic noises, there are three or more stochastic resonances

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.

On the interpretations of Langevin stochastic equation in different coordinate systems

International Nuclear Information System (INIS)

Martinez, E.; Lopez-Diaz, L.; Torres, L.; Alejos, O.

2004-01-01

The stochastic Langevin Landau-Lifshitz equation is usually utilized in micromagnetics formalism to account for thermal effects. Commonly, two different interpretations of the stochastic integrals can be made: Ito and Stratonovich. In this work, the Langevin-Landau-Lifshitz (LLL) equation is written in both Cartesian and Spherical coordinates. If Spherical coordinates are employed, the noise is additive, and therefore, Ito and Stratonovich solutions are equal. This is not the case when (LLL) equation is written in Cartesian coordinates. In this case, the Langevin equation must be interpreted in the Stratonovich sense in order to reproduce correct statistical results. Nevertheless, the statistics of the numerical results obtained from Euler-Ito and Euler-Stratonovich schemes are equivalent due to the additional numerical constraint imposed in Cartesian system after each time step, which itself assures that the magnitude of the magnetization is preserved

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

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.

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.

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.

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

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.

Stochastic Resonance Induced by Dichotomous Resistor in an Electric Circuit

International Nuclear Information System (INIS)

Li Jinghui; Han Yinxia

2007-01-01

An electric circuit with dichotomous resistor is investigated. It is shown that the amplitude of the average electric current washing the resistor represents the phenomenon of stochastic resonance, which is the response as a function of the correlation time of the dichotomous resistor.

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.

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.

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)

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.

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 resonance in the presence of slowly varying control parameters

International Nuclear Information System (INIS)

Nicolis, C; Nicolis, G

2005-01-01

The kinetics of transitions between states in a noisy system is studied in the simultaneous presence of a periodic forcing and a ramp. It is shown that the interaction between stochastic resonance and the action of the ramp may give rise to a new method for the control of the transition rates

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.

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.

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

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

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.

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

Fluctuations induced extinction and stochastic resonance effect in a model of tumor growth with periodic treatment

Energy Technology Data Exchange (ETDEWEB)

Li Dongxi, E-mail: lidongxi@mail.nwpu.edu.c [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Xu Wei; Guo, Yongfeng; Xu Yong [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)

2011-01-31

We investigate a stochastic model of tumor growth derived from the catalytic Michaelis-Menten reaction with positional and environmental fluctuations under subthreshold periodic treatment. Firstly, the influences of environmental fluctuations on the treatable stage are analyzed numerically. Applying the standard theory of stochastic resonance derived from the two-state approach, we derive the signal-to-noise ratio (SNR) analytically, which is used to measure the stochastic resonance phenomenon. It is found that the weak environmental fluctuations could induce the extinction of tumor cells in the subthreshold periodic treatment. The positional stability is better in favor of the treatment of the tumor cells. Besides, the appropriate and feasible treatment intensity and the treatment cycle should be highlighted considered in the treatment of tumor cells.

Fluctuations induced extinction and stochastic resonance effect in a model of tumor growth with periodic treatment

International Nuclear Information System (INIS)

Li Dongxi; Xu Wei; Guo, Yongfeng; Xu Yong

2011-01-01

We investigate a stochastic model of tumor growth derived from the catalytic Michaelis-Menten reaction with positional and environmental fluctuations under subthreshold periodic treatment. Firstly, the influences of environmental fluctuations on the treatable stage are analyzed numerically. Applying the standard theory of stochastic resonance derived from the two-state approach, we derive the signal-to-noise ratio (SNR) analytically, which is used to measure the stochastic resonance phenomenon. It is found that the weak environmental fluctuations could induce the extinction of tumor cells in the subthreshold periodic treatment. The positional stability is better in favor of the treatment of the tumor cells. Besides, the appropriate and feasible treatment intensity and the treatment cycle should be highlighted considered in the treatment of tumor cells.

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 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.

Stochastic resonance induced by the novel random transitions of two-dimensional weak damping bistable duffing oscillator and bifurcation of moment equation

International Nuclear Information System (INIS)

Zhang Guangjun; Xu Jianxue; Wang Jue; Yue Zhifeng; Zou Hailin

2009-01-01

In this paper stochastic resonance induced by the novel random transitions of two-dimensional weak damping bistable Duffing oscillator is analyzed by moment method. This kind of novel transition refers to the one among three potential well on two sides of bifurcation point of original system at the presence of internal noise. Several conclusions are drawn. First, the semi-analytical result of stochastic resonance induced by the novel random transitions of two-dimensional weak damping bistable Duffing oscillator can be obtained, and the semi-analytical result is qualitatively compatible with the one of Monte Carlo simulation. Second, a bifurcation of double-branch fixed point curves occurs in the moment equations with noise intensity as their bifurcation parameter. Third, the bifurcation of moment equations corresponds to stochastic resonance of original system. Finally, the mechanism of stochastic resonance is presented from another viewpoint through analyzing the energy transfer induced by the bifurcation of moment equation.

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.

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...

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

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

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...

Geometric and potential dynamics interpretation of the optic ring resonator bistability

Science.gov (United States)

Chiangga, S.; Chittha, T.; Frank, T. D.

2015-07-01

The optical bistability is a fundamental nonlinear feature of the ring resonator. A geometric and potential dynamics interpretation of the bistability is given. Accordingly, the bistability of the nonlinear system is shown to be a consequence of geometric laws of vector calculus describing the resonator ring. In contrast, the so-called transcendental relations that have been obtained in the literature in order to describe the optical wave are interpreted in terms of potential dynamical systems. The proposed novel interpretation provides new insights into the nature of the ring resonator optical bistability. The fundamental work by Rukhlenko, Premaratne and Agrawal (2010) as well as a more recent study by Chiangga, Pitakwongsaporn, Frank and Yupapin (2013) are considered.

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.

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.

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.

Stochastic resonance induced by novel random transitions of motion of FitzHugh-Nagumo neuron model

International Nuclear Information System (INIS)

Zhang Guangjun; Xu Jianxue

2005-01-01

In contrast to the previous studies which have dealt with stochastic resonance induced by random transitions of system motion between two coexisting limit cycle attractors in the FitzHugh-Nagumo (FHN) neuron model after Hopf bifurcation and which have dealt with the phenomenon of stochastic resonance induced by external noise when the model with periodic input has only one attractor before Hopf bifurcation, in this paper we have focused our attention on stochastic resonance (SR) induced by a novel transition behavior, the transitions of motion of the model among one attractor on the left side of bifurcation point and two attractors on the right side of bifurcation point under the perturbation of noise. The results of research show: since one bifurcation of transition from one to two limit cycle attractors and the other bifurcation of transition from two to one limit cycle attractors occur in turn besides Hopf bifurcation, the novel transitions of motion of the model occur when bifurcation parameter is perturbed by weak internal noise; the bifurcation point of the model may stochastically slightly shift to the left or right when FHN neuron model is perturbed by external Gaussian distributed white noise, and then the novel transitions of system motion also occur under the perturbation of external noise; the novel transitions could induce SR alone, and when the novel transitions of motion of the model and the traditional transitions between two coexisting limit cycle attractors after bifurcation occur in the same process the SR also may occur with complicated behaviors types; the mechanism of SR induced by external noise when FHN neuron model with periodic input has only one attractor before Hopf bifurcation is related to this kind of novel transition mentioned above

Extended Smoluchowski models for interpreting relaxation phenomena in liquids

International Nuclear Information System (INIS)

Polimeno, A.; Frezzato, D.; Saielli, G.; Moro, G.J.; Nordio, P.L.

1998-01-01

Interpretation of the dynamical behaviour of single molecules or collective modes in liquids has been increasingly centered, in the last decade, on complex liquid systems, including ionic solutions, polymeric liquids, supercooled fluids and liquid crystals. This has been made necessary by the need of interpreting dynamical data obtained by advanced experiments, like optical Kerr effect, time dependent fluorescence shift experiments, two-dimensional Fourier-transform and high field electron spin resonance and scattering experiments like quasi-elastic neutron scattering. This communication is centered on the definition, treatment and application of several extended stochastic models, which have proved to be very effective tools for interpreting and rationalizing complex relaxation phenomena in liquids structures. First, applications of standard Fokker-Planck equations for the orientational relaxation of molecules in isotropic and ordered liquid phase are reviewed. In particular attention will be focused on the interpretation of neutron scattering in nematics. Next, an extended stochastic model is used to interpret time-domain resolved fluorescence emission experiments. A two-body stochastic model allows the theoretical interpretation of dynamical Stokes shift effects in fluorescence emission spectra, performed on probes in isotropic and ordered polar phases. Finally, for the case of isotropic fluids made of small rigid molecules, a very detailed model is considered, which includes as basic ingredients a Fokker-Planck description of the molecular vibrational motion and the slow diffusive motion of a persistent cage structure together with the decay processes related to the changing structure of the cage. (author)

Stochastic resonance and noise delayed extinction in a model of two competing species

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Valenti, D.; Fiasconaro, A.; Spagnolo, B.

2004-01-01

We study the role of the noise in the dynamics of two competing species. We consider generalized Lotka-Volterra equations in the presence of a multiplicative noise, which models the interaction between the species and the environment. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence of a periodic driving term, which accounts for the environment temperature variation. We find noise-induced periodic oscillations of the species concentrations and stochastic resonance phenomenon. We find also a nonmonotonic behavior of the mean extinction time of one of the two competing species as a function of the additive noise intensity.

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

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

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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.

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.

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)

Interpretation of non-Markovian stochastic Schroedinger equations as a hidden-variable theory

International Nuclear Information System (INIS)

Gambetta, Jay; Wiseman, H.M.

2003-01-01

Do diffusive non-Markovian stochastic Schroedinger equations (SSEs) for open quantum systems have a physical interpretation? In a recent paper [Phys. Rev. A 66, 012108 (2002)] we investigated this question using the orthodox interpretation of quantum mechanics. We found that the solution of a non-Markovian SSE represents the state the system would be in at that time if a measurement was performed on the environment at that time, and yielded a particular result. However, the linking of solutions at different times to make a trajectory is, we concluded, a fiction. In this paper we investigate this question using the modal (hidden variable) interpretation of quantum mechanics. We find that the noise function z(t) appearing in the non-Markovian SSE can be interpreted as a hidden variable for the environment. That is, some chosen property (beable) of the environment has a definite value z(t) even in the absence of measurement on the environment. The non-Markovian SSE gives the evolution of the state of the system 'conditioned' on this environment hidden variable. We present the theory for diffusive non-Markovian SSEs that have as their Markovian limit SSEs corresponding to homodyne and heterodyne detection, as well as one which has no Markovian limit

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

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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

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

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.

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

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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.

Regarding light resonance interpretations of the B decay anomalies

Science.gov (United States)

Bishara, Fady; Haisch, Ulrich; Monni, Pier Francesco

2017-09-01

We sketch a novel method to search for light di-leptonic resonances by exploiting precision measurements of Drell-Yan production. Motivated by the recent hints of lepton flavor universality violation in B →K*ℓ+ℓ-, we illustrate our proposal by studying the case of spin-1 resonances that couple to muons and have masses in the range of a few GeV. We show that the existing LHC data on p p →Z/γ* →μ+μ- put nontrivial constraints on light di-muon resonance interpretations of B decay anomalies in a model-independent fashion. The impact of our proposal on the long-standing discrepancy in the anomalous magnetic moment of the muon is also briefly discussed.

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

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.

Inverse stochastic resonance induced by synaptic background activity with unreliable synapses

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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.

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

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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.

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.

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

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

Stochastic Switching Dynamics

DEFF Research Database (Denmark)

Simonsen, Maria

This thesis treats stochastic systems with switching dynamics. Models with these characteristics are studied from several perspectives. Initially in a simple framework given in the form of stochastic differential equations and, later, in an extended form which fits into the framework of sliding...... mode control. It is investigated how to understand and interpret solutions to models of switched systems, which are exposed to discontinuous dynamics and uncertainties (primarily) in the form of white noise. The goal is to gain knowledge about the performance of the system by interpreting the solution...

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

Directory of Open Access Journals (Sweden)

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

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

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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.

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.

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.

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.

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

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.

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

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 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)

Agreement in the Interpretation of Magnetic Resonance Images of the Lumbar Spine

DEFF Research Database (Denmark)

Kovacs, F M; Royuela, A; Jensen, Tue Secher

2009-01-01

Background: Correlation between clinical features and magnetic resonance imaging (MRI) findings is essential in low-back-pain patients. Most previous studies have analyzed concordance in the interpretation of lumbar MRI among a few radiologists who worked together. This may have overestimated...

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)

Estimating and interpreting a common stochastic component for the Brazilian industrial production index

Directory of Open Access Journals (Sweden)

Paulo Picchetti

2002-03-01

Full Text Available This paper employs a state-space formulation to model a common stochastic component in four different series that constitute the aggregate index of industrial production in Brazil. This estimated common component is then interpreted as a measurement of behavior of fundamentals in the brazilian economy and compared to the actual aggregate index.A partir de uma formulação em espaço de estado, modelamos um componente estocástico comum para quatro séries distintas que compõem o índice agregado de produção industrial calculado pelo IBGE para o Brasil. Esse componente estocástico comum estimado é então interpretado como uma medida do comportamento de fundamentos da economia brasileira, e comparado com o índice agregado efetivo.

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.

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.

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)

Stochastic coalgebraic logic

CERN Document Server

Doberkat, Ernst-Erich

2009-01-01

Combining coalgebraic reasoning, stochastic systems and logic, this volume presents the principles of coalgebraic logic from a categorical perspective. Modal logics are also discussed, including probabilistic interpretations and an analysis of Kripke models.

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

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.

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.

Stochastic temperature and the Nicolai map

International Nuclear Information System (INIS)

Hueffel, H.

1989-01-01

Just as standard temperature can be related to the time coordinate of Euclidean space, a new concept of 'stochastic temperature' may be introduced by associating it to the Parisi-Wu time of stochastic quantization. The perturbative equilibrium limit for a self-interacting scalar field is studied, and a 'thermal' mass shift to one loop is shown. In addition one may interpret the underlying stochastic process as a Nicolai map at nonzero 'temperature'. 22 refs. (Author)

Probabilistic interpretation of resonant states

Indian Academy of Sciences (India)

The present paper reviews the basic definition of the resonant state in quantum ... We show that particles leak from the central region in the resonant state. The ..... The basic idea is as follows (figure 4): Consider a resonant eigenstate. Φn(x ...

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...

Nuclear criticality safety: general. 3. Tokaimura Criticality Accident: Point Model Stochastic Neutronic Interpretation

International Nuclear Information System (INIS)

Mechitoua, Boukhmes

2001-01-01

This paper shows what can be the stochastic neutronic contribution for the interpretation of criticality accidents. Stochastic neutronic comprehensive texts may be found in refs.1 through 4. We limit our study to the use of initiation probability, which is an important stochastic neutronic tally. Initiation probability P may be defined as the probability for one neutron to initiate an infinite neutron fission chain. The complement probability of P is the extinction probability Q. The probability that the neutron fission chain produced by one neutron will quench is equal to the multiplication of the probability of production of i neutrons g i by the probability of extinction of these i neutrons. We can estimate P by a Newton or by a dichotomic method. We suppose that P S (t) is the probability that an infinite neutron fission chain has been initiated before time t by a neutron produced by the source S(t). P S (t + dt) is the sum of two probabilities: 1. the probability that an infinite neutron fission chain has been initiated before time t by a neutron produced by the source S(t): P S (t); 2. The second probability is a multiplication of two probabilities: the probability that there was no initiation before t that is 1-P S (t), and the probability that a neutron emitted by the source with the probability S dt initiates an infinite neutron fission chain with the probability P(t). This last relation gives the link between P and the source density. The aim of this paper is to show how one can apply the foregoing derivations. We have simplified the Tokaimura criticality accident for this application. We have mono-energetic neutrons with infinite and homogeneous media; we have two reactions: capture and fission. In this section, we show how one can estimate the initiation probability with a source density as a function of time. This estimation makes use of three steps: 1. Reactivity insertion: Estimation of the multiplication coefficient as a function of time K(t). This

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.

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)

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

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.

Stochastic interpretation of the advection-diffusion equation and its relevance to bed load transport

Science.gov (United States)

Ancey, C.; Bohorquez, P.; Heyman, J.

2015-12-01

The advection-diffusion equation is one of the most widespread equations in physics. It arises quite often in the context of sediment transport, e.g., for describing time and space variations in the particle activity (the solid volume of particles in motion per unit streambed area). Phenomenological laws are usually sufficient to derive this equation and interpret its terms. Stochastic models can also be used to derive it, with the significant advantage that they provide information on the statistical properties of particle activity. These models are quite useful when sediment transport exhibits large fluctuations (typically at low transport rates), making the measurement of mean values difficult. Among these stochastic models, the most common approach consists of random walk models. For instance, they have been used to model the random displacement of tracers in rivers. Here we explore an alternative approach, which involves monitoring the evolution of the number of particles moving within an array of cells of finite length. Birth-death Markov processes are well suited to this objective. While the topic has been explored in detail for diffusion-reaction systems, the treatment of advection has received no attention. We therefore look into the possibility of deriving the advection-diffusion equation (with a source term) within the framework of birth-death Markov processes. We show that in the continuum limit (when the cell size becomes vanishingly small), we can derive an advection-diffusion equation for particle activity. Yet while this derivation is formally valid in the continuum limit, it runs into difficulty in practical applications involving cells or meshes of finite length. Indeed, within our stochastic framework, particle advection produces nonlocal effects, which are more or less significant depending on the cell size and particle velocity. Albeit nonlocal, these effects look like (local) diffusion and add to the intrinsic particle diffusion (dispersal due

Affine stochastic mortality

NARCIS (Netherlands)

Schrager, D.F.

2006-01-01

We propose a new model for stochastic mortality. The model is based on the literature on affine term structure models. It satisfies three important requirements for application in practice: analytical tractibility, clear interpretation of the factors and compatibility with financial option pricing

Memristors Empower Spiking Neurons With Stochasticity

KAUST Repository

Al-Shedivat, Maruan

2015-06-01

Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms. © 2011 IEEE.

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)

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)

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.

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

Deterministic Versus Stochastic Interpretation of Continuously Monitored Sewer Systems

DEFF Research Database (Denmark)

Harremoës, Poul; Carstensen, Niels Jacob

1994-01-01

An analysis has been made of the uncertainty of input parameters to deterministic models for sewer systems. The analysis reveals a very significant uncertainty, which can be decreased, but not eliminated and has to be considered for engineering application. Stochastic models have a potential for ...

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.

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 theories of quantum mechanics

International Nuclear Information System (INIS)

De la Pena, L.; Cetto, A.M.

1991-01-01

The material of this article is organized into five sections. In Sect. I the basic characteristics of quantum systems are briefly discussed, with emphasis on their stochastic properties. In Sect. II a version of stochastic quantum mechanics is presented, to conclude that the quantum formalism admits an interpretation in terms of stochastic processes. In Sect. III the elements of stochastic electrodynamics are described, and its possibilities and limitations as a fundamental theory of quantum systems are discussed. Section IV contains a recent reformulation that overcomes the limitations of the theory discussed in the foregoing section. Finally, in Sect. V the theorems of EPR, Von Neumann and Bell are discussed briefly. The material is pedagogically presented and includes an ample list of references, but the details of the derivations are generally omitted. (Author)

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.

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.

Stochastic Erosion of Fractal Structure in Nonlinear Dynamical Systems

Science.gov (United States)

Agarwal, S.; Wettlaufer, J. S.

2014-12-01

We analyze the effects of stochastic noise on the Lorenz-63 model in the chaotic regime to demonstrate a set of general issues arising in the interpretation of data from nonlinear dynamical systems typical in geophysics. The model is forced using both additive and multiplicative, white and colored noise and it is shown that, through a suitable choice of the noise intensity, both additive and multiplicative noise can produce similar dynamics. We use a recently developed measure, histogram distance, to show the similarity between the dynamics produced by additive and multiplicative forcing. This phenomenon, in a nonlinear fractal structure with chaotic dynamics can be explained by understanding how noise affects the Unstable Periodic Orbits (UPOs) of the system. For delta-correlated noise, the UPOs erode the fractal structure. In the presence of memory in the noise forcing, the time scale of the noise starts to interact with the period of some UPO and, depending on the noise intensity, stochastic resonance may be observed. This also explains the mixing in dissipative dynamical systems in presence of white noise; as the fractal structure is smoothed, the decay of correlations is enhanced, and hence the rate of mixing increases with noise intensity.

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)

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.

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)...

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)

Stochastic quantization and topological theories

International Nuclear Information System (INIS)

Fainberg, V.Y.; Subbotin, A.V.; Kuznetsov, A.N.

1992-01-01

In the last two years topological quantum field theories (TQFT) have attached much attention. This paper reports that from the very beginning it was realized that due to a peculiar BRST-like symmetry these models admitted so-called Nicolai mapping: the Nicolai variables, in terms of which actions of the theories become gaussian, are nothing but (anti-) selfduality conditions or their generalizations. This fact became a starting point in the quest of possible stochastic interpretation to topological field theories. The reasons behind were quite simple and included, in particular, the well-known relations between stochastic processes and supersymmetry. The main goal would have been achieved, if it were possible to construct stochastic processes governed by Langevin or Fokker-Planck equations in a real Euclidean time leading to TQFT's path integrals (equivalently: to reformulate TQFTs as non-equilibrium phase dynamics of stochastic processes). Further on, if it would appear that these processes correspond to the stochastic quantization of theories of some definite kind, one could expect (d + 1)-dimensional TQFTs to share some common properties with d-dimensional ones

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.

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)

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.

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.

Characterization of stochastic spatially and spectrally partially coherent electromagnetic pulsed beams

International Nuclear Information System (INIS)

Ding Chaoliang; Lue Baida; Pan Liuzhan

2009-01-01

The unified theory of coherence and polarization proposed by Wolf is extended from stochastic stationary electromagnetic beams to stochastic spatially and spectrally partially coherent electromagnetic pulsed beams. Taking the stochastic electromagnetic Gaussian Schell-model pulsed (GSMP) beam as a typical example of stochastic spatially and spectrally partially coherent electromagnetic pulsed beams, the expressions for the spectral density, spectral degree of polarization and spectral degree of coherence of stochastic electromagnetic GSMP beams propagating in free space are derived. Some special cases are analyzed. The illustrative examples are given and the results are interpreted physically.

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

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.

Parameter allocation of parallel array bistable stochastic resonance and its application in communication systems

International Nuclear Information System (INIS)

Liu Jian; Zhai Qi-Qing; Wang You-Guo; Liu Jin

2016-01-01

In this paper, we propose a parameter allocation scheme in a parallel array bistable stochastic resonance-based communication system (P-BSR-CS) to improve the performance of weak binary pulse amplitude modulated (BPAM) signal transmissions. The optimal parameter allocation policy of the P-BSR-CS is provided to minimize the bit error rate (BER) and maximize the channel capacity (CC) under the adiabatic approximation condition. On this basis, we further derive the best parameter selection theorem in realistic communication scenarios via variable transformation. Specifically, the P-BSR structure design not only brings the robustness of parameter selection optimization, where the optimal parameter pair is not fixed but variable in quite a wide range, but also produces outstanding system performance. Theoretical analysis and simulation results indicate that in the P-BSR-CS the proposed parameter allocation scheme yields considerable performance improvement, particularly in very low signal-to-noise ratio (SNR) environments. (paper)

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)

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

Stochastic mechanics and quantum theory

International Nuclear Information System (INIS)

Goldstein, S.

1987-01-01

Stochastic mechanics may be regarded as both generalizing classical mechanics to processes with intrinsic randomness, as well as providing the sort of detailed description of microscopic events declared impossible under the traditional interpretation of quantum mechanics. It avoids the many conceptual difficulties which arise from the assumption that quantum mechanics, i.e., the wave function, provides a complete description of (microscopic) physical reality. Stochastic mechanics presents a unified treatment of the microscopic and macroscopic domains, in which the process of measurement plays no special physical role and which reduces to Newtonian mechanics in the macroscopic limit

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 goal-oriented error estimation with memory

Science.gov (United States)

Ackmann, Jan; Marotzke, Jochem; Korn, Peter

2017-11-01

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

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.

Interpretation of scrape-off layer profile evolution and first-wall ion flux statistics on JET using a stochastic framework based on fillamentary motion

Science.gov (United States)

Walkden, N. R.; Wynn, A.; Militello, F.; Lipschultz, B.; Matthews, G.; Guillemaut, C.; Harrison, J.; Moulton, D.; Contributors, JET

2017-08-01

This paper presents the use of a novel modelling technique based around intermittent transport due to filament motion, to interpret experimental profile and fluctuation data in the scrape-off layer (SOL) of JET during the onset and evolution of a density profile shoulder. A baseline case is established, prior to shoulder formation, and the stochastic model is shown to be capable of simultaneously matching the time averaged profile measurement as well as the PDF shape and autocorrelation function from the ion-saturation current time series at the outer wall. Aspects of the stochastic model are then varied with the aim of producing a profile shoulder with statistical measurements consistent with experiment. This is achieved through a strong localised reduction in the density sink acting on the filaments within the model. The required reduction of the density sink occurs over a highly localised region with the timescale of the density sink increased by a factor of 25. This alone is found to be insufficient to model the expansion and flattening of the shoulder region as the density increases, which requires additional changes within the stochastic model. An example is found which includes both a reduction in the density sink and filament acceleration and provides a consistent match to the experimental data as the shoulder expands, though the uniqueness of this solution can not be guaranteed. Within the context of the stochastic model, this implies that the localised reduction in the density sink can trigger shoulder formation, but additional physics is required to explain the subsequent evolution of the profile.

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 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.

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.

Perturbation analysis of spontaneous action potential initiation by stochastic ion channels

KAUST Repository

Keener, James P.; Newby, Jay M.

2011-01-01

A stochastic interpretation of spontaneous action potential initiation is developed for the Morris-Lecar equations. Initiation of a spontaneous action potential can be interpreted as the escape from one of the wells of a double well potential

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.

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.;

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.

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

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

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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.

BRS invariant stochastic quantization of Einstein gravity

International Nuclear Information System (INIS)

Nakazawa, Naohito.

1989-11-01

We study stochastic quantization of gravity in terms of a BRS invariant canonical operator formalism. By introducing artificially canonical momentum variables for the original field variables, a canonical formulation of stochastic quantization is proposed in the sense that the Fokker-Planck hamiltonian is the generator of the fictitious time translation. Then we show that there exists a nilpotent BRS symmetry in an enlarged phase space of the first-class constrained systems. The phase space is spanned by the dynamical variables, their canonical conjugate momentum variables, Faddeev-Popov ghost and anti-ghost. We apply the general BRS invariant formulation to stochastic quantization of gravity which is described as a second-class constrained system in terms of a pair of Langevin equations coupled with white noises. It is shown that the stochastic action of gravity includes explicitly the De Witt's type superspace metric which leads to a geometrical interpretation of quantum gravity analogous to nonlinear σ-models. (author)

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

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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.

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.

BRS symmetry in stochastic quantization of the gravitational field

International Nuclear Information System (INIS)

Nakazawa, Naohito.

1989-12-01

We study stochastic quantization of gravity in terms of a BRS invariant canonical operator formalism. By introducing artificially canonical momentum variables for the original field variables, a canonical formulation of stochastic quantization is proposed in a sense that the Fokker-Planck hamiltonian is the generator of the fictitious time translation. Then we show that there exists a nilpotent BRS symmetry in an enlarged phase space for gravity (in general, for the first-class constrained systems). The stochastic action of gravity includes explicitly an unique De Witt's type superspace metric which leads to a geometrical interpretation of quantum gravity analogous to nonlinear σ-models. (author)

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

Statistical and stochastic aspects of the delocalization problem in quantum mechanics

International Nuclear Information System (INIS)

Claverie, P.; Diner, S.

1976-01-01

The space-time behaviour of electrons in atoms and molecules is reviewed. The wave conception of the electron is criticized and the poverty of the non-reductionist attitude is underlined. Further, the two main interpretations of quantum mechanics are recalled: the Copenhagen and the Statistical Interpretations. The meaning and the successes of the Statistical Interpretation are explained and it is shown that it does not solve all problems because quantum mechanics is irreducible to a classical statistical theory. The fluctuation of the particle number and its relationship to loge theory, delocalization and correlation is studied. Finally, different stochastic models for microphysics are reviewed. The markovian Fenyes-Nelson process allows an interpretation of the original heuristic considerations of Schroedinger. Non-markov processes with Schroedinger time evolution are shown to be equivalent to the base state analysis of Feynmann but they are unsatisfactory from a probabilistic point of view. Stochastic electrodynamics is presented as the most satisfactory conception nowadays

Causality Illusion and Overconfidence in Predicting (QuasiStochastic Financial Events

Directory of Open Access Journals (Sweden)

Petr Houdek

2017-03-01

Full Text Available We argue that individuals systematically interpret sequences of events in a  causal manner. The aim of this article is to show that people do so even if they are aware of the stochastic nature of the respective sequence. The bias can explain some anomalous behaviour of investors in financial markets. Small as well as professional investors may illusorily perceive causality of former random success and future yield. Laboratory experiments testing the interpretation of stochastically occurring events in financial designs as well as analyses of real trading data from financial markets confirm that investors indeed interpret (quasirandom events casually; they make incorrect predictions and they egocentrically allocate responsibility for their success. The causality illusion induces overconfidence, inefficient investment and risk seeking. In the conclusion, we discuss factors that may limit effects of the causality illusion and suggest future areas for research.

Agreement in the Interpretation of Magnetic Resonance Images of the Lumbar Spine

International Nuclear Information System (INIS)

Kovacs, F.M.; Royuela, A.; Jensen, T.S.

2009-01-01

Background: Correlation between clinical features and magnetic resonance imaging (MRI) findings is essential in low-back-pain patients. Most previous studies have analyzed concordance in the interpretation of lumbar MRI among a few radiologists who worked together. This may have overestimated concordance. Purpose: To evaluate intra- and interobserver agreement in the interpretation of lumbar MRI performed in an open 0.2T system. Material and Methods: Seven radiologists from two different geographic settings in Spain interpreted the lumbar MRIs of 50 subjects representative of the general Danish population aged 40 years. The radiologists interpreted the images in routine clinical practice, having no knowledge of the clinical and demographic characteristics of the subjects and blinded to their colleagues' assessments. Six of the radiologists evaluated the same MRIs 14 days later, having no knowledge of the previous results. Data on the existence of disc degeneration, high-intensity zones, disc contour, Schmorl nodes, Modic changes, osteophytes, spondylolisthesis, and spinal stenosis were collected in the Nordic Modic Consensus Group Classification form. Intra- and interobserver agreement was analyzed for variables with a prevalence =10% and =90% by means of the kappa statistic. Results: Intra- and interobserver agreement was excellent for variables related to Modic changes, and fair to good for disc contour, high-intensity zones, and Schmorl nodes. The evaluations for disc degeneration and osteophytes were found to have fair to good intraobserver agreement and poor interobserver agreement. The agreement for the evaluations of spondylolisthesis and spinal stenosis was not analyzed because they were observed in <10% of reports. Conclusion: Images from 0.2T MRIs appear to lead to good agreement in the reporting of disc contour, high-intensity zones, Schmorl nodes, and, in particular, Modic changes, suggesting that they can possibly be reliably used for clinical research

Agreement in the Interpretation of Magnetic Resonance Images of the Lumbar Spine

Energy Technology Data Exchange (ETDEWEB)

Kovacs, F.M. (Dept. Cientfico, Fundacin Kovacs, Palma de Majorca (Spain)); Royuela, A. (Spanish Back Pain Research Network, Fundacin Kovacs, Palma de Majorca (Spain)); Jensen, T.S. (Back Research Center, Backcenter Funen, Ringe (Denmark)) (and others)

2009-06-15

Background: Correlation between clinical features and magnetic resonance imaging (MRI) findings is essential in low-back-pain patients. Most previous studies have analyzed concordance in the interpretation of lumbar MRI among a few radiologists who worked together. This may have overestimated concordance. Purpose: To evaluate intra- and interobserver agreement in the interpretation of lumbar MRI performed in an open 0.2T system. Material and Methods: Seven radiologists from two different geographic settings in Spain interpreted the lumbar MRIs of 50 subjects representative of the general Danish population aged 40 years. The radiologists interpreted the images in routine clinical practice, having no knowledge of the clinical and demographic characteristics of the subjects and blinded to their colleagues' assessments. Six of the radiologists evaluated the same MRIs 14 days later, having no knowledge of the previous results. Data on the existence of disc degeneration, high-intensity zones, disc contour, Schmorl nodes, Modic changes, osteophytes, spondylolisthesis, and spinal stenosis were collected in the Nordic Modic Consensus Group Classification form. Intra- and interobserver agreement was analyzed for variables with a prevalence =10% and =90% by means of the kappa statistic. Results: Intra- and interobserver agreement was excellent for variables related to Modic changes, and fair to good for disc contour, high-intensity zones, and Schmorl nodes. The evaluations for disc degeneration and osteophytes were found to have fair to good intraobserver agreement and poor interobserver agreement. The agreement for the evaluations of spondylolisthesis and spinal stenosis was not analyzed because they were observed in <10% of reports. Conclusion: Images from 0.2T MRIs appear to lead to good agreement in the reporting of disc contour, high-intensity zones, Schmorl nodes, and, in particular, Modic changes, suggesting that they can possibly be reliably used for clinical

Plasma transport in stochastic magnetic field caused by vacuum resonant magnetic perturbations at diverted tokamak edge

International Nuclear Information System (INIS)

Park, G.; Chang, C. S.; Joseph, I.; Moyer, R. A.

2010-01-01

A kinetic transport simulation for the first 4 ms of the vacuum resonant magnetic perturbations (RMPs) application has been performed for the first time in realistic diverted DIII-D tokamak geometry [J. Luxon, Nucl. Fusion 42, 614 (2002)], with the self-consistent evaluation of the radial electric field and the plasma rotation. It is found that, due to the kinetic effects, the stochastic parallel thermal transport is significantly reduced when compared to the standard analytic model [A. B. Rechester and M. N. Rosenbluth, Phys. Rev. Lett. 40, 38 (1978)] and the nonaxisymmetric perpendicular radial particle transport is significantly enhanced from the axisymmetric level. These trends agree with recent experimental result trends [T. E. Evans, R. A. Moyer, K. H. Burrell et al., Nat. Phys. 2, 419 (2006)]. It is also found, as a side product, that an artificial local reduction of the vacuum RMP fields in the vicinity of the magnetic separatrix can bring the kinetic simulation results to a more detailed agreement with experimental plasma profiles.

Stochastic time scale for the Universe

International Nuclear Information System (INIS)

Szydlowski, M.; Golda, Z.

1986-01-01

An intrinsic time scale is naturally defined within stochastic gradient dynamical systems. It should be interpreted as a ''relaxation time'' to a local potential minimum after the system has been randomly perturbed. It is shown that for a flat Friedman-like cosmological model this time scale is of order of the age of the Universe. 7 refs. (author)

AGN Accretion Physics in the Time Domain: Survey Cadences, Stochastic Analysis, and Physical Interpretations

Science.gov (United States)

Moreno, Jackeline; Vogeley, Michael S.; Richards, Gordon; O'Brien, John T.; Kasliwal, Vishal

2018-01-01

We present rigorous testing of survey cadences (K2, SDSS, CRTS, & Pan-STARRS) for quasar variability science using a magnetohydrodynamics synthetic lightcurve and the canonical lightcurve from Kepler, Zw 229.15. We explain where the state of the art is in regards to physical interpretations of stochastic models (CARMA) applied to AGN variability. Quasar variability offers a time domain approach of probing accretion physics at the SMBH scale. Evidence shows that the strongest amplitude changes in the brightness of AGN occur on long timescales ranging from months to hundreds of days. These global behaviors can be constrained by survey data despite low sampling resolution. CARMA processes provide a flexible family of models used to interpolate between data points, predict future observations and describe behaviors in a lightcurve. This is accomplished by decomposing a signal into rise and decay timescales, frequencies for cyclic behavior and shock amplitudes. Characteristic timescales may point to length-scales over which a physical process operates such as turbulent eddies, warping or hotspots due to local thermal instabilities. We present the distribution of SDSS Stripe 82 quasars in CARMA parameters space that pass our cadence tests and also explain how the Damped Harmonic Oscillator model, CARMA(2,1), reduces to the Damped Random Walk, CARMA(1,0), given the data in a specific region of the parameter space.

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

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.

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

Directory of Open Access Journals (Sweden)

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.

Stochastic ice stream dynamics.

Science.gov (United States)

Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca

2016-08-09

Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.

Stochastic Averaging and Stochastic Extremum Seeking

CERN Document Server

Liu, Shu-Jun

2012-01-01

Stochastic Averaging and Stochastic Extremum Seeking develops methods of mathematical analysis inspired by the interest in reverse engineering  and analysis of bacterial  convergence by chemotaxis and to apply similar stochastic optimization techniques in other environments. The first half of the text presents significant advances in stochastic averaging theory, necessitated by the fact that existing theorems are restricted to systems with linear growth, globally exponentially stable average models, vanishing stochastic perturbations, and prevent analysis over infinite time horizon. The second half of the text introduces stochastic extremum seeking algorithms for model-free optimization of systems in real time using stochastic perturbations for estimation of their gradients. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton). The design of algorithms...

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.

Stochastic kinetics

International Nuclear Information System (INIS)

Colombino, A.; Mosiello, R.; Norelli, F.; Jorio, V.M.; Pacilio, N.

1975-01-01

A nuclear system kinetics is formulated according to a stochastic approach. The detailed probability balance equations are written for the probability of finding the mixed population of neutrons and detected neutrons, i.e. detectrons, at a given level for a given instant of time. Equations are integrated in search of a probability profile: a series of cases is analyzed through a progressive criterium. It tends to take into account an increasing number of physical processes within the chosen model. The most important contribution is that solutions interpret analytically experimental conditions of equilibrium (moise analysis) and non equilibrium (pulsed neutron measurements, source drop technique, start up procedures)

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

Bidirectional Classical Stochastic Processes with Measurements and Feedback

Science.gov (United States)

Hahne, G. E.

2005-01-01

A measurement on a quantum system is said to cause the "collapse" of the quantum state vector or density matrix. An analogous collapse occurs with measurements on a classical stochastic process. This paper addresses the question of describing the response of a classical stochastic process when there is feedback from the output of a measurement to the input, and is intended to give a model for quantum-mechanical processes that occur along a space-like reaction coordinate. The classical system can be thought of in physical terms as two counterflowing probability streams, which stochastically exchange probability currents in a way that the net probability current, and hence the overall probability, suitably interpreted, is conserved. The proposed formalism extends the . mathematics of those stochastic processes describable with linear, single-step, unidirectional transition probabilities, known as Markov chains and stochastic matrices. It is shown that a certain rearrangement and combination of the input and output of two stochastic matrices of the same order yields another matrix of the same type. Each measurement causes the partial collapse of the probability current distribution in the midst of such a process, giving rise to calculable, but non-Markov, values for the ensuing modification of the system's output probability distribution. The paper concludes with an analysis of a classical probabilistic version of the so-called grandfather paradox.

Stochastic Spectral Descent for Discrete Graphical Models

International Nuclear Information System (INIS)

Carlson, David; Hsieh, Ya-Ping; Collins, Edo; Carin, Lawrence; Cevher, Volkan

2015-01-01

Interest in deep probabilistic graphical models has in-creased in recent years, due to their state-of-the-art performance on many machine learning applications. Such models are typically trained with the stochastic gradient method, which can take a significant number of iterations to converge. Since the computational cost of gradient estimation is prohibitive even for modestly sized models, training becomes slow and practically usable models are kept small. In this paper we propose a new, largely tuning-free algorithm to address this problem. Our approach derives novel majorization bounds based on the Schatten- norm. Intriguingly, the minimizers of these bounds can be interpreted as gradient methods in a non-Euclidean space. We thus propose using a stochastic gradient method in non-Euclidean space. We both provide simple conditions under which our algorithm is guaranteed to converge, and demonstrate empirically that our algorithm leads to dramatically faster training and improved predictive ability compared to stochastic gradient descent for both directed and undirected graphical models.

Narrow dibaryon resonances

International Nuclear Information System (INIS)

Kajdalov, A.B.

1986-01-01

Experimental data on np interactions indicating to existence of narrow resonances in pp-system are discussed. Possible theoretical interpretations of these resonances are given. Experimental characteristics of the dibaryon resonances with isospin I=2 are considered

Stochastic processes and applications diffusion processes, the Fokker-Planck and Langevin equations

CERN Document Server

Pavliotis, Grigorios A

2014-01-01

This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated.                 The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to eq...

Performance investigation of stochastic resonance in bistable systems with time-delayed feedback and three types of asymmetries

Science.gov (United States)

Liu, Jian; Wang, Youguo

2018-03-01

The simultaneous influence of potential asymmetries and time-delayed feedback on stochastic resonance (SR) subject to both periodic force and additive Gaussian white noise is investigated by using two-state theory and small-delay approximation, where three types of asymmetries include well-depth, well-width, and both well-depth and well-width asymmetries, respectively. The asymmetric types and time-delayed feedback determine the behaviors of SR, especially output signal-to-noise ratio (SNR) peaks, optimal additive noise intensity and feedback intensity. Moreover, the largest SNR in asymmetric SR is found to be relatively larger than symmetric one in some cases, whereas in other cases the symmetric SR is superior to asymmetric one, which is of dependence on time delay and feedback intensity. In addition, the SR with well-width asymmetry can suppress stronger noise than that with well-depth asymmetry under the action of same time delay, which is beneficial to weak signal detection.

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)

Stochastic motion due to a single wave in a magnetoplasma

International Nuclear Information System (INIS)

Smith, G.R.

1979-01-01

A single electrostatic wave in a magnetoplasma causes stochastic ion motion in several physically different situations. Various magnetic fields (uniform, tokamak, and mirror) and various propagation angles with respect to the field have been studied. A brief review of this work shows that all situations can be understood using the concept of overlapping resonances. Analytical calculations of the wave amplitude necessary for stochasticity have been carried out in some cases and compared with computer and laboratory experiments. In the case of an axisymmetric mirror field the calculations predict stochastic motion of ions with energy below a threshold that depends weakly on the wave amplitude and on the scale lengths of the magnetic field. Studies with an azimuthally asymmetric field show that the asymmetry causes substantial changes in the motion of some ions

Energy harvesting by dynamic unstability and internal resonance for piezoelectric beam

Energy Technology Data Exchange (ETDEWEB)

Lan, Chunbo; Qin, Weiyang, E-mail: 353481781@qq.com; Deng, Wangzheng [Department of Engineering Mechanics, Northwestern Polytechnical University, Xi' an 710072 (China)

2015-08-31

We investigated the energy harvesting of a vertical beam with tip mass under vertical excitations. We applied dynamic unstability and internal resonance to improve the efficiency of harvesting. The experiments of harmonic excitation were carried out. Results show that for the beam there exist internal resonances in the dynamically unstable and the buckling bistable cases. The dynamic unstability is a determinant for strong internal resonance or mode coupling, which can be used to create a large output from piezoelectric patches. Then, the experiments of stochastic excitation were carried out. Results prove that the internal resonance or mode coupling can transfer the excitation energy to the low order modes, mainly the first and the second one. This can bring about a large output voltage. For a stochastic excitation, it is proved that there is an optimal weight of tip mass for realizing internal resonance and producing large outputs.

Electricity Market Stochastic Dynamic Model and Its Mean Stability Analysis

Directory of Open Access Journals (Sweden)

Zhanhui Lu

2014-01-01

Full Text Available Based on the deterministic dynamic model of electricity market proposed by Alvarado, a stochastic electricity market model, considering the random nature of demand sides, is presented in this paper on the assumption that generator cost function and consumer utility function are quadratic functions. The stochastic electricity market model is a generalization of the deterministic dynamic model. Using the theory of stochastic differential equations, stochastic process theory, and eigenvalue techniques, the determining conditions of the mean stability for this electricity market model under small Gauss type random excitation are provided and testified theoretically. That is, if the demand elasticity of suppliers is nonnegative and the demand elasticity of consumers is negative, then the stochastic electricity market model is mean stable. It implies that the stability can be judged directly by initial data without any computation. Taking deterministic electricity market data combined with small Gauss type random excitation as numerical samples to interpret random phenomena from a statistical perspective, the results indicate the conclusions above are correct, valid, and practical.

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

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.

Stochastic background search correlating ALLEGRO with LIGO engineering data

International Nuclear Information System (INIS)

Whelan, John T; Daw, Edward; Heng, Ik Siong; McHugh, Martin P; Lazzarini, Albert

2003-01-01

We describe the role of correlation measurements between the LIGO interferometer in Livingston, LA, and the ALLEGRO resonant bar detector in Baton Rouge, LA, in searches for a stochastic background of gravitational waves. Such measurements provide a valuable complement to correlations between interferometers at the two LIGO sites, since they are sensitive in a different, higher, frequency band. Additionally, the variable orientation of the ALLEGRO detector provides a means to distinguish gravitational wave correlations from correlated environmental noise. We describe the analysis underway to set a limit on the strength of a stochastic background at frequencies near 900 Hz using ALLEGRO data and data from LIGO's E7 Engineering Run

Combined action of time-delay and colored cross-associated multiplicative and additive noises on stability and stochastic resonance for a stochastic metapopulation system

Science.gov (United States)

Wang, Kang-Kang; Zong, De-Cai; Wang, Ya-Jun; Li, Sheng-Hong

2016-05-01

In this paper, the transition between the stable state of a big density and the extinction state and stochastic resonance (SR) for a time-delayed metapopulation system disturbed by colored cross-correlated noises are investigated. By applying the fast descent method, the small time-delay approximation and McNamara and Wiesenfeld's SR theory, we investigate the impacts of time-delay, the multiplicative, additive noises and colored cross-correlated noise on the SNR and the shift between the two states of the system. Numerical results show that the multiplicative, additive noises and time-delay can all speed up the transition from the stable state to the extinction state, while the correlation noise and its correlation time can slow down the extinction process of the population system. With respect to SNR, the multiplicative noise always weakens the SR effect, while noise correlation time plays a dual role in motivating the SR phenomenon. Meanwhile, time-delay mainly plays a negative role in stimulating the SR phenomenon. Conversely, it could motivate the SR effect to increase the strength of the cross-correlation noise in the SNR-β plot, while the increase of additive noise intensity will firstly excite SR, and then suppress the SR effect.

Structure and properties of Hughston's stochastic extension of the Schroedinger equation

International Nuclear Information System (INIS)

Adler, Stephen L.; Horwitz, Lawrence P.

2000-01-01

Hughston has recently proposed a stochastic extension of the Schroedinger equation, expressed as a stochastic differential equation on projective Hilbert space. We derive new projective Hilbert space identities, which we use to give a general proof that Hughston's equation leads to state vector collapse to energy eigenstates, with collapse probabilities given by the quantum mechanical probabilities computed from the initial state. We discuss the relation of Hughston's equation to earlier work on norm-preserving stochastic equations, and show that Hughston's equation can be written as a manifestly unitary stochastic evolution equation for the pure state density matrix. We discuss the behavior of systems constructed as direct products of independent subsystems, and briefly address the question of whether an energy-based approach, such as Hughston's, suffices to give an objective interpretation of the measurement process in quantum mechanics. (c) 2000 American Institute of Physics

Markov Chain Models for Stochastic Behavior in Resonance Overlap Regions

Science.gov (United States)

McCarthy, Morgan; Quillen, Alice

2018-01-01

We aim to predict lifetimes of particles in chaotic zoneswhere resonances overlap. A continuous-time Markov chain model isconstructed using mean motion resonance libration timescales toestimate transition times between resonances. The model is applied todiffusion in the co-rotation region of a planet. For particles begunat low eccentricity, the model is effective for early diffusion, butnot at later time when particles experience close encounters to the planet.

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

Single-spin stochastic optical reconstruction microscopy.

Science.gov (United States)

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

2014-10-14

We experimentally demonstrate precision addressing of single-quantum emitters by combined optical microscopy and spin resonance techniques. To this end, we use 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) measurements on NV spins. This allows the assignment of spin resonance spectra to individual NV center locations with nanometer-scale resolution and thus further improves spatial discrimination. For example, we resolved formerly indistinguishable emitters by their spectra. Furthermore, ODMR spectra contain metrology information allowing for sub-diffraction-limit sensing of, for instance, magnetic or electric fields with inherently parallel data acquisition. As an example, we have detected nuclear spins with nanometer-scale precision. Finally, we give prospects of how this technique can evolve into a fully parallel quantum sensor for nanometer resolution imaging of delocalized quantum correlations.

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

Thermal interpretation of infrared dynamics in de Sitter

Energy Technology Data Exchange (ETDEWEB)

Rigopoulos, Gerasimos, E-mail: gerasimos.rigopoulos@ncl.ac.uk [School of Mathematics and Statistics, Newcastle University, Herschel Building, Newcastle upon Tyne, NE1 7RU U.K. (United Kingdom)

2016-07-01

The infrared dynamics of a light, minimally coupled scalar field in de Sitter spacetime with Ricci curvature R = 12 H {sup 2}, averaged over horizon sized regions of physical volume V {sub H} = (4π/3)(1/ H ){sup 3}, can be interpreted as Brownian motion in a medium with de Sitter temperature T {sub DS} = h-bar H /2π. We demonstrate this by directly deriving the effective action of scalar field fluctuations with wavelengths larger than the de Sitter curvature radius and generalizing Starobinsky's seminal results on stochastic inflation. The effective action describes stochastic dynamics and the fluctuating force drives the field to an equilibrium characterized by a thermal Gibbs distribution at temperature T {sub DS} which corresponds to a de Sitter invariant state. Hence, approach towards this state can be interpreted as thermalization. We show that the stochastic kinetic energy of the coarse-grained description corresponds to the norm of ∂{sub μ}φ and takes a well defined value per horizon volume ½((∇φ){sup 2}) = − ½ T {sub DS}/ V {sub H} . This approach allows for the non-perturbative computation of the de Sitter invariant stress energy tensor ( T {sub μν}) for an arbitrary scalar potential.

Excited states in stochastic electrodynamics

International Nuclear Information System (INIS)

Franca, H.M.; Marshall, T.W.

1987-12-01

It is shown that the set of Wigner functions associated with the excited states of the harmonic oscillator constitute a complete set of functions over the phase space. An arbitraty distribution can be expanded in terms of these Wigner functions. By studying the time evolution, according to Stochastic Electrodynamics, of the expansion coefficients, becomes feasible to separate explicity the contributionsof the radiative reaction and the vaccuum field to the Einsten. A coefficients for this system. A simple semiclassical explanation of the Weisskopf-Heitler phenomenon in resonance fluorescence is also supplied. (author) [pt

Stochastic inflation: Quantum phase-space approach

International Nuclear Information System (INIS)

Habib, S.

1992-01-01

In this paper a quantum-mechanical phase-space picture is constructed for coarse-grained free quantum fields in an inflationary universe. The appropriate stochastic quantum Liouville equation is derived. Explicit solutions for the phase-space quantum distribution function are found for the cases of power-law and exponential expansions. The expectation values of dynamical variables with respect to these solutions are compared to the corresponding cutoff regularized field-theoretic results (we do not restrict ourselves only to left-angle Φ 2 right-angle). Fair agreement is found provided the coarse-graining scale is kept within certain limits. By focusing on the full phase-space distribution function rather than a reduced distribution it is shown that the thermodynamic interpretation of the stochastic formalism faces several difficulties (e.g., there is no fluctuation-dissipation theorem). The coarse graining does not guarantee an automatic classical limit as quantum correlations turn out to be crucial in order to get results consistent with standard quantum field theory. Therefore, the method does not by itself constitute an explanation of the quantum to classical transition in the early Universe. In particular, we argue that the stochastic equations do not lead to decoherence

On the Physical Interpretation of the Saleh-Valenzuela Model and the definition of its power delay profiles

NARCIS (Netherlands)

Meijerink, Arjan; Molisch, Andreas F.

2014-01-01

The physical motivation and interpretation of the stochastic propagation channel model of Saleh and Valenzuela are discussed in detail. This motivation mainly relies on assumptions on the stochastic properties of the positions of transmitter, receiver and scatterers in the propagation environment,

Efficacy of Stochastic Vestibular Stimulation to Improve Locomotor Performance in a Discordant Sensory Environment

Science.gov (United States)

Temple, D. R.; De Dios, Y. E.; Layne, C. S.; Bloomberg, J. J.; Mulavara, A. P.

2016-01-01

Astronauts exposed to microgravity face sensorimotor challenges incurred when readapting to a gravitational environment. Sensorimotor Adaptability (SA) training has been proposed as a countermeasure to improve locomotor performance during re-adaptation, and it is suggested that the benefits of SA training may be further enhanced by improving detection of weak sensory signals via mechanisms such as stochastic resonance when a non-zero level of stochastic white noise based electrical stimulation is applied to the vestibular system (stochastic vestibular stimulation, SVS). The purpose of this study was to test the efficacy of using SVS to improve short-term adaptation in a sensory discordant environment during performance of a locomotor task.

Stochastic background search correlating ALLEGRO with LIGO engineering data

Energy Technology Data Exchange (ETDEWEB)

Whelan, John T [Department of Physics, Loyola University, New Orleans, Louisiana 70118 (United States); Daw, Edward [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Heng, Ik Siong [Max-Planck-Institut fuer Gravitationsphysik, Albert-Einstein-Institut, Aussenstelle Hannover, D-30167 Hannover (Germany); McHugh, Martin P [Department of Physics, Loyola University, New Orleans, Louisiana 70118 (United States); Lazzarini, Albert [LIGO Laboratory, California Institute of Technology, Pasadena, CA 91125 (United States)

2003-09-07

We describe the role of correlation measurements between the LIGO interferometer in Livingston, LA, and the ALLEGRO resonant bar detector in Baton Rouge, LA, in searches for a stochastic background of gravitational waves. Such measurements provide a valuable complement to correlations between interferometers at the two LIGO sites, since they are sensitive in a different, higher, frequency band. Additionally, the variable orientation of the ALLEGRO detector provides a means to distinguish gravitational wave correlations from correlated environmental noise. We describe the analysis underway to set a limit on the strength of a stochastic background at frequencies near 900 Hz using ALLEGRO data and data from LIGO's E7 Engineering Run.

Trapping in stochastic mechanics and applications to covers of clouds and radiation belts

International Nuclear Information System (INIS)

Albeverio, S.; Blanchard, P.; Combe, P.; Rodriguez, R.; Sirugue, M.; Sirugue-Collin, M.

1984-11-01

It is possible to assign a stochastic acceleration to conservative stochastic diffusion processes. As a basic assumption, this stochastic acceleration is set equal to the deterministic smooth component of the external force acting on the particle, whereas the influences of the remainder is modelled by a diffusion coefficient. In this paper, we shall try to see whether it can account for the observation in two cases: the cover of clouds of planets and the radiation belts in the planetary magnetic field. We describe the basic properties of Newtonian Diffusion Stochastic Processes and indicate their connection with Schroedinger-like equations. Furthermore we give a heuristic interpretation of the nodal surfaces as impenetrable barriers for Newtonian Stochastic Diffusion Processes. The possible applications to the observed average cloud covering in the planetary atmosphere are presented we discuss the radiation belts (Van Allen Belts) along the previous ideas

A Stochastic model for two-station hydraulics exhibiting transient impact

DEFF Research Database (Denmark)

Jacobsen, Judith L.; Madsen, Henrik; Harremoës, Poul

1997-01-01

The objective of the paper is to interpret data on water level variation in a river affected by overflow from a sewer system during rain. The simplest possible, hydraulic description is combined with stochastic methods for data analysis and model parameter estimation. This combination...

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.

Inter-Observer Agreement on Diffusion-Weighted Magnetic Resonance Imaging Interpretation for Diagnosis of Acute Ischemic Stroke Among Emergency Physicians

Directory of Open Access Journals (Sweden)

Deniz ORAY

2015-06-01

Full Text Available SUMMARY: Objectives: Diffusion-weighted magnetic resonance imaging (DW-MRI is a highly sensitive tool for the detection of early ischemic stroke and is excellent at detecting small and early infarcts. Nevertheless, conflict may arise and judgments may differ among different interpreters. Inter-observer variability shows the systematic difference among different observers and is expressed as the kappa (Κ coefficient. In this study, we aimed to determinate the inter-observer variability among emergency physicians in the use of DW-MRI for the diagnosis of acute ischemic stroke. Methods: Cranial DW-MRI images of 50 patients were interpreted in this retrospective observational cross-sectional study. Patients who were submitted to DW-MRI imaging for a suspected acute ischemic stroke were included in the study, unless the scans were ordered by any of the reviewers or they were absent in the system. The scans were blindly and randomly interpreted by four emergency physicians. Inter-observer agreement between reviewers was evaluated using Fleiss’ Κ statistics. Results: The mean kappa value for high signal on diffusion-weighted images (DWI and for reduction on apparent diffusion coefficient (ADC were substantial (k=0.67 and moderate (k=0.60 respectively. The correlation for detection of the presence of ischemia and location was substantial (k: 0.67. There were 18 false-positive and 4 false-negative evaluations of DWI, 15 false positive and 8 false-negative evaluations of ADC. Conclusions: Our data suggest that DW-MRI is reliable in screening for ischemic stroke when interpreted by emergency physicians in the emergency department. The levels of stroke identification and variability show that emergency physicians may have an acceptable level of agreement. Key words: Emergency department, diffusion weighted magnetic resonance imaging, inter-observer agreement, ischemic stroke

Electron heat transport in stochastic magnetic layer

International Nuclear Information System (INIS)

Becoulet, M.; Ghendrih, Ph.; Capes, H.; Grosman, A.

1999-06-01

Progress in the theoretical understanding of the local behaviour of the temperature field in ergodic layer was done in the framework of quasi-linear approach but this quasi-linear theory was not complete since the resonant modes coupling (due to stochasticity) was neglected. The stochastic properties of the magnetic field in the ergodic zone are now taken into account by a non-linear coupling of the temperature modes. The three-dimension heat transfer modelling in the ergodic-divertor configuration is performed by quasi-linear (ERGOT1) and non-linear (ERGOT2) numerical codes. The formalism and theoretical basis of both codes are presented. The most important effect that can be simulated with non-linear code is the averaged temperature profile flattening that occurs in the ergodic zone and the barrier creation that appears near the separatrix during divertor operation. (A.C.)

Moment Lyapunov Exponent and Stochastic Stability of Binary Airfoil under Combined Harmonic and Non-Gaussian Colored Noise Excitations

Science.gov (United States)

Hu, D. L.; Liu, X. B.

Both periodic loading and random forces commonly co-exist in real engineering applications. However, the dynamic behavior, especially dynamic stability of systems under parametric periodic and random excitations has been reported little in the literature. In this study, the moment Lyapunov exponent and stochastic stability of binary airfoil under combined harmonic and non-Gaussian colored noise excitations are investigated. The noise is simplified to an Ornstein-Uhlenbeck process by applying the path-integral method. Via the singular perturbation method, the second-order expansions of the moment Lyapunov exponent are obtained, which agree well with the results obtained by the Monte Carlo simulation. Finally, the effects of the noise and parametric resonance (such as subharmonic resonance and combination additive resonance) on the stochastic stability of the binary airfoil system are discussed.

Calibration of the ALLEGRO resonant detector

Energy Technology Data Exchange (ETDEWEB)

McHugh, Martin P [Department of Physics, Loyola University, New Orleans, Louisiana 70118 (United States); Johnson, Warren W [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Hamilton, William O [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Hanson, Jonathan [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Heng, Ik Siong [University of Glasgow, Glasgow G12 8QQ (United Kingdom); McNeese, Daniel [Department of Physics, Loyola University, New Orleans, Louisiana 70118 (United States); Miller, Phillip [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Nettles, Damon [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Weaver, Jordan [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Zhang Ping [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States)

2005-09-21

We describe a method for calibrating the ALLEGRO resonant detector. The resulting response function can be used to transform the observed data backwards to gravitational strain data. These data are the input to a cross-correlation analysis to search for stochastic gravitational waves.

Calibration of the ALLEGRO resonant detector

International Nuclear Information System (INIS)

McHugh, Martin P; Johnson, Warren W; Hamilton, William O; Hanson, Jonathan; Heng, Ik Siong; McNeese, Daniel; Miller, Phillip; Nettles, Damon; Weaver, Jordan; Zhang Ping

2005-01-01

We describe a method for calibrating the ALLEGRO resonant detector. The resulting response function can be used to transform the observed data backwards to gravitational strain data. These data are the input to a cross-correlation analysis to search for stochastic gravitational waves

Stochastic mechanics of mixed states

International Nuclear Information System (INIS)

Jaekel, M.T.; Pignon, D.

1984-01-01

Nelson's stochastic interpretation of quantum mechanics is extended from the case of pure states to that of mixed states. It is shown that a pure probabilistic formalism, which applies the Newton-Nelson Law to the initial position and velocity distributions, does not reproduce the time evolution predicted by quantum mechanics. In order to recover the latter, a new notion must be introduced, that of pure quantum states, over which the mixture has to be decomposed, and which then satisfy the Newton-Nelson Law independently. (author)

Suppression of large edge-localized modes in high-confinement DIII-D plasmas with a stochastic magnetic boundary.

Science.gov (United States)

Evans, T E; Moyer, R A; Thomas, P R; Watkins, J G; Osborne, T H; Boedo, J A; Doyle, E J; Fenstermacher, M E; Finken, K H; Groebner, R J; Groth, M; Harris, J H; La Haye, R J; Lasnier, C J; Masuzaki, S; Ohyabu, N; Pretty, D G; Rhodes, T L; Reimerdes, H; Rudakov, D L; Schaffer, M J; Wang, G; Zeng, L

2004-06-11

A stochastic magnetic boundary, produced by an applied edge resonant magnetic perturbation, is used to suppress most large edge-localized modes (ELMs) in high confinement (H-mode) plasmas. The resulting H mode displays rapid, small oscillations with a bursty character modulated by a coherent 130 Hz envelope. The H mode transport barrier and core confinement are unaffected by the stochastic boundary, despite a threefold drop in the toroidal rotation. These results demonstrate that stochastic boundaries are compatible with H modes and may be attractive for ELM control in next-step fusion tokamaks.

Stochastic Resonance in Electron Transfer Oscillations of Extended Viologen

Czech Academy of Sciences Publication Activity Database

Hromadová, Magdaléna; Valášek, Michal; Fanelli, N.; Randriamahazaka, N.; Pospíšil, Lubomír

2014-01-01

Roč. 118, č. 17 (2014), s. 9066-9072 ISSN 1932-7447 R&D Projects: GA ČR GA13-19213S; GA ČR(CZ) GA14-05180S Grant - others:Rada Programu interní porpory projektů mezinárodní spolupráce AV ČR M200401202 Program:M Institutional support: RVO:61388955 ; RVO:61388963 Keywords : Circuit resonance * Harmonic analysis * Magnetic resonance Subject RIV: CG - Electrochemistry Impact factor: 4.772, year: 2014

Competition model for aperiodic stochastic resonance in a Fitzhugh-Nagumo model of cardiac sensory neurons.

Science.gov (United States)

Kember, G C; Fenton, G A; Armour, J A; Kalyaniwalla, N

2001-04-01

Regional cardiac control depends upon feedback of the status of the heart from afferent neurons responding to chemical and mechanical stimuli as transduced by an array of sensory neurites. Emerging experimental evidence shows that neural control in the heart may be partially exerted using subthreshold inputs that are amplified by noisy mechanical fluctuations. This amplification is known as aperiodic stochastic resonance (ASR). Neural control in the noisy, subthreshold regime is difficult to see since there is a near absence of any correlation between input and the output, the latter being the average firing (spiking) rate of the neuron. This lack of correlation is unresolved by traditional energy models of ASR since these models are unsuitable for identifying "cause and effect" between such inputs and outputs. In this paper, the "competition between averages" model is used to determine what portion of a noisy, subthreshold input is responsible, on average, for the output of sensory neurons as represented by the Fitzhugh-Nagumo equations. A physiologically relevant conclusion of this analysis is that a nearly constant amount of input is responsible for a spike, on average, and this amount is approximately independent of the firing rate. Hence, correlation measures are generally reduced as the firing rate is lowered even though neural control under this model is actually unaffected.

Stochastic Analysis 2010

CERN Document Server

Crisan, Dan

2011-01-01

"Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa

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

Science.gov (United States)

Shi, Pei-Ming; Li, Qun; Han, Dong-Ying

2017-06-01

This paper investigates a new asymmetric bistable model driven by correlated multiplicative colored noise and additive white noise. The mean first-passage time (MFPT) and the signal-to-noise ratio (SNR) as the indexes of evaluating the model are researched. Based on the two-state theory and the adiabatic approximation theory, the expressions of MFPT and SNR have been obtained for the asymmetric bistable system driven by a periodic signal, correlated multiplicative colored noise and additive noise. Simulation results show that it is easier to generate stochastic resonance (SR) to adjust the intensity of correlation strength λ. Meanwhile, the decrease of asymmetric coefficient r2 and the increase of noise intensity are beneficial to realize the transition between the two steady states in the system. At the same time, the twice SR phenomena can be observed by adjusting additive white noise and correlation strength. The influence of asymmetry of potential function on the MFPTs in two different directions is different.

High-Resolution Replication Profiles Define the Stochastic Nature of Genome Replication Initiation and Termination

Directory of Open Access Journals (Sweden)

Michelle Hawkins

2013-11-01

Full Text Available Eukaryotic genome replication is stochastic, and each cell uses a different cohort of replication origins. We demonstrate that interpreting high-resolution Saccharomyces cerevisiae genome replication data with a mathematical model allows quantification of the stochastic nature of genome replication, including the efficiency of each origin and the distribution of termination events. Single-cell measurements support the inferred values for stochastic origin activation time. A strain, in which three origins were inactivated, confirmed that the distribution of termination events is primarily dictated by the stochastic activation time of origins. Cell-to-cell variability in origin activity ensures that termination events are widely distributed across virtually the whole genome. We propose that the heterogeneity in origin usage contributes to genome stability by limiting potentially deleterious events from accumulating at particular loci.

The stochastic resonance for the incidence function model of metapopulation

Science.gov (United States)

Li, Jiang-Cheng; Dong, Zhi-Wei; Zhou, Ruo-Wei; Li, Yun-Xian; Qian, Zhen-Wei

2017-06-01

A stochastic model with endogenous and exogenous periodicities is proposed in this paper on the basis of metapopulation dynamics to model the crop yield losses due to pests and diseases. The rationale is that crop yield losses occur because the physiology of the growing crop is negatively affected by pests and diseases in a dynamic way over time as crop both grows and develops. Metapopulation dynamics can thus be used to model the resultant crop yield losses. The stochastic metapopulation process is described by using the Simplified Incidence Function model (IFM). Compared to the original IFMs, endogenous and exogenous periodicities are considered in the proposed model to handle the cyclical patterns observed in pest infestations, diseases epidemics, and exogenous affecting factors such as temperature and rainfalls. Agricultural loss data in China are used to fit the proposed model. Experimental results demonstrate that: (1) Model with endogenous and exogenous periodicities is a better fit; (2) When the internal system fluctuations and external environmental fluctuations are negatively correlated, EIL or the cost of loss is monotonically increasing; when the internal system fluctuations and external environmental fluctuations are positively correlated, an outbreak of pests and diseases might occur; (3) If the internal system fluctuations and external environmental fluctuations are positively correlated, an optimal patch size can be identified which will greatly weaken the effects of external environmental influence and hence inhibit pest infestations and disease epidemics.

Equivalent-circuit model for the thickness-shear mode resonator with a viscoelastic film near film resonance.

Science.gov (United States)

Martin, S J; Bandey, H L; Cernosek, R W; Hillman, A R; Brown, M J

2000-01-01

We derive a lumped-element, equivalent-circuit model for the thickness-shear mode (TSM) resonator with a viscoelastic film. This modified Butterworth-Van Dyke model includes in the motional branch a series LCR resonator, representing the quartz resonance, and a parallel LCR resonator, representing the film resonance. This model is valid in the vicinity of film resonance, which occurs when the acoustic phase shift across the film is an odd multiple of pi/2 rad. For low-loss films, this model accurately predicts the frequency changes and damping that arise at resonance and is a reasonable approximation away from resonance. Elements of the parallel LCR resonator are explicitly related to film properties and can be interpreted in terms of elastic energy storage and viscous power dissipation. The model leads to a simple graphical interpretation of the coupling between the quartz and film resonances and facilitates understanding of the resulting responses. These responses are compared with predictions from the transmission-line and Sauerbrey models.

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.

Improving Sensorimotor Function and Adaptation using Stochastic Vestibular Stimulation

Science.gov (United States)

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

2014-01-01

Astronauts experience sensorimotor changes during adaption to G-transitions that occur when entering and exiting microgravity. Post space flight, these sensorimotor disturbances can include postural and gait instability, visual performance changes, manual control disruptions, spatial disorientation, and motion sickness, all of which can hinder the operational capabilities of the astronauts. Crewmember safety would be significantly increased if sensorimotor changes brought on by gravitational changes could be mitigated and adaptation could be facilitated. The goal of this research is to investigate and develop the use of electrical stochastic vestibular stimulation (SVS) as a countermeasure to augment sensorimotor function and facilitate adaptation. For this project, SVS will be applied via electrodes on the mastoid processes at imperceptible amplitude levels. We hypothesize that SVS will improve sensorimotor performance through the phenomena of stochastic resonance, which occurs when the response of a nonlinear system to a weak input signal is optimized by the application of a particular nonzero level of noise. In line with the theory of stochastic resonance, a specific optimal level of SVS will be found and tested for each subject [1]. Three experiments are planned to investigate the use of SVS in sensory-dependent tasks and performance. The first experiment will aim to demonstrate stochastic resonance in the vestibular system through perception based motion recognition thresholds obtained using a 6-degree of freedom Stewart platform in the Jenks Vestibular Laboratory at Massachusetts Eye and Ear Infirmary. A range of SVS amplitudes will be applied to each subject and the subjectspecific optimal SVS level will be identified as that which results in the lowest motion recognition threshold, through previously established, well developed methods [2,3,4]. The second experiment will investigate the use of optimal SVS in facilitating sensorimotor adaptation to system

Electrical noise modulates perception of electrical pulses in humans: sensation enhancement via stochastic resonance.

Science.gov (United States)

Iliopoulos, Fivos; Nierhaus, Till; Villringer, Arno

2014-03-01

Although noise is usually considered to be harmful for signal detection and information transmission, stochastic resonance (SR) describes the counterintuitive phenomenon of noise enhancing the detection and transmission of weak input signals. In mammalian sensory systems, SR-related phenomena may arise both in the peripheral and the central nervous system. Here, we investigate behavioral SR effects of subliminal electrical noise stimulation on the perception of somatosensory stimuli in humans. We compare the likelihood to detect near-threshold pulses of different intensities applied on the left index finger during presence vs. absence of subliminal noise on the same or an adjacent finger. We show that (low-pass) noise can enhance signal detection when applied on the same finger. This enhancement is strong for near-threshold pulses below the 50% detection threshold and becomes stronger when near-threshold pulses are applied as brief trains. The effect reverses at pulse intensities above threshold, especially when noise is replaced by subliminal sinusoidal stimulation, arguing for a peripheral direct current addition. Unfiltered noise applied on longer pulses enhances detection of all pulse intensities. Noise applied to an adjacent finger has two opposing effects: an inhibiting effect (presumably due to lateral inhibition) and an enhancing effect (most likely due to SR in the central nervous system). In summary, we demonstrate that subliminal noise can significantly modulate detection performance of near-threshold stimuli. Our results indicate SR effects in the peripheral and central nervous system.

Stochastic theory of nonequilibrium steady states and its applications. Part I

International Nuclear Information System (INIS)

Zhang Xuejuan; Qian Hong; Qian Min

2012-01-01

The concepts of equilibrium and nonequilibrium steady states are introduced in the present review as mathematical concepts associated with stationary Markov processes. For both discrete stochastic systems with master equations and continuous diffusion processes with Fokker–Planck equations, the nonequilibrium steady state (NESS) is characterized in terms of several key notions which are originated from nonequilibrium physics: time irreversibility, breakdown of detailed balance, free energy dissipation, and positive entropy production rate. After presenting this NESS theory in pedagogically accessible mathematical terms that require only a minimal amount of prerequisites in nonlinear differential equations and the theory of probability, it is applied, in Part I, to two widely studied problems: the stochastic resonance (also known as coherent resonance) and molecular motors (also known as Brownian ratchet). Although both areas have advanced rapidly on their own with a vast amount of literature, the theory of NESS provides them with a unifying mathematical foundation. Part II of this review contains applications of the NESS theory to processes from cellular biochemistry, ranging from enzyme catalyzed reactions, kinetic proofreading, to zeroth-order ultrasensitivity.

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.

Stochastic and non-stochastic effects - a conceptual analysis

International Nuclear Information System (INIS)

Karhausen, L.R.

1980-01-01

The attempt to divide radiation effects into stochastic and non-stochastic effects is discussed. It is argued that radiation or toxicological effects are contingently related to radiation or chemical exposure. Biological effects in general can be described by general laws but these laws never represent a necessary connection. Actually stochastic effects express contingent, or empirical, connections while non-stochastic effects represent semantic and non-factual connections. These two expressions stem from two different levels of discourse. The consequence of this analysis for radiation biology and radiation protection is discussed. (author)

On Resonant Heating Below the Cyclotron Frequency

International Nuclear Information System (INIS)

Chen, Liu; Lin, Zhihong; White, R.

2001-01-01

Resonant heating of particles by an electrostatic wave propagating perpendicular to a confining uniform magnetic field is examined. It is shown that, with a sufficiently large wave amplitude, significant perpendicular stochastic heating can be obtained with wave frequency at a fraction of the cyclotron frequency

Enhancing optical response of graphene through stochastic resonance

Science.gov (United States)

Ying, Lei; Huang, Liang; Lai, Ying-Cheng

2018-04-01

Enhancing the optical response of graphene is a topic of interest with applications in optoelectronics. Subject to light irradiation, graphene can exhibit nontrivial topologically insulating states, effectively turning itself into a Floquet topological insulator due to the time periodicity of the external driving. We find that, when random disorder is present, its interplay with the topologically insulating states can have a dramatic effect on electronic transport through graphene. In particular, we consider the prototypical setting where a graphene nanoribbon is irradiated by circularly polarized light, where the length of the nanoribbon is sufficiently long so that evanescent states have little effect on transport. We uncover a resonance phenomenon in which the conductance is enhanced as the disorder strength is increased from zero, reaches a maximum value for an optimal level of disorder, and decreases as the disorder is strengthened further. With respect to its value at the zero-disorder strength, the maximum conductance value can be as much as 50 % higher. Qualitatively, this can be understood as a result of the dynamical interplay between disorder and Floquet states (channels) generated by light irradiation. Quantitatively, the resonance phenomenon can be explained in the framework of Born theory, where the disorder reorganizes the Floquet Hamiltonian and enhances the effective coupling between the adjacent Floquet conducting channels. That is, disorder is capable of promoting both photon absorption and emission, leading to significant enhancement of nonequilibrium electronic transport. We demonstrate the robustness of the resonance phenomenon by investigating the effects of spatial symmetry breaking on transport and provide an understanding based on analyzing the behavior of the density of states of the Floquet channels.

Periodic and stochastic thermal modulation of protein folding kinetics.

Science.gov (United States)

Platkov, Max; Gruebele, Martin

2014-07-21

Chemical reactions are usually observed either by relaxation of a bulk sample after applying a sudden external perturbation, or by intrinsic fluctuations of a few molecules. Here we show that the two ideas can be combined to measure protein folding kinetics, either by periodic thermal modulation, or by creating artificial thermal noise that greatly exceeds natural thermal fluctuations. We study the folding reaction of the enzyme phosphoglycerate kinase driven by periodic temperature waveforms. As the temperature waveform unfolds and refolds the protein, its fluorescence color changes due to FRET (Förster resonant Energy Transfer) of two donor/acceptor fluorophores labeling the protein. We adapt a simple model of periodically driven kinetics that nicely fits the data at all temperatures and driving frequencies: The phase shifts of the periodic donor and acceptor fluorescence signals as a function of driving frequency reveal reaction rates. We also drive the reaction with stochastic temperature waveforms that produce thermal fluctuations much greater than natural fluctuations in the bulk. Such artificial thermal noise allows the recovery of weak underlying signals due to protein folding kinetics. This opens up the possibility for future detection of a stochastic resonance for protein folding subject to noise with controllable amplitude.

Comments on the use of stochastic processes in the field of the ionizing radiations

International Nuclear Information System (INIS)

Alvarez Romero, Jose T.

2008-01-01

Stochastic process is the name given to a time dependent random process, unfortunately, its time dependence is not always clearly emphasized. In fact, such dependence is not unequivocally stated in the different disciplines of radiation physics, radiobiology or in radiation protection. This is the cause of some conceptual confusion when interpreting relationships between quantities is analyzed, e.g.: imparted energy vs. absorbed dose, stochastic vs. deterministic biological effects; or in radiation protection models, whether: linear or quadratic, relative or absolute. Most of these relationships are associated to stochastic phenomena, and they carry a time dependence that requires clarification. To mention some examples, in radiation physics: the absorbed dose is a non stochastic quantity resulting from averaging a stochastic one namely, the imparted energy, over a representative ensemble via an operation analogous to the Gibbs-Einstein algorithm. On the other hand stochastic quantities require specialized mathematical techniques of stochastic processes to handle them. These refinements are unfortunately ignored in the reports of ICRU 33 and 60. Essentially, a problem to be solved is to establish a clear relationship between micro or mesoscopic stochastic quantities and their macroscopic counterparts, these latter ones possibly being time dependent or not. This is the main objective of microdosimetry. Another problem is to describe phenomena such as electronic equilibrium which is nothing else than a stationary state thus exhibiting no time dependence. Still a different question is the interpretation of radioactive decay as a stochastic process of the Poisson and Markov type. In radiobiology a basic problem is the study of biological stochastic phenomena is to determine the characteristics and structure of those time dependent probabilistic functions allowing the quantification of macroscopic biological manifestations, such as carcinogenesis or genetic effects

SUPPESSION OF LARGE EDGE LOCALIZED MODES IN HIGH CONFINEMENT DIII-D PLASMAS WITH A STOCHASTIC MAGNETIC BOUNDARY

International Nuclear Information System (INIS)

EVANS, TE; MOYER, RA; THOMAS, PR; WATKINS, JG; OSBORNE, TH; BOEDO, JA; FENSTERMACHER, ME; FINKEN, KH; GROEBNER, RJ; GROTH, M; HARRIS, JH; LAHAYE, RJ; LASNIER, CJ; MASUZAKI, S; OHYABU, N; PRETTY, D; RHODES, TL; REIMERDES, H; RUDAKOV, DL; SCHAFFER, MJ; WANG, G; ZENG, L.

2003-01-01

OAK-B135 A stochastic magnetic boundary, produced by an externally applied edge resonant magnetic perturbation, is used to suppress large edge localized modes (ELMs) in high confinement (H-mode) plasmas. The resulting H-mode displays rapid, small oscillations with a bursty character modulated by a coherent 130 Hz envelope. The H-mode transport barrier is unaffected by the stochastic boundary. The core confinement of these discharges is unaffected, despite a three-fold drop in the toroidal rotation in the plasma core. These results demonstrate that stochastic boundaries are compatible with H-modes and may be attractive for ELM control in next-step burning fusion tokamaks

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.

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.

Pediatric magnetic resonance imaging

International Nuclear Information System (INIS)

Cohen, M.D.

1986-01-01

This book defines the current clinical potential of magnetic resonance imaging and focuses on direct clinical work with pediatric patients. A section dealing with the physics of magnetic resonance imaging provides an introduction to enable clinicians to utilize the machine and interpret the images. Magnetic resonance imaging is presented as an appropriate imaging modality for pediatric patients utilizing no radiation

Spin isovector giant resonances in (n,p) reactions

International Nuclear Information System (INIS)

Spicer, B.M.

1997-01-01

The present status of the study of spin-flip isovector giant resonances, using the (n,p) charge exchange reaction, is reviewed. After a brief history of the discovery of these giant resonances, a critical appraisal of the interpretation of the data in terms of giant resonances is given, along with some of the theoretical advances that impact on the interpretation of these data. A sampling of the results obtained for typical targets is given, followed by the interpretation of these results. A brief statement is made concerning the way forward in experimental technique for nuclear structure research using charge exchange reactions

Noncausal stochastic calculus

CERN Document Server

Ogawa, Shigeyoshi

2017-01-01

This book presents an elementary introduction to the theory of noncausal stochastic calculus that arises as a natural alternative to the standard theory of stochastic calculus founded in 1944 by Professor Kiyoshi Itô. As is generally known, Itô Calculus is essentially based on the "hypothesis of causality", asking random functions to be adapted to a natural filtration generated by Brownian motion or more generally by square integrable martingale. The intention in this book is to establish a stochastic calculus that is free from this "hypothesis of causality". To be more precise, a noncausal theory of stochastic calculus is developed in this book, based on the noncausal integral introduced by the author in 1979. After studying basic properties of the noncausal stochastic integral, various concrete problems of noncausal nature are considered, mostly concerning stochastic functional equations such as SDE, SIE, SPDE, and others, to show not only the necessity of such theory of noncausal stochastic calculus but ...

An analysis of current drive by travelling wave based on theory of intrinsic stochasticity

International Nuclear Information System (INIS)

Murakami, Akihiko; Midzuno, Yukio.

1982-04-01

The mechanism of the current generation in a collisionless plasma by a train of travelling mirrors with modulated phase velocity is studied based on the theory of intrinsic stochasticity. It is shown that, if the phase modulation is small, the main contribution to the current generation comes from the phase mixing of the trajectories of trapped electrons in each Fourier component of a driving wave. For the case of a moderate phase modulation, however, formation of a large stochastic region due to the overlapping of primary resonances is very effective for increasing the generated current. Large phase modulation has little advantage in the current generation because the stochastic regions are formed, so to speak, at random in the phase plane. The results of analytical evaluation based on the above theory agree quite well with results of numerical experiments. (author)

New observations concerning the interpretation of magnetic resonance spectroscopy of meningioma

Energy Technology Data Exchange (ETDEWEB)

Yue, Qiang [University of Tsukuba, Department of Neurosurgery, Institute of Clinical Medicine, Tsukuba Science City, Ibaraki (Japan); West China Hospital of Sichuan University, Huaxi MR Research Center, Department of Radiology, Chengdu (China); Isobe, Tomonori [Kitasato University, Department of Medical Technology, School of Allied Health Sciences, Minato (Japan); Shibata, Yasushi; Kawamura, Hiraku; Yamamoto, Youhei; Takano, Shingo; Matsumura, Akira [University of Tsukuba, Department of Neurosurgery, Institute of Clinical Medicine, Tsukuba Science City, Ibaraki (Japan); Anno, Izumi [University of Tsukuba, Department of Radiology, Institute of Clinical Medicine, Tsukuba (Japan)

2008-12-15

This study was aimed to clarify some ambiguities in the interpretation of proton magnetic resonance spectroscopy (1H-MRS) of meningiomas. The cases of 31 meningioma patients (27 benign and 4 nonbenign meningiomas) that underwent single-voxel 1H-MRS (PRESS sequence, TR/TE = 2,000 ms/68, 136, 272 ms) were retrospectively analyzed. To verify the findings of in-vivo study, phantoms were measured, and pathological sections of 11 patients were reviewed. All meningiomas demonstrated increased choline and decreased creatine, except for a lipomatous meningioma that only displayed a prominent lipid (Lip) peak. Alanine (Ala) and lactate (Lac) coexisted in eight cases, indicating an alternative pathway of energy metabolism in meningiomas. They partially overlapped with each other and demonstrated a triplet-like spectral pattern, which was consistent with phantom study. Glutamine/glutamate (Glx) was helpful for the recognition of meningioma when Ala was absent. N-acetyl compounds(NACs) were observed in nine cases whose voxels were completely limited within the tumors, indicating that meningiomas might have endogenous NACs. Lac was indicative of an aggressive meningioma, although not always a nonbenign one. Lip not only represented micronecrosis in nonbenign meningiomas, but also reflected microcystic changes or fatty degeneration in benign meningiomas. 1H-MRS reflects some distinctive biochemical and pathological changes of meningiomas that might be misinterpreted. (orig.)

Fuzzy stochastic damage mechanics (FSDM based on fuzzy auto-adaptive control theory

Directory of Open Access Journals (Sweden)

Ya-jun Wang

2012-06-01

Full Text Available In order to fully interpret and describe damage mechanics, the origin and development of fuzzy stochastic damage mechanics were introduced based on the analysis of the harmony of damage, probability, and fuzzy membership in the interval of [0,1]. In a complete normed linear space, it was proven that a generalized damage field can be simulated through β probability distribution. Three kinds of fuzzy behaviors of damage variables were formulated and explained through analysis of the generalized uncertainty of damage variables and the establishment of a fuzzy functional expression. Corresponding fuzzy mapping distributions, namely, the half-depressed distribution, swing distribution, and combined swing distribution, which can simulate varying fuzzy evolution in diverse stochastic damage situations, were set up. Furthermore, through demonstration of the generalized probabilistic characteristics of damage variables, the cumulative distribution function and probability density function of fuzzy stochastic damage variables, which show β probability distribution, were modified according to the expansion principle. The three-dimensional fuzzy stochastic damage mechanical behaviors of the Longtan rolled-concrete dam were examined with the self-developed fuzzy stochastic damage finite element program. The statistical correlation and non-normality of random field parameters were considered comprehensively in the fuzzy stochastic damage model described in this paper. The results show that an initial damage field based on the comprehensive statistical evaluation helps to avoid many difficulties in the establishment of experiments and numerical algorithms for damage mechanics analysis.

On the interpretation and rotational assignment of degenerate four-wave mixing spectra: Four-photon line strengths for crossover resonances in NO A 2Σ+--X 2Π

International Nuclear Information System (INIS)

Friedman-Hill, E.J.; Rahn, L.A.; Farrow, R.L.

1994-01-01

We present here a set of equations specifically adapted to simulation of fully resonant, high-resolution, phase-conjugate degenerate four-wave mixing (DFWM) in molecular gases. Signal-intensity dependence on molecular wave functions, lifetimes, and laser beam polarizations is explicitly included in these equations. The emphasis of the presentation is on both physically intuitive interpretation and a practical, ''cookbook'' approach to spectral simulation. We present experimental verification of our calculations drawn from the spectrum of dilute NO in N 2 at low pressures. Both degenerate two-level and three-level (crossover) resonances were observed. The experimental spectral intensities are accurately reproduced by the expressions presented here. We point out some of the subtleties of DFWM spectra that could be used as aids to interpretation, especially the use of laser polarization as a probe for spectral line assignments

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

OpenAIRE

Srokowski, Grzegorz; Radzimińska, Agnieszka; Weber-Rajek, Magdalena; Piekorz, Zuzanna; Siedlaczek, Marcin; Jasionek, Agnieszka; Srokowska, Anna; Zukow, Walery

2015-01-01

Srokowski Grzegorz, Radzimińska Agnieszka, Weber-Rajek Magdalena, Piekorz Zuzanna, Siedlaczek Marcin, Jasionek Agnieszka, Srokowska Anna, Zukow Walery. Wpływ rezonansu stochastycznego na równowagę dziecka z Mózgowym Porażeniem Dziecięcym = Influence of stochastic resonance on body balance of children with Cerebral Palsy. Journal of Education, Health and Sport. 2015;5(12):521-534. eISSN 2391-8306. DOI http://dx.doi.org/10.5281/zenodo.42266 http://ojs.ukw.edu.pl/index.php/johs/article/view/...

Stochastic behaviour of particle orbits in field reversed geometries

International Nuclear Information System (INIS)

Finn, J.M.

1979-01-01

Studies of stochastic or ergodic behaviour of beam particle orbits in axisymmetric systems with field reversal produced by ion rings or by neutral injection are presented. In the former case a large class of orbits is ergodic, whereas in the latter most are integrable. Effects of ergodic behaviour on particle confinement, equilibrium, magnetic compression, and stability are discussed. The modification, due to ergodic orbits of the stability criterion for low frequency (ω << ωsub(ci)) resonant instabilities is presented. (author)

Remote vibrotactile noise improves light touch sensation in stroke survivors' fingertips via stochastic resonance.

Science.gov (United States)

Enders, Leah R; Hur, Pilwon; Johnson, Michelle J; Seo, Na Jin

2013-10-11

Stroke rehabilitation does not often integrate both sensory and motor recovery. While subthreshold noise was shown to enhance sensory signal detection at the site of noise application, having a noise-generating device at the fingertip to enhance fingertip sensation and potentially enhance dexterity for stroke survivors is impractical, since the device would interfere with object manipulation. This study determined if remote application of subthreshold vibrotactile noise (away from the fingertips) improves fingertip tactile sensation with potential to enhance dexterity for stroke survivors. Index finger and thumb pad sensation was measured for ten stroke survivors with fingertip sensory deficit using the Semmes-Weinstein Monofilament and Two-Point Discrimination Tests. Sensation scores were measured with noise applied at one of three intensities (40%, 60%, 80% of the sensory threshold) to one of four locations of the paretic upper extremity (dorsal hand proximal to the index finger knuckle, dorsal hand proximal to the thumb knuckle, dorsal wrist, volar wrist) in a random order, as well as without noise at beginning (Pre) and end (Post) of the testing session. Vibrotactile noise of all intensities and locations instantaneously and significantly improved Monofilament scores of the index fingertip and thumb tip (p sensation, independent of noise location and intensity. Vibrotactile noise at the wrist and dorsal hand may have enhanced the fingertips' light touch sensation via stochastic resonance and interneuronal connections. While long-term benefits of noise in stroke patients warrants further investigation, this result demonstrates potential that a wearable device applying vibrotactile noise at the wrist could enhance sensation and grip ability without interfering with object manipulation in everyday tasks.

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.

Stochastic processes

CERN Document Server

Parzen, Emanuel

1962-01-01

Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization.

Science.gov (United States)

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Wong, Wai Peng; Chen, Chun-Hung

2017-04-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort.

Dynamics and Physiological Roles of Stochastic Firing Patterns Near Bifurcation Points

Science.gov (United States)

Jia, Bing; Gu, Huaguang

2017-06-01

Different stochastic neural firing patterns or rhythms that appeared near polarization or depolarization resting states were observed in biological experiments on three nervous systems, and closely matched those simulated near bifurcation points between stable equilibrium point and limit cycle in a theoretical model with noise. The distinct dynamics of spike trains and interspike interval histogram (ISIH) of these stochastic rhythms were identified and found to build a relationship to the coexisting behaviors or fixed firing frequency of four different types of bifurcations. Furthermore, noise evokes coherence resonances near bifurcation points and plays important roles in enhancing information. The stochastic rhythms corresponding to Hopf bifurcation points with fixed firing frequency exhibited stronger coherence degree and a sharper peak in the power spectrum of the spike trains than those corresponding to saddle-node bifurcation points without fixed firing frequency. Moreover, the stochastic firing patterns changed to a depolarization resting state as the extracellular potassium concentration increased for the injured nerve fiber related to pathological pain or static blood pressure level increased for aortic depressor nerve fiber, and firing frequency decreased, which were different from the physiological viewpoint that firing frequency increased with increasing pressure level or potassium concentration. This shows that rhythms or firing patterns can reflect pressure or ion concentration information related to pathological pain information. Our results present the dynamics of stochastic firing patterns near bifurcation points, which are helpful for the identification of both dynamics and physiological roles of complex neural firing patterns or rhythms, and the roles of noise.

Can a microscopic stochastic model explain the emergence of pain cycles in patients?

International Nuclear Information System (INIS)

Di Patti, Francesca; Fanelli, Duccio

2009-01-01

A stochastic model is introduced here to investigate the molecular mechanisms which trigger the perception of pain. The action of analgesic drug compounds is discussed in a dynamical context, where the competition with inactive species is explicitly accounted for. Finite size effects inevitably perturb the mean-field dynamics: oscillations in the amount of bound receptors are spontaneously manifested, driven by the noise which is intrinsic to the system under scrutiny. These effects are investigated both numerically, via stochastic simulations, and analytically, through a large size expansion. The claim that our findings could provide a consistent interpretative framework for explaining the emergence of cyclic behaviors in response to analgesic treatments is substantiated

Beam-plasma generators of stochastic microwave oscillations using for plasma heating in fusion and plasma-chemistry devices and ionospheric investigations

Energy Technology Data Exchange (ETDEWEB)

Mitin, L A; Perevodchikov, V I; Shapiro, A L; Zavyalov, M A [All-Russian Electrotechnical Inst., Moscow (Russian Federation); Bliokh, Yu P; Fajnberg, Ya B [Kharkov Inst. of Physics and Technology (Russian Federation)

1997-12-31

The results of theoretical and experimental investigations of a generator of stochastic microwave power based on a beam-plasma inertial feedback amplifier is discussed with a view to using stochastic oscillations for plasma heating. The plasma heating efficiency in the region of low-frequency resonance in the geometry of the Tokamak is considered theoretically. It is shown that the temperature of heating is proportional to the power multiplied by the spectra width of the noiselike signal. The creation and heating of plasma by stochastic microwave power in an oversized waveguide without external magnetic field is discussed with a view to plasma-chemistry applications. It is shown that the efficiency of heating are defined by the time of phase instability of the stochastic power. (author). 3 figs., 13 refs.

Comparative analysis of magnetic resonance in the polaron pair recombination and the triplet exciton-polaron quenching models

Science.gov (United States)

Mkhitaryan, V. V.; Danilović, D.; Hippola, C.; Raikh, M. E.; Shinar, J.

2018-01-01

We present a comparative theoretical study of magnetic resonance within the polaron pair recombination (PPR) and the triplet exciton-polaron quenching (TPQ) models. Both models have been invoked to interpret the photoluminescence detected magnetic resonance (PLDMR) results in π -conjugated materials and devices. We show that resonance line shapes calculated within the two models differ dramatically in several regards. First, in the PPR model, the line shape exhibits unusual behavior upon increasing the microwave power: it evolves from fully positive at weak power to fully negative at strong power. In contrast, in the TPQ model, the PLDMR is completely positive, showing a monotonic saturation. Second, the two models predict different dependencies of the resonance signal on the photoexcitation power, PL. At low PL, the resonance amplitude Δ I /I is ∝PL within the PPR model, while it is ∝PL2 crossing over to PL3 within the TPQ model. On the physical level, the differences stem from different underlying spin dynamics. Most prominently, a negative resonance within the PPR model has its origin in the microwave-induced spin-Dicke effect, leading to the resonant quenching of photoluminescence. The spin-Dicke effect results from the spin-selective recombination, leading to a highly correlated precession of the on-resonance pair partners under the strong microwave power. This effect is not relevant for TPQ mechanism, where the strong zero-field splitting renders the majority of triplets off resonance. On the technical level, the analytical evaluation of the line shapes for the two models is enabled by the fact that these shapes can be expressed via the eigenvalues of a complex Hamiltonian. This bypasses the necessity of solving the much larger complex linear system of the stochastic Liouville equations. Our findings pave the way towards a reliable discrimination between the two mechanisms via cw PLDMR.

Critical appraisal of rigour in interpretive phenomenological nursing research.

Science.gov (United States)

de Witt, Lorna; Ploeg, Jenny

2006-07-01

This paper reports a critical review of published nursing research for expressions of rigour in interpretive phenomenology, and a new framework of rigour specific to this methodology is proposed. The rigour of interpretive phenomenology is an important nursing research methods issue that has direct implications for the legitimacy of nursing science. The use of a generic set of qualitative criteria of rigour for interpretive phenomenological studies is problematic because it is philosophically inconsistent with the methodology and creates obstacles to full expression of rigour in such studies. A critical review was conducted of the published theoretical interpretive phenomenological nursing literature from 1994 to 2004 and the expressions of rigour in this literature identified. We used three sources to inform the derivation of a proposed framework of expressions of rigour for interpretive phenomenology: the phenomenological scholar van Manen, the theoretical interpretive phenomenological nursing literature, and Madison's criteria of rigour for hermeneutic phenomenology. The nursing literature reveals a broad range of criteria for judging the rigour of interpretive phenomenological research. The proposed framework for evaluating rigour in this kind of research contains the following five expressions: balanced integration, openness, concreteness, resonance, and actualization. Balanced integration refers to the intertwining of philosophical concepts in the study methods and findings and a balance between the voices of study participants and the philosophical explanation. Openness is related to a systematic, explicit process of accounting for the multiple decisions made throughout the study process. Concreteness relates to usefulness for practice of study findings. Resonance encompasses the experiential or felt effect of reading study findings upon the reader. Finally, actualization refers to the future realization of the resonance of study findings. Adoption of this

Nonlinear resonance and dynamical chaos in a diatomic molecule driven by a resonant ir field

International Nuclear Information System (INIS)

Berman, G.P.; Bulgakov, E.N.; Holm, D.D.

1995-01-01

We consider the transition from regular motion to dynamical chaos in a classical model of a diatomic molecule which is driven by a circularly polarized resonant ir field. Under the conditions of a nearly two-dimensional case, the Hamiltonian reduces to that for the nonintegrable motion of a charged particle in an electromagnetic wave [A. J. Lichtenberg and M. A. Lieberman, Regular and Stochastic Motion (Springer-Verlag, City, 1983)]. In the general case, the transition to chaos is connected with the overlapping of vibrational-rotational nonlinear resonances and appears even at rather low radiation field intensity, S approx-gt 1 GW/cm 2 . We also discuss the possibility of experimentally observing this transition

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 .

Stability of the trivial solution for linear stochastic differential equations with Poisson white noise

International Nuclear Information System (INIS)

Grigoriu, Mircea; Samorodnitsky, Gennady

2004-01-01

Two methods are considered for assessing the asymptotic stability of the trivial solution of linear stochastic differential equations driven by Poisson white noise, interpreted as the formal derivative of a compound Poisson process. The first method attempts to extend a result for diffusion processes satisfying linear stochastic differential equations to the case of linear equations with Poisson white noise. The developments for the method are based on Ito's formula for semimartingales and Lyapunov exponents. The second method is based on a geometric ergodic theorem for Markov chains providing a criterion for the asymptotic stability of the solution of linear stochastic differential equations with Poisson white noise. Two examples are presented to illustrate the use and evaluate the potential of the two methods. The examples demonstrate limitations of the first method and the generality of the second method

Non-Markovian stochastic Schroedinger equations: Generalization to real-valued noise using quantum-measurement theory

International Nuclear Information System (INIS)

Gambetta, Jay; Wiseman, H.M.

2002-01-01

Do stochastic Schroedinger equations, also known as unravelings, have a physical interpretation? In the Markovian limit, where the system on average obeys a master equation, the answer is yes. Markovian stochastic Schroedinger equations generate quantum trajectories for the system state conditioned on continuously monitoring the bath. For a given master equation, there are many different unravelings, corresponding to different sorts of measurement on the bath. In this paper we address the non-Markovian case, and in particular the sort of stochastic Schroedinger equation introduced by Strunz, Diosi, and Gisin [Phys. Rev. Lett. 82, 1801 (1999)]. Using a quantum-measurement theory approach, we rederive their unraveling that involves complex-valued Gaussian noise. We also derive an unraveling involving real-valued Gaussian noise. We show that in the Markovian limit, these two unravelings correspond to heterodyne and homodyne detection, respectively. Although we use quantum-measurement theory to define these unravelings, we conclude that the stochastic evolution of the system state is not a true quantum trajectory, as the identity of the state through time is a fiction

Detecting change in stochastic sound sequences.

Directory of Open Access Journals (Sweden)

Benjamin Skerritt-Davis

2018-05-01

Full Text Available Our ability to parse our acoustic environment relies on the brain's capacity to extract statistical regularities from surrounding sounds. Previous work in regularity extraction has predominantly focused on the brain's sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. It has been previously shown that the brain is sensitive to the marginal lower-order statistics of sound sequences (i.e., mean and variance. In this work, we investigate the brain's sensitivity to higher-order statistics describing temporal dependencies between sound events through a series of change detection experiments, where listeners are asked to detect changes in randomness in the pitch of tone sequences. Behavioral data indicate listeners collect statistical estimates to process incoming sounds, and a perceptual model based on Bayesian inference shows a capacity in the brain to track higher-order statistics. Further analysis of individual subjects' behavior indicates an important role of perceptual constraints in listeners' ability to track these sensory statistics with high fidelity. In addition, the inference model facilitates analysis of neural electroencephalography (EEG responses, anchoring the analysis relative to the statistics of each stochastic stimulus. This reveals both a deviance response and a change-related disruption in phase of the stimulus-locked response that follow the higher-order statistics. These results shed light on the brain's ability to process stochastic sound sequences.

Numerical resolution of N-dimensional Fokker-Plank stochastic equations

International Nuclear Information System (INIS)

Garcia-Olivares, A.; Muoz, A.

1992-01-01

This document describes the use of a library of programs able to solve stochastic Fokker-Planck equations in a N-dimensional space. the input data are essentially: (i) the initial distribution of the stochastic variable, (ii) the drift and fluctuation coefficients as a function of the state (which can be obtained from the transition probabilities between neighboring states) and (iii) some parameters controlling the run. A last version of the library accepts sources and sinks defined in the states space. The output is the temporal evolution of the probability distribution in the space defined by a N-dimensional grid. Some applications and readings in Synergetics, Self-Organization, transport phenomena, Ecology and other fields are suggested. If the probability distribution is interpreted as a distribution of particles then the codes can be used to solve the N-dimensional problem of advection-diffusion. (author) 21 fig. 16 ref

Numerical Resolution of N-dimensional Fokker-Planck stochastic equations

International Nuclear Information System (INIS)

Garcia-Olivares, R. A.; Munoz Roldan, A.

1992-01-01

This document describes the use of a library of programs able to solve stochastic Fokker-Planck equations in a N-dimensional space. The input data are essentially: (i) the initial distribution of the stochastic variable, (ii) the drift and fluctuation coefficients as a function of the state (which can be obtained from the transition probabilities between neighboring states) and (iii) some parameters controlling the run. A last version of the library accepts sources and sinks defined in the states space. The output is the temporal evolution of the probability distribution in the space defined by a N-dimensional grid. Some applications and readings in Synergetic, Self-Organization, transport phenomena, Ecology and other fields are suggested. If the probability distribution is interpreted as a distribution of particles then the codes can be used to solve the N-dimensional problem of advection-diffusion. (Author) 16 refs

Stochastic Resonance of Accretion Disk and the Persistent Low ...

Indian Academy of Sciences (India)

luminosity and power spectral density (PSD) for an oscillating disk. Then ... interpretation of the persistent low-frequency quasi-periodic oscillations ... response of the system is enhanced by the noise due to the cooperative effect of noise.

Marian Smoluchowski as the founder of the physics of stochastic phenomena

International Nuclear Information System (INIS)

Chandrasekhar, S.

1989-01-01

This paper present a discussion on Marian Smoluchowski, the originator (along with Einstein) of the theory of Brownian motion; who gave the correct interpretation of the phenomenon of critical opalescence. The author focuses on a series of papers which Smoluchowski wrote in which the foundations of the modern theory of stochastic processes were laid and the related paradoxes of Loschmidt and Zermelo were discussed

Shear Layer Dynamics in Resonating Cavity Flows

National Research Council Canada - National Science Library

Ukeiley, Lawrence

2004-01-01

.... The PIV data was also combined with the surface pressure measurements through the application of the Quadratic Stochastic Estimation procedure to provide time resolved snapshots of the flow field. Examination of these results indicate the strong pumping action of the cavity regardless of whether resonance existed and was used to visualize the large scale structures interacting with the aft wall.

Physical interpretation of Monte Carlo wave-function and stochastic Schroedinger equation methods for cavity quantum electrodynamics

International Nuclear Information System (INIS)

Kist, Tarso B.L.; Orszag, M.; Davidovich, L.

1997-01-01

The dynamics of open system is frequently modeled in terms of a small system S coupled to a reservoir R, the last having an infinitely larger number of degree of freedom than S. Usually the dynamics of the S variables may be of interest, which can be studied using either Langevin equations, or master equations, or yet the path integral formulation. Useful alternatives for the master equation method are the Monte Carlo Wave-function method (MCWF), and Stochastic Schroedinger Equations (SSE's). The methods MCWF and SSE's recently experienced a fast development both in their theoretical background and applications to the study of the dissipative quantum systems dynamics in quantum optics. Even though these alternatives can be shown to be formally equivalent to the master equation approach, they are often regarded as mathematical tricks, with no relation to a concrete physical evolution of the system. The advantage of using them is that one has to deal with state vectors, instead of density matrices, thus reducing the total amount of matrix elements to be calculated. In this work, we consider the possibility of giving a physical interpretation to these methods, in terms of continuous measurements made on the evolving system. We show that physical realizations of the two methods are indeed possible, for a mode of the electromagnetic field in a cavity interacting with a continuum of modes corresponding to the field outside the cavity. Two schemes are proposed, consisting of a mode of the electromagnetic field interacting with a beam of Rydberg two-level atoms. In these schemes, the field mode plays the role of a small system and the atomic beam plays the role of a reservoir (infinitely larger number of degrees of freedom at finite temperature, the interaction between them being given by the Jaynes-Cummings model

Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility

NARCIS (Netherlands)

van Haastrecht, A.; Lord, R.; Pelsser, A.; Schrager, D.

2009-01-01

We consider the pricing of long-dated insurance contracts under stochastic interest rates and stochastic volatility. In particular, we focus on the valuation of insurance options with long-term equity or foreign exchange exposures. Our modeling framework extends the stochastic volatility model of

Linking agent-based models and stochastic models of financial markets.

Science.gov (United States)

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

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

The origin of the algebra of quantum operators in the stochastic formulation of quantum mechanics

International Nuclear Information System (INIS)

Davidson, M.

1979-01-01

The origin of the algebra of the non-commuting operators of quantum mechanics is explained in the general Fenyes-Nelson stochastic models in which the diffusion constant is a free parameter. This is achieved by continuing the diffusion constant to imaginary values, a continuation which destroys the physical interpretation, but does not affect experimental predictions. This continuation leads to great mathematical simplification in the stochastic theory, and to an understanding of the entire mathematical formalism of quantum mechanics. It is more than a formal construction because the diffusion parameter is not an observable in these theories. (Auth.)

Stochastic thermodynamics

Science.gov (United States)

Eichhorn, Ralf; Aurell, Erik

2014-04-01

'Stochastic thermodynamics as a conceptual framework combines the stochastic energetics approach introduced a decade ago by Sekimoto [1] with the idea that entropy can consistently be assigned to a single fluctuating trajectory [2]'. This quote, taken from Udo Seifert's [3] 2008 review, nicely summarizes the basic ideas behind stochastic thermodynamics: for small systems, driven by external forces and in contact with a heat bath at a well-defined temperature, stochastic energetics [4] defines the exchanged work and heat along a single fluctuating trajectory and connects them to changes in the internal (system) energy by an energy balance analogous to the first law of thermodynamics. Additionally, providing a consistent definition of trajectory-wise entropy production gives rise to second-law-like relations and forms the basis for a 'stochastic thermodynamics' along individual fluctuating trajectories. In order to construct meaningful concepts of work, heat and entropy production for single trajectories, their definitions are based on the stochastic equations of motion modeling the physical system of interest. Because of this, they are valid even for systems that are prevented from equilibrating with the thermal environment by external driving forces (or other sources of non-equilibrium). In that way, the central notions of equilibrium thermodynamics, such as heat, work and entropy, are consistently extended to the non-equilibrium realm. In the (non-equilibrium) ensemble, the trajectory-wise quantities acquire distributions. General statements derived within stochastic thermodynamics typically refer to properties of these distributions, and are valid in the non-equilibrium regime even beyond the linear response. The extension of statistical mechanics and of exact thermodynamic statements to the non-equilibrium realm has been discussed from the early days of statistical mechanics more than 100 years ago. This debate culminated in the development of linear response

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

Science.gov (United States)

Varga, Katherine Yvonne

2015-01-01

We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…

Normal perinatal and paediatric postmortem magnetic resonance imaging appearances

Energy Technology Data Exchange (ETDEWEB)

Arthurs, Owen J. [Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London (United Kingdom); UCL Institute of Child Health, London (United Kingdom); Barber, Joy L. [Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London (United Kingdom); Taylor, Andrew M. [Cardiorespiratory Division, Great Ormond Street Hospital for Children NHS Foundation Trust, London (United Kingdom); UCL Institute of Cardiovascular Science, Centre for Cardiovascular Imaging, London (United Kingdom); Sebire, Neil J. [UCL Institute of Child Health, London (United Kingdom); Department of Histopathology, Great Ormond Street Hospital for Children NHS Foundation Trust, London (United Kingdom)

2015-04-01

As postmortem imaging becomes more widely used following perinatal and paediatric deaths, the correct interpretation of images becomes imperative, particularly given the increased use of postmortem magnetic resonance imaging. Many pathological processes may have similar appearances in life and following death. A thorough knowledge of normal postmortem changes is therefore required within postmortem magnetic resonance imaging to ensure that these are not mistakenly interpreted as significant pathology. Similarly, some changes that are interpreted as pathological if they occur during life may be artefacts on postmortem magnetic resonance imaging that are of limited significance. This review serves to illustrate briefly those postmortem magnetic resonance imaging changes as part of the normal changes after death in fetuses and children, and highlight imaging findings that may confuse or mislead an observer to identifying pathology where none is present. (orig.)

Challenges in conditioning a stochastic geological model of a heterogeneous glacial aquifer to a comprehensive soft data set

DEFF Research Database (Denmark)

Koch, Julian; He, Xin; Jensen, Karsten Høgh

2014-01-01

In traditional hydrogeological investigations, one geological model is often used based on subjective interpretations and sparse data availability. This deterministic approach usually does not account for any uncertainties. Stochastic simulation methods address this problem and can capture......TEM data set are derived from a histogram probability matching method, where resistivity is paired with the corresponding lithology from the categorized borehole data. This study integrates two distinct data sources into the stochastic modeling process that represent two extremes of the conditioning...

Dihadronic and dileptonic resonances

International Nuclear Information System (INIS)

Gareev, F.A.; Barabanov, M.Yu.; Kazacha, G.S.

1997-01-01

Simple phenomenological rules are suggested for calculation of dihadron and dilepton resonance masses. A general interpretation is given for different exotic resonances in nuclear physics: Darmstadt-effect, dibaryon, dipion and other resonances. Information about the inner structure of e ± , proton, neutron, pions and so on can be obtained from the usual reactions of the type e + + e - =>γγ, e ± +γ=>e ± γ, e ± μ ± , e ± N... at low, intermediate and high energies using existing experimental devices

Resonant behaviour of MHD waves on magnetic flux tubes. I - Connection formulae at the resonant surfaces. II - Absorption of sound waves by sunspots

Science.gov (United States)

Sakurai, Takashi; Goossens, Marcel; Hollweg, Joseph V.

1991-01-01

The present method of addressing the resonance problems that emerge in such MHD phenomena as the resonant absorption of waves at the Alfven resonance point avoids solving the fourth-order differential equation of dissipative MHD by recourse to connection formulae across the dissipation layer. In the second part of this investigation, the absorption of solar 5-min oscillations by sunspots is interpreted as the resonant absorption of sounds by a magnetic cylinder. The absorption coefficient is interpreted (1) analytically, under certain simplifying assumptions, and numerically, under more general conditions. The observed absorption coefficient magnitude is explained over suitable parameter ranges.

Heat dissipation and information flow for delayed bistable Langevin systems near coherence resonance.

Science.gov (United States)

Xiao, Tiejun

2016-11-01

In this paper, stochastic thermodynamics of delayed bistable Langevin systems near coherence resonance is discussed. We calculate the heat dissipation rate and the information flow of a delayed bistable Langevin system under various noise intensities. Both the heat dissipation rate and the information flow are found to be bell-shaped functions of the noise intensity, which implies that coherence resonance manifests itself in the thermodynamic properties.

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.

Stochastic neuron models

CERN Document Server

Greenwood, Priscilla E

2016-01-01

This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...

Coarse-graining stochastic biochemical networks: adiabaticity and fast simulations

Energy Technology Data Exchange (ETDEWEB)

Nemenman, Ilya [Los Alamos National Laboratory; Sinitsyn, Nikolai [Los Alamos National Laboratory; Hengartner, Nick [Los Alamos National Laboratory

2008-01-01

We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical kinetics networks, which rests on elimination of fast chemical species without a loss of information about mesoscoplc, non-Poissonian fluctuations of the slow ones. Our approach, which is similar to the Born-Oppenhelmer approximation in quantum mechanics, follows from the stochastic path Integral representation of the cumulant generating function of reaction events. In applications with a small number of chemIcal reactions, It produces analytical expressions for cumulants of chemical fluxes between the slow variables. This allows for a low-dimensional, Interpretable representation and can be used for coarse-grained numerical simulation schemes with a small computational complexity and yet high accuracy. As an example, we derive the coarse-grained description for a chain of biochemical reactions, and show that the coarse-grained and the microscopic simulations are in an agreement, but the coarse-gralned simulations are three orders of magnitude faster.

Experimental study of proton stochastic cooling in the NAP-M

International Nuclear Information System (INIS)

Dement'ev, E.N.; Zinevich, N.I.; Medvedko, A.S.; Parkhomchuk, V.V.; Pestrikov, D.V.

1983-01-01

Experimental results on stochastic cooling of a proton beam in the NAP-M are presented. The estimation of the possibility or the cooling method usage in antiproton accumulator rings and also for the study of the cooling peculiarities is the aim of the experiments. Two systems for stochastic cooling have been studied: the wide-band width one and the system with a resonance filter at the input. The experiments are conducted at the energy of 62 MeV. The experiments conducted have shown the possibility of antiproton accumulation. Thermal noises of the feedback system limit the cooling time to approximately 150 s for the single channel system. To attain the cooling time of approximately 1s about one hundred systems operating in parallel connection is required. Mutual effect of particles and coherent instabilities limit the maximum intensity of the particle beam cooled during approximately 1s with the value of approximately 10 7 particles at technically attainable values of the frequency bandwidth

Improving Sensorimotor Function Using Stochastic Vestibular Stimulation

Science.gov (United States)

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

2014-01-01

Astronauts experience sensorimotor changes during spaceflight, particularly during G-transition phases. Post flight sensorimotor changes may include postural and gait instability, spatial disorientation, and visual performance decrements, all of which can degrade operational capabilities of the astronauts and endanger the crew. Crewmember safety would be improved if these detrimental effects of spaceflight could be mitigated by a sensorimotor countermeasure and even further if adaptation to baseline could be facilitated. 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 performance through stochastic resonance (SR). The SR phenomenon occurs when the response of a nonlinear system to a weak input signal is optimized by the application of a particular nonzero level of noise. Two studies have been initiated to investigate the beneficial effects and potential practical usage of SVS. In both studies, electrical vestibular stimulation is applied via electrodes on the mastoid processes using a constant current stimulator. The first study aims to determine the repeatability of the effect of vestibular stimulation on sensorimotor performance and perception in order to better understand the practical use of SVS. The beneficial effect of low levels of SVS on balance performance has been shown in the past. This research uses the same balance task repeated multiple times within a day and across days to study the repeatability of the stimulation effects. The balance test consists of 50 sec trials in which the subject stands with his or her feet together, arms crossed, and eyes closed on compliant foam. Varying levels of SVS, ranging from 0-700 micro A, are applied across different trials. The subject-specific optimal SVS level is that which results in the best balance performance as measured by inertial

Stochastic tools in turbulence

CERN Document Server

Lumey, John L

2012-01-01

Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the

Stochastic population theories

CERN Document Server

Ludwig, Donald

1974-01-01

These notes serve as an introduction to stochastic theories which are useful in population biology; they are based on a course given at the Courant Institute, New York, in the Spring of 1974. In order to make the material. accessible to a wide audience, it is assumed that the reader has only a slight acquaintance with probability theory and differential equations. The more sophisticated topics, such as the qualitative behavior of nonlinear models, are approached through a succession of simpler problems. Emphasis is placed upon intuitive interpretations, rather than upon formal proofs. In most cases, the reader is referred elsewhere for a rigorous development. On the other hand, an attempt has been made to treat simple, useful models in some detail. Thus these notes complement the existing mathematical literature, and there appears to be little duplication of existing works. The authors are indebted to Miss Jeanette Figueroa for her beautiful and speedy typing of this work. The research was supported by the Na...

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.

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.

Transit time for resonant tunneling

International Nuclear Information System (INIS)

Garcia Calderon, G.; Rubio, A.

1990-09-01

This work considers properties of the partial widths in one dimensional elastic resonant tunneling in order to propose a transit-time τ tr = (h/2π)/Γ n T res ) where Γ n is the elastic width and T res the transmission coefficient at resonance energy. This time is interpreted as an average over the resonance energy width. It is shown that the tunneling current density integrated across a sharp resonance is inversely proportional to τ tr . This transit time may be much larger than the values predicted by other definitions. (author). 20 refs

Stochastic processes in cell biology

CERN Document Server

Bressloff, Paul C

2014-01-01

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily...

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)

Stochastic pump effect and geometric phases in dissipative and stochastic systems

Energy Technology Data Exchange (ETDEWEB)

Sinitsyn, Nikolai [Los Alamos National Laboratory

2008-01-01

The success of Berry phases in quantum mechanics stimulated the study of similar phenomena in other areas of physics, including the theory of living cell locomotion and motion of patterns in nonlinear media. More recently, geometric phases have been applied to systems operating in a strongly stochastic environment, such as molecular motors. We discuss such geometric effects in purely classical dissipative stochastic systems and their role in the theory of the stochastic pump effect (SPE).

Deterministic and stochastic control of chimera states in delayed feedback oscillator

Energy Technology Data Exchange (ETDEWEB)

Semenov, V. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Zakharova, A.; Schöll, E. [Institut für Theoretische Physik, TU Berlin, Hardenbergstraße 36, 10623 Berlin (Germany); Maistrenko, Y. [Institute of Mathematics and Center for Medical and Biotechnical Research, NAS of Ukraine, Tereschenkivska Str. 3, 01601 Kyiv (Ukraine)

2016-06-08

Chimera states, characterized by the coexistence of regular and chaotic dynamics, are found in a nonlinear oscillator model with negative time-delayed feedback. The control of these chimera states by external periodic forcing is demonstrated by numerical simulations. Both deterministic and stochastic external periodic forcing are considered. It is shown that multi-cluster chimeras can be achieved by adjusting the external forcing frequency to appropriate resonance conditions. The constructive role of noise in the formation of a chimera states is shown.

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

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.

Multiple-scale stochastic processes: Decimation, averaging and beyond

Energy Technology Data Exchange (ETDEWEB)

Bo, Stefano, E-mail: stefano.bo@nordita.org [Nordita, KTH Royal Institute of Technology and Stockholm University, Roslagstullsbacken 23, SE-106 91 Stockholm (Sweden); Celani, Antonio [Quantitative Life Sciences, The Abdus Salam International Centre for Theoretical Physics (ICTP), Strada Costiera 11, I-34151 - Trieste (Italy)

2017-02-07

The recent experimental progresses in handling microscopic systems have allowed to probe them at levels where fluctuations are prominent, calling for stochastic modeling in a large number of physical, chemical and biological phenomena. This has provided fruitful applications for established stochastic methods and motivated further developments. These systems often involve processes taking place on widely separated time scales. For an efficient modeling one usually focuses on the slower degrees of freedom and it is of great importance to accurately eliminate the fast variables in a controlled fashion, carefully accounting for their net effect on the slower dynamics. This procedure in general requires to perform two different operations: decimation and coarse-graining. We introduce the asymptotic methods that form the basis of this procedure and discuss their application to a series of physical, biological and chemical examples. We then turn our attention to functionals of the stochastic trajectories such as residence times, counting statistics, fluxes, entropy production, etc. which have been increasingly studied in recent years. For such functionals, the elimination of the fast degrees of freedom can present additional difficulties and naive procedures can lead to blatantly inconsistent results. Homogenization techniques for functionals are less covered in the literature and we will pedagogically present them here, as natural extensions of the ones employed for the trajectories. We will also discuss recent applications of these techniques to the thermodynamics of small systems and their interpretation in terms of information-theoretic concepts.

A stochastic model of hormesis

International Nuclear Information System (INIS)

Yakovlev, A.Yu.; Tsodikov, A.D.; Bass, L.

1993-01-01

In order to describe the life-prolonging effect of some agents that are harmful at higher doses, ionizing radiations in particular, a stochastic model is developed in terms of accumulation and progression of intracellular lesions caused by the environment and by the agent itself. The processes of lesion repair, operating at the molecular and cellular level, are assumed to be responsible for this hormesis effect within the framework of the proposed model. Properties of lifetime distributions, derived for analysis of animal experiments with prolonged and acute irradiation, are given special attention. The model provides efficient means of interpreting experimental findings, as evidenced by its application to analysis of some published data on the hormetic effects of prolonged irradiation and of procaine on animal longevity. 51 refs., 2 figs., 1 tabs

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

Lifetime distribution in thermal fatigue - a stochastic geometry approach

International Nuclear Information System (INIS)

Kullig, E.; Michel, B.

1996-02-01

The present report describes the interpretation approach for crack patterns which are generated on the smooth surface of austenitic specimens under thermal fatigue loading. A framework for the fracture mechanics characterization of equibiaxially loaded branched surface cracks is developed which accounts also for crack interaction effects. Advanced methods for the statistical evaluation of crack patterns using suitable characteristic quantities are developed. An efficient simulation procedure allows to identify the impact of different variables of the stochastic crack growth model with respect to the generated crack patterns. (orig.) [de

Interpretation of the Electron Paramagnetic Resonance Spectra of Copper(II)-Tyrosine Complex

Science.gov (United States)

Xu, Xiao-Hui; Kuang, Min-Quan

2017-12-01

The electron paramagnetic resonance (EPR) spectra of [Cu(l-tyrosine)2]n (CuA) were interpreted based on the fourth-order perturbation treatments where the contributions due to the local distortion, ligand orbit and spin-orbit coupling were included. The calculated band transitions d_{x^2} - y^2 to dxy (≈16412 cm-1) and d_{z^2} (≈14845 cm-1) agree well with the band analysis results (d_{x^2} - y^2 \\to d_{xy} ≈16410 and d_{x^2} - y^2 \\to d_{z^2} ≈14850 cm-1). The unresolved separations d_{x^2} - y^2 \\to d_{xz} and d_{x^2} - y^2 \\to d_{yz} in the absorption spectra were evaluated as 26283 and 26262 cm-1, respectively. For CuA, copper chromophores in 1,3-diaminorpropane isophtalate copper(II) complex (CuB) and N-methyl-1,2-diaminoetaane-bis copper(II) polymer (CuC), the transition d_{x^2} - y^2 \\to d_{xy} (=E1≈10Dq) suffered an increase with a decrease in R̅L which was evaluated as the mean value of the copper-ligand bond lengths. The correlations between the tetragonal elongation ratio ρ (=(Rz-R̅L)/R̅L) (or the ratio G=(gz-ge)/((gx+gy)/2-ge)) and the g isotropy gav (=(gx+gy+gz)/3) (or the covalency factor N) for CuA, CuB and CuC were acquired and all the results were discussed.

A stochastic perturbation theory for non-autonomous systems

Energy Technology Data Exchange (ETDEWEB)

Moon, W., E-mail: wm275@damtp.cam.ac.uk [Yale University, New Haven, Connecticut 06520-8109 (United States); Wettlaufer, J. S., E-mail: wettlaufer@maths.ox.ac.uk [Yale University, New Haven, Connecticut 06520-8109 (United States); Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom)

2013-12-15

We develop a perturbation theory for a class of first order nonlinear non-autonomous stochastic ordinary differential equations that arise in climate physics. The perturbative procedure produces moments in terms of integral delay equations, whose order by order decay is characterized in a Floquet-like sense. Both additive and multiplicative sources of noise are discussed and the question of how the nature of the noise influences the results is addressed theoretically and numerically. By invoking the Martingale property, we rationalize the transformation of the underlying Stratonovich form of the model to an Ito form, independent of whether the noise is additive or multiplicative. The generality of the analysis is demonstrated by developing it both for a Brownian particle moving in a periodically forced quartic potential, which acts as a simple model of stochastic resonance, as well as for our more complex climate physics model. The validity of the approach is shown by comparison with numerical solutions. The particular climate dynamics problem upon which we focus involves a low-order model for the evolution of Arctic sea ice under the influence of increasing greenhouse gas forcing ΔF{sub 0}. The deterministic model, developed by Eisenman and Wettlaufer [“Nonlinear threshold behavior during the loss of Arctic sea ice,” Proc. Natl. Acad. Sci. U.S.A. 106(1), 28–32 (2009)] exhibits several transitions as ΔF{sub 0} increases and the stochastic analysis is used to understand the manner in which noise influences these transitions and the stability of the system.

Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power

DEFF Research Database (Denmark)

Chen, Peiyuan; Siano, Pierluigi; Bak-Jensen, Birgitte

2010-01-01

This paper proposes a stochastic optimization algorithm that aims to minimize the expectation of the system power losses by controlling wind turbine (WT) power factors. This objective of the optimization is subject to the probability constraints of bus voltage and line current requirements....... The optimization algorithm utilizes the stochastic models of wind power generation (WPG) and load demand to take into account their stochastic variation. The stochastic model of WPG is developed on the basis of a limited autoregressive integrated moving average (LARIMA) model by introducing a crosscorrelation...... structure to the LARIMA model. The proposed stochastic optimization is carried out on a 69-bus distribution system. Simulation results confirm that, under various combinations of WPG and load demand, the system power losses are considerably reduced with the optimal setting of WT power factor as compared...

Singular stochastic differential equations

CERN Document Server

Cherny, Alexander S

2005-01-01

The authors introduce, in this research monograph on stochastic differential equations, a class of points termed isolated singular points. Stochastic differential equations possessing such points (called singular stochastic differential equations here) arise often in theory and in applications. However, known conditions for the existence and uniqueness of a solution typically fail for such equations. The book concentrates on the study of the existence, the uniqueness, and, what is most important, on the qualitative behaviour of solutions of singular stochastic differential equations. This is done by providing a qualitative classification of isolated singular points, into 48 possible types.

On the interpretation of double-packer tests in heterogeneous porous media: Numerical simulations using the stochastic continuum analogue

International Nuclear Information System (INIS)

Follin, S.

1992-12-01

Flow in fractured crystalline (hard) rocks is of interest in Sweden for assessing the postclosure radiological safety of a deep repository for high-level nuclear waste. For simulation of flow and mass transport in the far field different porous media concepts are often used, whereas discrete fracture/channel network concepts are often used for near-field simulations. Due to lack of data, it is generally necessary to have resort to single-hole double-packer test data for the far-field simulations, i.e., test data on a small scale are regularized in order to fit a comparatively coarser numerical discretization, which is governed by various computational constraints. In the present study the Monte Carlo method is used to investigate the relationship between the transmissivity value interpreted and the corresponding radius of influence in conjunction with single-hole double-packer tests in heterogeneous formations. The numerical flow domain is treated as a two-dimensional heterogeneous porous medium with a spatially varying diffusivity on 3 m scale. The Monte Carlo simulations demonstrate the sensitivity to the correlation range of a spatially varying diffusivity field. In contradiction to what is tacitly assumed in stochastic subsurface hydrology, the results show that the lateral support scale (e.g., the radius of influence) of transmissivity measurements in heterogeneous porous media is a random variable, which is affected by both the hydraulic and statistical characteristics. If these results are general, the traditional methods for scaling-up, assuming a constant lateral scale of support and a multi normal distribution, may lead to an underestimation of the persistence and connectivity of transmissive zones, particularly in highly heterogeneous porous media

Observation of the M1 giant resonance by resonance averaging in 106Pd

International Nuclear Information System (INIS)

Kopecky, J.

1987-01-01

An investigation of capture of 2 keV and 24 keV neutrons in a 105 Pd target resulted in resonance-averaged intensities of primary gamma rays with energies between 5.2 and 9.5 MeV. From these intensities the gamma ray strength functions have been evaluated for E1, M1 and E2 radiation and compared with predictions of the giant resonance theory. The inclusion of an energy dependent spreading width for the E1 giant resonance is necessary. The energy distribution of M1 reduced strength is consistent with an interpretation of a broad resonance around 8.8 MeV. E2 data agrees satisfactorily with the giant extrapolation. (orig.)

Restoring the encoding properties of a stochastic neuron model by an exogenous noise

Science.gov (United States)

Paffi, Alessandra; Camera, Francesca; Apollonio, Francesca; d'Inzeo, Guglielmo; Liberti, Micaela

2015-01-01

Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR) phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed. PMID:25999845

Restoring the encoding properties of a stochastic neuron model by an exogenous noise

Directory of Open Access Journals (Sweden)

Alessandra ePaffi

2015-05-01

Full Text Available Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed.

Sensing (un)binding events via surface plasmons: effects of resonator geometry

Science.gov (United States)

Antosiewicz, Tomasz J.; Claudio, Virginia; Käll, Mikael

2016-04-01

The resonance conditions of localized surface plasmon resonances (LSPRs) can be perturbed in any number ways making plasmon nanoresonators viable tools in detection of e.g. phase changes, pH, gasses, and single molecules. Precise measurement via LSPR of molecular concentrations hinge on the ability to confidently count the number of molecules attached to a metal resonator and ideally to track binding and unbinding events in real-time. These two requirements make it necessary to rigorously quantify relations between the number of bound molecules and response of plasmonic sensors. This endeavor is hindered on the one hand by a spatially varying response of a given plasmonic nanosensor. On the other hand movement of molecules is determined by stochastic effects (Brownian motion) as well as deterministic flow, if present, in microfluidic channels. The combination of molecular dynamics and the electromagnetic response of the LSPR yield an uncertainty which is little understood and whose effect is often disregarded in quantitative sensing experiments. Using a combination of electromagnetic finite-difference time-domain (FDTD) calculations of the plasmon resonance peak shift of various metal nanosensors (disk, cone, rod, dimer) and stochastic diffusion-reaction simulations of biomolecular interactions on a sensor surface we clarify the interplay between position dependent binding probability and inhomogeneous sensitivity distribution. We show, how the statistical characteristics of the total signal upon molecular binding are determined. The proposed methodology is, in general, applicable to any sensor and any transduction mechanism, although the specifics of implementation will vary depending on circumstances. In this work we focus on elucidating how the interplay between electromagnetic and stochastic effects impacts the feasibility of employing particular shapes of plasmonic sensors for real-time monitoring of individual binding reactions or sensing low concentrations

Recent advances in ambit stochastics with a view towards tempo-spatial stochastic volatility/intermittency

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.; Benth, Fred Espen; Veraart, Almut

Ambit stochastics is the name for the theory and applications of ambit fields and ambit processes and constitutes a new research area in stochastics for tempo-spatial phenomena. This paper gives an overview of the main findings in ambit stochastics up to date and establishes new results on genera...

Functional Abstraction of Stochastic Hybrid Systems

NARCIS (Netherlands)

Bujorianu, L.M.; Blom, Henk A.P.; Hermanns, H.

2006-01-01

The verification problem for stochastic hybrid systems is quite difficult. One method to verify these systems is stochastic reachability analysis. Concepts of abstractions for stochastic hybrid systems are needed to ease the stochastic reachability analysis. In this paper, we set up different ways

Stochastic quantisation: theme and variation

International Nuclear Information System (INIS)

Klauder, J.R.; Kyoto Univ.

1987-01-01

The paper on stochastic quantisation is a contribution to the book commemorating the sixtieth birthday of E.S. Fradkin. Stochastic quantisation reformulates Euclidean quantum field theory in the language of Langevin equations. The generalised free field is discussed from the viewpoint of stochastic quantisation. An artificial family of highly singular model theories wherein the space-time derivatives are dropped altogether is also examined. Finally a modified form of stochastic quantisation is considered. (U.K.)

Modelling anisotropic covariance using stochastic development and sub-Riemannian frame bundle geometry

DEFF Research Database (Denmark)

Sommer, Stefan Horst; Svane, Anne Marie

2017-01-01

distributions. We discuss a factorization of the frame bundle projection map through this bundle, the natural sub-Riemannian structure of the frame bundle, the effect of holonomy, and the existence of subbundles where the Hormander condition is satisfied such that the Brownian motions have smooth transition......We discuss the geometric foundation behind the use of stochastic processes in the frame bundle of a smooth manifold to build stochastic models with applications in statistical analysis of non-linear data. The transition densities for the projection to the manifold of Brownian motions developed...... in the frame bundle lead to a family of probability distributions on the manifold. We explain how data mean and covariance can be interpreted as points in the frame bundle or, more precisely, in the bundle of symmetric positive definite 2-tensors analogously to the parameters describing Euclidean normal...

STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...

African Journals Online (AJOL)

eobe

STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.

Interpretation and clinical applications

International Nuclear Information System (INIS)

Higgins, C.B.

1987-01-01

This chapter discusses the factors to be kept in mind during routine interpretation of MR images. This includes the factors that determine contrast on standard spin-echo images and some distinguishing features between true lesions and artifactually simulated lesions. This chapter also indicates the standard protocols for MRI of various portions of the body. Finally, the current indications for MRI of various portions of the body are suggested; however, it is recognized that the indications for MRI are rapidly increasing and consequently, at the time of publication of this chapter, it is likely that many more applications will have become evident. Interpretation of magnetic resonance (MR) images requires consideration of anatomy and tissue characteristics and extraction of artifacts resulting from motion and other factors

The Covariance and Bicovariance of the Stochastic Neutron Field

International Nuclear Information System (INIS)

Perez, R.B.; Mattingly, J.K.; Valentine, T.E.; Mihalczo, J.T.

2000-01-01

On the basis of the general stochastic neutron field theory developed by Munoz-Cobo et al, results on the covariance and bicovariance of the neutron field have been presented. These two statistical quantities are obtained from the counts observed in detectors operating during a period of time (gate length), Δ qc . A classical example is the so called Feynmann Y-function that is defined as the variance to mean ratio of the neutron field. Upon taking the limit of the covariance and bicovariance function for Δ qc r a rrow O , one obtains the two and three detector cross correlation functions respectively. The mathematical structure of the results so obtained have a transparent physical interpretation in terms of the space and delay time overlap between the field-of-view of the detectors. For the first time, an expression has been obtained for the bispectrum function of the stochastic neutron field and for the appropriate weight functions to be used as space-energy-angle correction factors for the one-point kinetics approximation

Stochastic quantization and gravity

International Nuclear Information System (INIS)

Rumpf, H.

1984-01-01

We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)

Stochastic climate theory

NARCIS (Netherlands)

Gottwald, G.A.; Crommelin, D.T.; Franzke, C.L.E.; Franzke, C.L.E.; O'Kane, T.J.

2017-01-01

In this chapter we review stochastic modelling methods in climate science. First we provide a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism. The Mori-Zwanzig equations contain a Markov term, a memory term and a term suggestive of

Resonant interaction of energetic ions with Alfven-like perturbations in stellarators

International Nuclear Information System (INIS)

Karulin, N.; Wobig, H.

1994-04-01

The modification of passing guiding center orbits of 3.5 MeV alpha particles and 45 keV protons in the presence of global Alfven eigenmodes (GAE's) is studied in modular advanced stellarators. It is found that if resonances between particles and waves occur, drift surfaces form a set of island structures. The mode numbers of the perturbations, which are dangerous for the energetic particle confinement, are discussed for two particular stellarators (Helias reactor and Wendelstein 7-AS). The perturbation amplitudes corresponding to the onset of orbit stochasticity are studied numerically. The coefficient of the collisionless stochastic diffusion is estimated using the island width derived analytically. (orig.)

2–stage stochastic Runge–Kutta for stochastic delay differential equations

Energy Technology Data Exchange (ETDEWEB)

Rosli, Norhayati; Jusoh Awang, Rahimah [Faculty of Industrial Science and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang (Malaysia); Bahar, Arifah; Yeak, S. H. [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)

2015-05-15

This paper proposes a newly developed one-step derivative-free method, that is 2-stage stochastic Runge-Kutta (SRK2) to approximate the solution of stochastic delay differential equations (SDDEs) with a constant time lag, r > 0. General formulation of stochastic Runge-Kutta for SDDEs is introduced and Stratonovich Taylor series expansion for numerical solution of SRK2 is presented. Local truncation error of SRK2 is measured by comparing the Stratonovich Taylor expansion of the exact solution with the computed solution. Numerical experiment is performed to assure the validity of the method in simulating the strong solution of SDDEs.

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

Science.gov (United States)

Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

Phase 1 report on sensor technology, data fusion and data interpretation for site characterization

International Nuclear Information System (INIS)

Beckerman, M.

1991-10-01

In this report we discuss sensor technology, data fusion and data interpretation approaches of possible maximal usefulness for subsurface imaging and characterization of land-fill waste sites. Two sensor technologies, terrain conductivity using electromagnetic induction and ground penetrating radar, are described and the literature on the subject is reviewed. We identify the maximum entropy stochastic method as one providing a rigorously justifiable framework for fusing the sensor data, briefly summarize work done by us in this area, and examine some of the outstanding issues with regard to data fusion and interpretation. 25 refs., 17 figs

Advances in magnetic resonance 2

CERN Document Server

Waugh, John S

2013-01-01

Advances in Magnetic Resonance, Volume 2, features a mixture of experimental and theoretical contributions. The book contains four chapters and begins with an ambitious and general treatment of the problem of signal-to-noise ratio in magnetic resonance. This is followed by separate chapters on the interpretation of nuclear relaxation in fluids, with special reference to hydrogen; and various aspects of molecular theory of importance in NMR.

Space-time-modulated stochastic processes

Science.gov (United States)

Giona, Massimiliano

2017-10-01

Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.

RES: Regularized Stochastic BFGS Algorithm

Science.gov (United States)

Mokhtari, Aryan; Ribeiro, Alejandro

2014-12-01

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.

Elitism and Stochastic Dominance

OpenAIRE

Bazen, Stephen; Moyes, Patrick

2011-01-01

Stochastic dominance has typically been used with a special emphasis on risk and inequality reduction something captured by the concavity of the utility function in the expected utility model. We claim that the applicability of the stochastic dominance approach goes far beyond risk and inequality measurement provided suitable adpations be made. We apply in the paper the stochastic dominance approach to the measurment of elitism which may be considered the opposite of egalitarianism. While the...

Full particle orbit effects in regular and stochastic magnetic fields

Energy Technology Data Exchange (ETDEWEB)

Ogawa, Shun, E-mail: shun.ogawa@cpt.univ-mrs.fr [Aix Marseille Univ., Univ. Toulon, CNRS, CPT, Marseille (France); CEA, IRFM, F-13108 St. Paul-lez-Durance Cedex (France); Cambon, Benjamin; Leoncini, Xavier; Vittot, Michel [Aix Marseille Univ., Univ. Toulon, CNRS, CPT, Marseille (France); Castillo-Negrete, Diego del [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6169 (United States); Dif-Pradalier, Guilhem; Garbet, Xavier [CEA, IRFM, F-13108 St. Paul-lez-Durance Cedex (France)

2016-07-15

We present a numerical study of charged particle motion in a time-independent magnetic field in cylindrical geometry. The magnetic field model consists of an unperturbed reversed-shear (non-monotonic q-profile) helical part and a perturbation consisting of a superposition of modes. Contrary to most of the previous studies, the particle trajectories are computed by directly solving the full Lorentz force equations of motion in a six-dimensional phase space using a sixth-order, implicit, symplectic Gauss-Legendre method. The level of stochasticity in the particle orbits is diagnosed using averaged, effective Poincare sections. It is shown that when only one mode is present, the particle orbits can be stochastic even though the magnetic field line orbits are not stochastic (i.e., fully integrable). The lack of integrability of the particle orbits in this case is related to separatrix crossing and the breakdown of the global conservation of the magnetic moment. Some perturbation consisting of two modes creates resonance overlapping, leading to Hamiltonian chaos in magnetic field lines. Then, the particle orbits exhibit a nontrivial dynamics depending on their energy and pitch angle. It is shown that the regions where the particle motion is stochastic decrease as the energy increases. The non-monotonicity of the q-profile implies the existence of magnetic ITBs (internal transport barriers) which correspond to shearless flux surfaces located in the vicinity of the q-profile minimum. It is shown that depending on the energy, these magnetic ITBs might or might not confine particles. That is, magnetic ITBs act as an energy-dependent particle confinement filter. Magnetic field lines in reversed-shear configurations exhibit topological bifurcations (from homoclinic to heteroclinic) due to separatrix reconnection. We show that a similar but more complex scenario appears in the case of particle orbits that depend in a non-trivial way on the energy and pitch angle of the

Stochastic analytic regularization

International Nuclear Information System (INIS)

Alfaro, J.

1984-07-01

Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)

On Stochastic Dependence

Science.gov (United States)

Meyer, Joerg M.

2018-01-01

The contrary of stochastic independence splits up into two cases: pairs of events being favourable or being unfavourable. Examples show that both notions have quite unexpected properties, some of them being opposite to intuition. For example, transitivity does not hold. Stochastic dependence is also useful to explain cases of Simpson's paradox.

Stochastic massless fields I: Integer spin

International Nuclear Information System (INIS)

Lim, S.C.

1981-04-01

Nelson's stochastic quantization scheme is applied to classical massless tensor potential in ''Coulomb'' gauge. The relationship between stochastic potential field in various gauges is discussed using the case of vector potential as an illustration. It is possible to identify the Euclidean tensor potential with the corresponding stochastic field in physical Minkowski space-time. Stochastic quantization of massless fields can also be carried out in terms of field strength tensors. An example of linearized stochastic gravitational field in vacuum is given. (author)

Resonance probe; La sonde a resonance

Energy Technology Data Exchange (ETDEWEB)

Lepechinsky, D; Messiaen, A; Rolland, P [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1966-07-01

After a brief review of papers recently published on the resonance probe as a tool for plasma diagnostics, the main features of the theory proposed by one of us are recalled. In this theory the geometry of the resonator formed by the probe, the ion sheath and the plasma is explicitly taken into account with the quasi-static and cold plasma approximations. Some new results emerging from this theory are indicated and a comparison with experimental data obtained with a spherical probe placed in a quiescent mercury-vapour plasma is made. A good quantitative agreement has been observed, indicating that the theory is satisfactory and justifying the assumptions involved. Nevertheless it appears that in some cases experimental results can only be interpreted when non collisional damping phenomena are taken into consideration. (author) [French] Apres un apercu des etudes recemment publiees sur la sonde a resonance pour le diagnostic des plasmas, on rappelle l'essentiel de la theorie proposee par l'un de nous ou il est tenu compte explicitement de la geometrie du resonateur forme par le systeme sonde-gaine ionique-plasma dans l'approximation quasi-statique et du plasma froid. On indique quelques resultats nouveaux pouvant etre tires de cette theorie et on la confronte avec les donnees experimentales obtenues pour une sonde spherique placee dans un plasma de mercure en equilibre. Un tres bon accord quantitatif a ete constate, indiquant que la theorie est satisfaisante et justifiant les approximations faites dans celle-ci. Il apparait toutefois que certains resultats experimentaux ne peuvent etre interpretes qu'en tenant compte des phenomenes d'amortissement non collisionnels. (auteur)

Stochastic processes inference theory

CERN Document Server

Rao, Malempati M

2014-01-01

This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.

Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

KAUST Repository

Jaleel, Hassan

2018-04-08

Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a framework for the comparative analysis of stochastic learning dynamics with different update rules but same steady-state behavior. We present the framework in the context of two learning dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through an example setup of sensor coverage game that for each of these dynamics, the paths to stochastically stable states exhibit distinctive behaviors. Therefore, we propose multiple criteria to analyze and quantify the differences in the short and medium run behavior of stochastic learning dynamics. We derive and compare upper bounds on the expected hitting time to the set of Nash equilibria for both LLL and ML. For the medium to long-run behavior, we identify a set of tools from the theory of perturbed Markov chains that result in a hierarchical decomposition of the state space into collections of states called cycles. We compare LLL and ML based on the proposed criteria and develop invaluable insights into the comparative behavior of the two dynamics.

Quantum stochastics

CERN Document Server

Chang, Mou-Hsiung

2015-01-01

The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...

Stochastic cooling

International Nuclear Information System (INIS)

Bisognano, J.; Leemann, C.

1982-03-01

Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron

Stochastic optimal control, forward-backward stochastic differential equations and the Schroedinger equation

Energy Technology Data Exchange (ETDEWEB)

Paul, Wolfgang; Koeppe, Jeanette [Institut fuer Physik, Martin Luther Universitaet, 06099 Halle (Germany); Grecksch, Wilfried [Institut fuer Mathematik, Martin Luther Universitaet, 06099 Halle (Germany)

2016-07-01

The standard approach to solve a non-relativistic quantum problem is through analytical or numerical solution of the Schroedinger equation. We show a way to go around it. This way is based on the derivation of the Schroedinger equation from conservative diffusion processes and the establishment of (several) stochastic variational principles leading to the Schroedinger equation under the assumption of a kinematics described by Nelson's diffusion processes. Mathematically, the variational principle can be considered as a stochastic optimal control problem linked to the forward-backward stochastic differential equations of Nelson's stochastic mechanics. The Hamilton-Jacobi-Bellmann equation of this control problem is the Schroedinger equation. We present the mathematical background and how to turn it into a numerical scheme for analyzing a quantum system without using the Schroedinger equation and exemplify the approach for a simple 1d problem.

Possibility of narrow resonances of the omega anti omega-system

International Nuclear Information System (INIS)

Duerr, H.P.

1975-01-01

The possibility of resonances of the Ω anti Ω-system is discussed on the basis of the medium and long range meson exchange forces. The total and partial widths of these resonances are estimated by using well known formulas of nuclear physics. It is demonstrated that analogously the phi- and rho-mesons may be interpreted as p-states of the K anti K- and π π-system, respectively. There appears, however, only a slim chance to interpret the new narrow resonances psi (3100) and psi (3700) as 7 d 1 - and 7 g 1 -Ω anti Ω configurations

Giant dipole resonance in hot nuclei

International Nuclear Information System (INIS)

Mau, N.V.

1993-01-01

Giant resonances built on an excited state of the nucleus at a finite temperature T are studied. The following questions are investigated: how long such collective effects occur in a nucleus when T increases. How the properties of the giant resonances vary when the temperature increases. How the study of giant resonances in hot nuclei can give information on the structure of the nucleus in a highly excited state. The special case of the giant dipole resonance is studied. Some of the experimental results are reviewed and in their theoretical interpretation is discussed. (K.A.). 56 refs., 20 figs., 4 tabs

Stochastic Analysis : A Series of Lectures

CERN Document Server

Dozzi, Marco; Flandoli, Franco; Russo, Francesco

2015-01-01

This book presents in thirteen refereed survey articles an overview of modern activity in stochastic analysis, written by leading international experts. The topics addressed include stochastic fluid dynamics and regularization by noise of deterministic dynamical systems; stochastic partial differential equations driven by Gaussian or Lévy noise, including the relationship between parabolic equations and particle systems, and wave equations in a geometric framework; Malliavin calculus and applications to stochastic numerics; stochastic integration in Banach spaces; porous media-type equations; stochastic deformations of classical mechanics and Feynman integrals and stochastic differential equations with reflection. The articles are based on short courses given at the Centre Interfacultaire Bernoulli of the Ecole Polytechnique Fédérale de Lausanne, Switzerland, from January to June 2012. They offer a valuable resource not only for specialists, but also for other researchers and Ph.D. students in the fields o...

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

Generation of the auroral electron velocity distribution by stochastic acceleration

International Nuclear Information System (INIS)

Bryant, D.A.; Cook, A.C.; Wang, Z.-S.; Angelis, U. de.

1990-07-01

In a further development of the wave theory of the aurora, it is demonstrated, using a Monte-Carlo numerical model, that the characteristic peak in the auroral electron velocity distribution can be generated stochastically through resonant interactions between an initially monotonic distribution and lower-hybrid electrostatic turbulence. The principal requirement is that the velocity spectrum of resonant waves has a sharp cut-off at high velocity. It is then shown that a cut-off is expected as a natural consequence of the difference between the phase and group velocities of lower-hybrid waves. The possibility is considered that a second peak, sometimes observed at lower velocities, is due to the same statistical mechanism, arising from the damping of waves of low phase velocity. An enhancement of wave intensity is found at higher velocities, where momentum flows preferentially from electrons to waves. The relation between the wave theory and the currently prevailing potential-difference theory emerges clearly from the analysis. (author)

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)

Do cosmic rays perturb the operation of a large resonant spherical detector of gravitational waves?

International Nuclear Information System (INIS)

Pizzella, G.

1999-01-01

The sensitivity of resonant gravitational wave detectors is reviewed. The effect of cosmic rays on a large spherical detector is considered. It is shown that the sensibility to short bursts, to monochromatic and to stochastic GW is not significantly degraded by cosmic rays. For a two-detector experiment, only one detector needs to be installed in an underground laboratory. This supports the idea to install a resonant detector at sea-level near a GW interferometer

Do cosmic rays perturb the operation of a large resonant spherical detector of gravitational waves?

Energy Technology Data Exchange (ETDEWEB)

Pizzella, G. [Rome Univ. Tor Vergata, Rome (Italy). Physics Dept.; Inst. for Nuclear Physics, Frascati, RM (Italy)

1999-07-01

The sensitivity of resonant gravitational wave detectors is reviewed. The effect of cosmic rays on a large spherical detector is considered. It is shown that the sensibility to short bursts, to monochromatic and to stochastic GW is not significantly degraded by cosmic rays. For a two-detector experiment, only one detector needs to be installed in an underground laboratory. This supports the idea to install a resonant detector at sea-level near a GW interferometer.

Interpretation of hydraulic conductivity data and parameter evaluation for groundwater flow models

International Nuclear Information System (INIS)

Niemi, A.

1991-01-01

The report reviews recent developments in evaluating effective permeabilities for groundwater flow models, starting from methods of well test interpretation for and proceeding to the principles of parameter estimation. Basic concepts of parameter evaluation as well as expressions derived for effective permeabilities in traditional porous medium are described. Due to the assumptions made, these do often not apply for fractured media. Specific features of fractured medium are discussed, including approaches used determining the size of a possible REV and questions related to the application of stochastic theories. Due to the difficulties encountered when applying traditional deterministic models for fractured media, stochastic and fracture network approaches have been developed. The application of these techniques is still under development, the main questions to be resolved being related to the scarcity of data

Thermal and Driven Stochastic Growth of Langmuir Waves in the Solar Wind and Earth's Foreshock

Science.gov (United States)

Cairns, Iver H.; Robinson, P. A.; Anderson, R. R.

2000-01-01

Statistical distributions of Langmuir wave fields in the solar wind and the edge of Earth's foreshock are analyzed and compared with predictions for stochastic growth theory (SGT). SGT quantitatively explains the solar wind, edge, and deep foreshock data as pure thermal waves, driven thermal waves subject to net linear growth and stochastic effects, and as waves in a pure SGT state, respectively, plus radiation near the plasma frequency f(sub p). These changes are interpreted in terms of spatial variations in the beam instability's growth rate and evolution toward a pure SGT state. SGT analyses of field distributions are shown to provide a viable alternative to thermal noise spectroscopy for wave instruments with coarse frequency resolution, and to separate f(sub p) radiation from Langmuir waves.

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.

Stochastic Reachability Analysis of Hybrid Systems

CERN Document Server

Bujorianu, Luminita Manuela

2012-01-01

Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then...

Homogenization of the stochastic Navier–Stokes equation with a stochastic slip boundary condition

KAUST Repository

Bessaih, Hakima

2015-11-02

The two-dimensional Navier–Stokes equation in a perforated domain with a dynamical slip boundary condition is considered. We assume that the dynamic is driven by a stochastic perturbation on the interior of the domain and another stochastic perturbation on the boundaries of the holes. We consider a scaling (ᵋ for the viscosity and 1 for the density) that will lead to a time-dependent limit problem. However, the noncritical scaling (ᵋ, β > 1) is considered in front of the nonlinear term. The homogenized system in the limit is obtained as a Darcy’s law with memory with two permeabilities and an extra term that is due to the stochastic perturbation on the boundary of the holes. The nonhomogeneity on the boundary contains a stochastic part that yields in the limit an additional term in the Darcy’s law. We use the two-scale convergence method after extending the solution with 0 inside the holes to pass to the limit. By Itô stochastic calculus, we get uniform estimates on the solution in appropriate spaces. Due to the stochastic integral, the pressure that appears in the variational formulation does not have enough regularity in time. This fact made us rely only on the variational formulation for the passage to the limit on the solution. We obtain a variational formulation for the limit that is solution of a Stokes system with two pressures. This two-scale limit gives rise to three cell problems, two of them give the permeabilities while the third one gives an extra term in the Darcy’s law due to the stochastic perturbation on the boundary of the holes.

Stochastic Estimation via Polynomial Chaos

Science.gov (United States)

2015-10-01

AFRL-RW-EG-TR-2015-108 Stochastic Estimation via Polynomial Chaos Douglas V. Nance Air Force Research...COVERED (From - To) 20-04-2015 – 07-08-2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Stochastic Estimation via Polynomial Chaos ...This expository report discusses fundamental aspects of the polynomial chaos method for representing the properties of second order stochastic

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.)

Stochastic parameterizing manifolds and non-Markovian reduced equations stochastic manifolds for nonlinear SPDEs II

CERN Document Server

Chekroun, Mickaël D; Wang, Shouhong

2015-01-01

In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.

Stochastic spin-one massive field

International Nuclear Information System (INIS)

Lim, S.C.

1984-01-01

Stochastic quantization schemes of Nelson and Parisi and Wu are applied to a spin-one massive field. Unlike the scalar case Nelson's stochastic spin-one massive field cannot be identified with the corresponding euclidean field even if the fourth component of the euclidean coordinate is taken as equal to the real physical time. In the Parisi-Wu quantization scheme the stochastic Proca vector field has a similar property as the scalar field; which has an asymptotically stationary part and a transient part. The large equal-time limit of the expectation values of the stochastic Proca field are equal to the expectation values of the corresponding euclidean field. In the Stueckelberg formalism the Parisi-Wu scheme gives rise to a stochastic vector field which differs from the massless gauge field in that the gauge cannot be fixed by the choice of boundary condition. (orig.)

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

A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

Energy Technology Data Exchange (ETDEWEB)

Hosking, John Joseph Absalom, E-mail: j.j.a.hosking@cma.uio.no [University of Oslo, Centre of Mathematics for Applications (CMA) (Norway)

2012-12-15

We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966-979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197-216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

International Nuclear Information System (INIS)

Hosking, John Joseph Absalom

2012-01-01

We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966–979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197–216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

Stochastic TDHF and the Boltzman-Langevin equation

International Nuclear Information System (INIS)

Suraud, E.; Reinhard, P.G.

1991-01-01

Outgoing from a time-dependent theory of correlations, we present a stochastic differential equation for the propagation of ensembles of Slater determinants, called Stochastic Time-Dependent Hartree-Fock (Stochastic TDHF). These ensembles are allowed to develop large fluctuations in the Hartree-Fock mean fields. An alternative stochastic differential equation, the Boltzmann-Langevin equation, can be derived from Stochastic TDHF by averaging over subensembles with small fluctuations

Acoustic resonances of fluid-immersed elastic cylinders and spheroids: Theory and experiment

Science.gov (United States)

Niemiec, Jan; Überall, Herbert; Bao, X. L.

2002-05-01

Frequency resonances in the scattering of acoustic waves from a target object are caused by the phase matching of surface waves repeatedly encircling the object. This is exemplified here by considering elastic finite cylinders and spheroids, and the phase-matching condition provides a means of calculating the complex resonance frequencies of such objects. Tank experiments carried out at Catholic University, or at the University of Le Havre, France by G. Maze and J. Ripoche, have been interpreted using this approach. The experiments employed sound pulses to measure arrival times, which allowed identification of the surface paths taken by the surface waves, thus giving rise to resonances in the scattering amplitude. A calculation of the resonance frequencies using the T-matrix approach showed satisfactory agreement with the experimental resonance frequencies that were either measured directly (as at Le Havre), or that were obtained by the interpretation of measured arrival times (at Catholic University) using calculated surface wave paths, and the extraction of resonance frequencies therefrom, on the basis of the phase-matching condition. Results for hemispherically endcapped, evacuated steel cylinders obtained in a lake experiment carried out by the NSWC were interpreted in the same fashion.

Stochastic quantization of Proca field

International Nuclear Information System (INIS)

Lim, S.C.

1981-03-01

We discuss the complications that arise in the application of Nelson's stochastic quantization scheme to classical Proca field. One consistent way to obtain spin-one massive stochastic field is given. It is found that the result of Guerra et al on the connection between ground state stochastic field and the corresponding Euclidean-Markov field extends to the spin-one case. (author)

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.

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.

Nuclear magnetic resonance spectroscopy and imaging

International Nuclear Information System (INIS)

Jiang Weiping; Wang Qi; Zhou Xin

2013-01-01

This paper briefly introduces the basic principle of nuclear magnetic resonance (NMR). Protein's structures and functions and dynamics studied by liquid NMR are elaborated; methods for enhancing the resolution of solid state NMR and its applications are discussed; the principle of magnetic resonance imaging (MRI) is interpreted, and applications in different aspects are reviewed. Finally, the progress of NMR is commented. (authors)

Double diffusivity model under stochastic forcing

Science.gov (United States)

Chattopadhyay, Amit K.; Aifantis, Elias C.

2017-05-01

The "double diffusivity" model was proposed in the late 1970s, and reworked in the early 1980s, as a continuum counterpart to existing discrete models of diffusion corresponding to high diffusivity paths, such as grain boundaries and dislocation lines. It was later rejuvenated in the 1990s to interpret experimental results on diffusion in polycrystalline and nanocrystalline specimens where grain boundaries and triple grain boundary junctions act as high diffusivity paths. Technically, the model pans out as a system of coupled Fick-type diffusion equations to represent "regular" and "high" diffusivity paths with "source terms" accounting for the mass exchange between the two paths. The model remit was extended by analogy to describe flow in porous media with double porosity, as well as to model heat conduction in media with two nonequilibrium local temperature baths, e.g., ion and electron baths. Uncoupling of the two partial differential equations leads to a higher-ordered diffusion equation, solutions of which could be obtained in terms of classical diffusion equation solutions. Similar equations could also be derived within an "internal length" gradient (ILG) mechanics formulation applied to diffusion problems, i.e., by introducing nonlocal effects, together with inertia and viscosity, in a mechanics based formulation of diffusion theory. While being remarkably successful in studies related to various aspects of transport in inhomogeneous media with deterministic microstructures and nanostructures, its implications in the presence of stochasticity have not yet been considered. This issue becomes particularly important in the case of diffusion in nanopolycrystals whose deterministic ILG-based theoretical calculations predict a relaxation time that is only about one-tenth of the actual experimentally verified time scale. This article provides the "missing link" in this estimation by adding a vital element in the ILG structure, that of stochasticity, that takes into

Granular compaction and stretched exponentials - Experiments and a numerical stochastic model

Directory of Open Access Journals (Sweden)

Nicolas Maxime

2017-01-01

Full Text Available We present a stochastic model to investigate the compaction kinetics of a granular material submitted to vibration. The model is compared to experimental results obtained with glass beads and with a cohesive powder. We also propose a physical interpretation of the characteristic time τ and the exponent β of the stretched exponential function widely used to represent the granular compaction kinetics, and we show that the characteristic time is proportional to the number of grains to move. The exponent β is expressed as a logarithmic compaction rate.

Power Laws in Stochastic Processes for Social Phenomena: An Introductory Review

Science.gov (United States)

Kumamoto, Shin-Ichiro; Kamihigashi, Takashi

2018-03-01

Many phenomena with power laws have been observed in various fields of the natural and social sciences, and these power laws are often interpreted as the macro behaviors of systems that consist of micro units. In this paper, we review some basic mathematical mechanisms that are known to generate power laws. In particular, we focus on stochastic processes including the Yule process and the Simon process as well as some recent models. The main purpose of this paper is to explain the mathematical details of their mechanisms in a self-contained manner.

Learning Theory Estimates with Observations from General Stationary Stochastic Processes.

Science.gov (United States)

Hang, Hanyuan; Feng, Yunlong; Steinwart, Ingo; Suykens, Johan A K

2016-12-01

This letter investigates the supervised learning problem with observations drawn from certain general stationary stochastic processes. Here by general, we mean that many stationary stochastic processes can be included. We show that when the stochastic processes satisfy a generalized Bernstein-type inequality, a unified treatment on analyzing the learning schemes with various mixing processes can be conducted and a sharp oracle inequality for generic regularized empirical risk minimization schemes can be established. The obtained oracle inequality is then applied to derive convergence rates for several learning schemes such as empirical risk minimization (ERM), least squares support vector machines (LS-SVMs) using given generic kernels, and SVMs using gaussian kernels for both least squares and quantile regression. It turns out that for independent and identically distributed (i.i.d.) processes, our learning rates for ERM recover the optimal rates. For non-i.i.d. processes, including geometrically [Formula: see text]-mixing Markov processes, geometrically [Formula: see text]-mixing processes with restricted decay, [Formula: see text]-mixing processes, and (time-reversed) geometrically [Formula: see text]-mixing processes, our learning rates for SVMs with gaussian kernels match, up to some arbitrarily small extra term in the exponent, the optimal rates. For the remaining cases, our rates are at least close to the optimal rates. As a by-product, the assumed generalized Bernstein-type inequality also provides an interpretation of the so-called effective number of observations for various mixing processes.

Optimal Control for Stochastic Delay Evolution Equations

Energy Technology Data Exchange (ETDEWEB)

Meng, Qingxin, E-mail: mqx@hutc.zj.cn [Huzhou University, Department of Mathematical Sciences (China); Shen, Yang, E-mail: skyshen87@gmail.com [York University, Department of Mathematics and Statistics (Canada)

2016-08-15

In this paper, we investigate a class of infinite-dimensional optimal control problems, where the state equation is given by a stochastic delay evolution equation with random coefficients, and the corresponding adjoint equation is given by an anticipated backward stochastic evolution equation. We first prove the continuous dependence theorems for stochastic delay evolution equations and anticipated backward stochastic evolution equations, and show the existence and uniqueness of solutions to anticipated backward stochastic evolution equations. Then we establish necessary and sufficient conditions for optimality of the control problem in the form of Pontryagin’s maximum principles. To illustrate the theoretical results, we apply stochastic maximum principles to study two examples, an infinite-dimensional linear-quadratic control problem with delay and an optimal control of a Dirichlet problem for a stochastic partial differential equation with delay. Further applications of the two examples to a Cauchy problem for a controlled linear stochastic partial differential equation and an optimal harvesting problem are also considered.

Introduction to stochastic calculus

CERN Document Server

Karandikar, Rajeeva L

2018-01-01

This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but rigorous treatment of the subject, including a range of advanced topics. The book discusses in-depth topics such as quadratic variation, Ito formula, and Emery topology. The authors briefly address continuous semi-martingales to obtain growth estimates and study solution of a stochastic differential equation (SDE) by using the technique of random time change. Later, by using Metivier–Pellumail inequality, the solutions to SDEs driven by general semi-martingales are discussed. The connection of the theory with mathematical finance is briefly discussed and the book has extensive treatment on the representation of martingales as stochastic integrals and a second fundamental theorem of asset pricing. Intended for undergraduate- and beginning graduate-level stud...

Stochastic excitation of low frequency variability in the midlatitude atmosphere

International Nuclear Information System (INIS)

Ioannou, P.J.; Farrell, B.F.

1994-01-01

Spectral analysis of the transient geopotential variance of the midlatitude atmosphere reveals a sharp peak in the wavenumber-period spectra concentrated at large scales (zonal wave numbers m 10 days). This is surprising because conventional baroclinic instability calculations predict a broad maximum of the variance at synoptic scale (8 < m < 12) with associated period of a few days. In this work we review the method for calculating the maintained variance and associated fluxes and then discuss some results pertaining to the interpretation of the EOF's which arise from the stochastic dynamics of non-normal dynamical systems

Brownian motion, martingales, and stochastic calculus

CERN Document Server

Le Gall, Jean-François

2016-01-01

This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter. Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested i...

Perturbation analysis of spontaneous action potential initiation by stochastic ion channels

KAUST Repository

Keener, James P.

2011-07-01

A stochastic interpretation of spontaneous action potential initiation is developed for the Morris-Lecar equations. Initiation of a spontaneous action potential can be interpreted as the escape from one of the wells of a double well potential, and we develop an asymptotic approximation of the mean exit time using a recently developed quasistationary perturbation method. Using the fact that the activating ionic channel\\'s random openings and closings are fast relative to other processes, we derive an accurate estimate for the mean time to fire an action potential (MFT), which is valid for a below-threshold applied current. Previous studies have found that for above-threshold applied current, where there is only a single stable fixed point, a diffusion approximation can be used. We also explore why different diffusion approximation techniques fail to estimate the MFT. © 2011 American Physical Society.

Stochastic line motion and stochastic flux conservation for nonideal hydromagnetic models

International Nuclear Information System (INIS)

Eyink, Gregory L.

2009-01-01

We prove that smooth solutions of nonideal (viscous and resistive) incompressible magnetohydrodynamic (MHD) equations satisfy a stochastic law of flux conservation. This property implies that the magnetic flux through a surface is equal to the average of the magnetic fluxes through an ensemble of surfaces advected backward in time by the plasma velocity perturbed with a random white noise. Our result is an analog of the well-known Alfven theorem of ideal MHD and is valid for any value of the magnetic Prandtl number. A second stochastic conservation law is shown to hold at unit Prandtl number, a random version of the generalized Kelvin theorem derived by Bekenstein and Oron for ideal MHD. These stochastic conservation laws are not only shown to be consequences of the nonideal MHD equations but are proved in fact to be equivalent to those equations. We derive similar results for two more refined hydromagnetic models, Hall MHD and the two-fluid plasma model, still assuming incompressible velocities and isotropic transport coefficients. Finally, we use these results to discuss briefly the infinite-Reynolds-number limit of hydromagnetic turbulence and to support the conjecture that flux conservation remains stochastic in that limit.

Magnetic Resonance Imaging (MRI) -- Head

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Full Text Available ... by the interpreting radiologist. Frequently, the differentiation of abnormal (diseased) tissue from normal tissues is better with ... Tumor Treatment Magnetic Resonance Imaging (MRI) Safety Alzheimer's Disease Head Injury Brain Tumors Images related to Magnetic ...

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

Brownian motion and stochastic calculus

CERN Document Server

Karatzas, Ioannis

1998-01-01

This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...

Variance decomposition in stochastic simulators.

Science.gov (United States)

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Science.gov (United States)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Energy Technology Data Exchange (ETDEWEB)

Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

KAUST Repository

Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

2015-01-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

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.

An introduction to probability and stochastic processes

CERN Document Server

Melsa, James L

2013-01-01

Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

Research on nonlinear stochastic dynamical price model

International Nuclear Information System (INIS)

Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng

2008-01-01

In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies

Stochastic Systems Uncertainty Quantification and Propagation

CERN Document Server

Grigoriu, Mircea

2012-01-01

Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents: ·         A clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis   ·          Probabilistic models for random variables an...

Stochastic-field cavitation model

International Nuclear Information System (INIS)

Dumond, J.; Magagnato, F.; Class, A.

2013-01-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations

Stochastic-field cavitation model

Science.gov (United States)

Dumond, J.; Magagnato, F.; Class, A.

2013-07-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.

Equal-potential interpretation of electrically induced resonances in metamaterials

DEFF Research Database (Denmark)

Peng, Liang; Mortensen, N. Asger

2011-01-01

We propose a general description of electrically induced resonances (EIR) in metamaterials (MMs) comprising subwavelength unit cells. Based on classical electrodynamics, we found that EIR is governed by an equal-potential effect. Our theory accounts for the EIR phenomena and can give a renewed...... definition of the effective electric field and hence effective permittivity for MMs made of either dielectrics or metals as well as combinations thereof. The EIR, inherent to the periodic structures, may be the unifying origin of recently observed anomalous electromagnetic phenomena, e.g. the enhanced...

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...

Resonant diphoton phenomenology simplified

International Nuclear Information System (INIS)

Panico, Giuliano; Vecchi, Luca; Wulzer, Andrea

2016-01-01

A framework is proposed to describe resonant diphoton phenomenology at hadron colliders in full generality. It can be employed for a comprehensive model-independent interpretation of the experimental data. Within the general framework, few benchmark scenarios are defined as representative of the various phenomenological options and/or of motivated new physics scenarios. Their usage is illustrated by performing a characterization of the 750 GeV excess, based on a recast of available experimental results. We also perform an assessment of which properties of the resonance could be inferred, after discovery, by a careful experimental study of the diphoton distributions. These include the spin J of the new particle and its dominant production mode. Partial information on its CP-parity can also be obtained, but only for J≥2. The complete determination of the resonance CP properties requires studying the pattern of the initial state radiation that accompanies the resonant diphoton production.

Stochastic volatility of volatility in continuous time

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole; Veraart, Almut

This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility...... of volatility can be defined both non-parametrically, where we link it to the quadratic variation of the stochastic variance process, and parametrically, where we propose two new SV models which allow for stochastic volatility of volatility. In addition, we show that volatility of volatility can be estimated...

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.

Set-Valued Stochastic Lebesque Integral and Representation Theorems

Directory of Open Access Journals (Sweden)

Jungang Li

2008-06-01

Full Text Available In this paper, we shall firstly illustrate why we should introduce set-valued stochastic integrals, and then we shall discuss some properties of set-valued stochastic processes and the relation between a set-valued stochastic process and its selection set. After recalling the Aumann type definition of stochastic integral, we shall introduce a new definition of Lebesgue integral of a set-valued stochastic process with respect to the time t . Finally we shall prove the presentation theorem of set-valued stochastic integral and dis- cuss further properties that will be useful to study set-valued stochastic differential equations with their applications.

Instantaneous stochastic perturbation theory

International Nuclear Information System (INIS)

Lüscher, Martin

2015-01-01

A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.

A retrodictive stochastic simulation algorithm

International Nuclear Information System (INIS)

Vaughan, T.G.; Drummond, P.D.; Drummond, A.J.

2010-01-01

In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.

Stochastic processes and quantum theory

International Nuclear Information System (INIS)

Klauder, J.R.

1975-01-01

The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)

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...

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.''

Momentum Maps and Stochastic Clebsch Action Principles

Science.gov (United States)

Cruzeiro, Ana Bela; Holm, Darryl D.; Ratiu, Tudor S.

2018-01-01

We derive stochastic differential equations whose solutions follow the flow of a stochastic nonlinear Lie algebra operation on a configuration manifold. For this purpose, we develop a stochastic Clebsch action principle, in which the noise couples to the phase space variables through a momentum map. This special coupling simplifies the structure of the resulting stochastic Hamilton equations for the momentum map. In particular, these stochastic Hamilton equations collectivize for Hamiltonians that depend only on the momentum map variable. The Stratonovich equations are derived from the Clebsch variational principle and then converted into Itô form. In comparing the Stratonovich and Itô forms of the stochastic dynamical equations governing the components of the momentum map, we find that the Itô contraction term turns out to be a double Poisson bracket. Finally, we present the stochastic Hamiltonian formulation of the collectivized momentum map dynamics and derive the corresponding Kolmogorov forward and backward equations.

Observation and resonant x-ray optical interpretation of multi-atom resonant photoemission effects in O 1s emission from NiO

International Nuclear Information System (INIS)

Mannella, N.; Yang, S.-H.; Mun, B.S.; Garcia de Abajo, F.J.; Kay, A.W.; Sell, B.C.; Watanabe, M.; Ohldag, H.; Arenholz, E.; Young, A.T.; Hussain, Z.; Van Hove, M.A.; Fadley, C.S.

2006-01-01

We present experimental and theoretical results for the variation of the O 1s intensity from a NiO(001) surface as the excitation energy is varied through the Ni 2p1/2,3/2 absorption resonances, and as the incidence angle of the radiation is varied from grazing to larger values. For grazing incidence, a strong multi-atom resonant photoemission(MARPE) effect is seen on the O 1s intensity as the Ni 2p resonances are crossed, but its magnitude decreases rapidly as the incidence angle is increased. Resonant x-ray optical (RXRO) calculations are found to predict these effects very well, although the experimental effects are found to decrease at higher incidence angles faster than those in theory. The potential influence of photoelectron diffraction effects on such measurements are also considered, including experimental data with azimuthal-angle variation and corresponding multiple-scattering-diffraction calculations, but we conclude that they do not vary beyond what is expected on the basis of the change in photoelectron kinetic energy. Varying from linear polarization to circular polarization is found to enhance these effects in NiO considerably, although the reasons are not clear. We also discuss the relationship of these measurements to other related interatomic resonance experiments and theoretical developments, and make some suggestions for future studies in this area

Stochastic biomathematical models with applications to neuronal modeling

CERN Document Server

Batzel, Jerry; Ditlevsen, Susanne

2013-01-01

Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

A Stochastic Slow Extraction Scheme For U70 Synchrotron

CERN Document Server

Ivanov, S

2004-01-01

Outcomes of a feasibility study for a low-budget sto-chastic slow extraction system in the U70 proton synchro-tron of IHEP are reported. The existing 200 MHz (spill) RF system is to be employed as a longitudinal kicker. It will be driven by a sum of a non-random RF carrier plus an additive random amplitude-modulated signal - either quadrature or in-phase, or both. A few novel solutions to be implemented in the longitudinal diffusion technique that would force protons into the conventional 3-rd order transverse extraction resonance are foreseen so as to com-ply with the technical constraints inherent in U70. Getting a-few-seconds-long and high-quality spills is assessed as being viable with the system in question.

Introduction to stochastic dynamic programming

CERN Document Server

Ross, Sheldon M; Lukacs, E

1983-01-01

Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the

Stochastic Finite Elements in Reliability-Based Structural Optimization

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Engelund, S.

Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...

BRST stochastic quantization

International Nuclear Information System (INIS)

Hueffel, H.

1990-01-01

After a brief review of the BRST formalism and of the Parisi-Wu stochastic quantization method we introduce the BRST stochastic quantization scheme. It allows the second quantization of constrained Hamiltonian systems in a manifestly gauge symmetry preserving way. The examples of the relativistic particle, the spinning particle and the bosonic string are worked out in detail. The paper is closed by a discussion on the interacting field theory associated to the relativistic point particle system. 58 refs. (Author)

Clinical magnetic resonance: imaging and spectroscopy

International Nuclear Information System (INIS)

Andrew, E.R.; Bydder, Graeme; Griffiths, John; Iles, Richard; Styles, Peter

1990-01-01

This book begins with a readable, comprehensive but non-mathematical introduction to the basic underlying principles of magnetic resonance. Further chapters include information on the theory and principles of MRI and MRS, the interpretation of MR images, the clinical applications and scope of MRI and MRS, practical aspects of spectroscopy and magnetic resonance, and also the practical problems associated with the siting, safety and operation of large MRI and MRS equipment. (author)

Stochastic quantum gravity

International Nuclear Information System (INIS)

Rumpf, H.

1987-01-01

We begin with a naive application of the Parisi-Wu scheme to linearized gravity. This will lead into trouble as one peculiarity of the full theory, the indefiniteness of the Euclidean action, shows up already at this level. After discussing some proposals to overcome this problem, Minkowski space stochastic quantization will be introduced. This will still not result in an acceptable quantum theory of linearized gravity, as the Feynman propagator turns out to be non-causal. This defect will be remedied only after a careful analysis of general covariance in stochastic quantization has been performed. The analysis requires the notion of a metric on the manifold of metrics, and a natural candidate for this is singled out. With this a consistent stochastic quantization of Einstein gravity becomes possible. It is even possible, at least perturbatively, to return to the Euclidean regime. 25 refs. (Author)

Stochastic models, estimation, and control

CERN Document Server

Maybeck, Peter S

1982-01-01

This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.

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.

Stochastic simulation and robust design optimization of integrated photonic filters

Directory of Open Access Journals (Sweden)

Weng Tsui-Wei

2016-07-01

Full Text Available Manufacturing variations are becoming an unavoidable issue in modern fabrication processes; therefore, it is crucial to be able to include stochastic uncertainties in the design phase. In this paper, integrated photonic coupled ring resonator filters are considered as an example of significant interest. The sparsity structure in photonic circuits is exploited to construct a sparse combined generalized polynomial chaos model, which is then used to analyze related statistics and perform robust design optimization. Simulation results show that the optimized circuits are more robust to fabrication process variations and achieve a reduction of 11%–35% in the mean square errors of the 3 dB bandwidth compared to unoptimized nominal designs.

A heterogeneous stochastic FEM framework for elliptic PDEs

International Nuclear Information System (INIS)

Hou, Thomas Y.; Liu, Pengfei

2015-01-01

We introduce a new concept of sparsity for the stochastic elliptic operator −div(a(x,ω)∇(⋅)), which reflects the compactness of its inverse operator in the stochastic direction and allows for spatially heterogeneous stochastic structure. This new concept of sparsity motivates a heterogeneous stochastic finite element method (HSFEM) framework for linear elliptic equations, which discretizes the equations using the heterogeneous coupling of spatial basis with local stochastic basis to exploit the local stochastic structure of the solution space. We also provide a sampling method to construct the local stochastic basis for this framework using the randomized range finding techniques. The resulting HSFEM involves two stages and suits the multi-query setting: in the offline stage, the local stochastic structure of the solution space is identified; in the online stage, the equation can be efficiently solved for multiple forcing functions. An online error estimation and correction procedure through Monte Carlo sampling is given. Numerical results for several problems with high dimensional stochastic input are presented to demonstrate the efficiency of the HSFEM in the online stage

Separable quadratic stochastic operators

International Nuclear Information System (INIS)

Rozikov, U.A.; Nazir, S.

2009-04-01

We consider quadratic stochastic operators, which are separable as a product of two linear operators. Depending on properties of these linear operators we classify the set of the separable quadratic stochastic operators: first class of constant operators, second class of linear and third class of nonlinear (separable) quadratic stochastic operators. Since the properties of operators from the first and second classes are well known, we mainly study the properties of the operators of the third class. We describe some Lyapunov functions of the operators and apply them to study ω-limit sets of the trajectories generated by the operators. We also compare our results with known results of the theory of quadratic operators and give some open problems. (author)

Trajectory averaging for stochastic approximation MCMC algorithms

KAUST Repository

Liang, Faming

2010-01-01

to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic

Dynamical and hamiltonian dilations of stochastic processes

International Nuclear Information System (INIS)

Baumgartner, B.; Gruemm, H.-R.

1982-01-01

This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)

Suppression of large edge localized modes with edge resonant magnetic fields in high confinement DIII-D plasmas

International Nuclear Information System (INIS)

Thomas, P.R.; Becoulet, M.; Evans, T.E.; Osborne, T.H.; Groebner, R.J.; Jackson, G.L.; Haye, R.J. La; Schaffer, M.J.; West, W.P.; Moyer, R.A.; Rhodes, T.L.; Rudakov, D.L.; Watkins, J.G.; Boedo, J.A.; Doyle, E.J.; Wang, G.; Zeng, L.; Fenstermacher, M.E.; Groth, M.; Lasnier, C.J.; Finken, K.H.; Harris, J.H.; Pretty, D.G.; Masuzaki, S.; Ohyabu, N.; Reimerdes, H.; Wade, M.R.

2005-01-01

Large divertor heat pulses due to Type-I edge localized modes (ELMs) have been eliminated reproducibly in DIII-D with small dc currents driven in a simple magnetic perturbation coil. The current required to eliminate all but a few isolated Type-I ELMs, during a coil pulse, is less than 0.4% of plasma current. Modelling shows that the perturbation fields resonate with plasma flux surfaces across most of the pedestal region (0.9 ≤ N ≤ 1.0), when q95 = 3.7±0.2 creating small remnant magnetic islands surrounded by weakly stochastic field lines. The stored energy, N , H-mode quality factor and global energy confinement time are unaltered by the magnetic perturbation. At high collisionality (ν* ∼0.5-1), there is no obvious effect of the perturbation on the edge profiles and yet ELMs are suppressed, nearly completely, for up to 9τ E . At low collisionality (ν* <0.1), there is a density pump-out and complete ELM suppression, reminiscent of the DIIID QH- mode. Other differences, specifically in the resonance condition and the magnetic fluctuations, suggest that different mechanisms are at play in the different collisionality regimes. In addition to a description and interpretation of the DIIID data, the application of this method to ELM control on other machines, such as JET and ITER will be discussed. (author)

Matrix models and stochastic growth in Donaldson-Thomas theory

Energy Technology Data Exchange (ETDEWEB)

Szabo, Richard J. [Department of Mathematics, Heriot-Watt University, Colin Maclaurin Building, Riccarton, Edinburgh EH14 4AS, United Kingdom and Maxwell Institute for Mathematical Sciences, Edinburgh (United Kingdom); Tierz, Miguel [Grupo de Fisica Matematica, Complexo Interdisciplinar da Universidade de Lisboa, Av. Prof. Gama Pinto, 2, PT-1649-003 Lisboa (Portugal); Departamento de Analisis Matematico, Facultad de Ciencias Matematicas, Universidad Complutense de Madrid, Plaza de Ciencias 3, 28040 Madrid (Spain)

2012-10-15

We show that the partition functions which enumerate Donaldson-Thomas invariants of local toric Calabi-Yau threefolds without compact divisors can be expressed in terms of specializations of the Schur measure. We also discuss the relevance of the Hall-Littlewood and Jack measures in the context of BPS state counting and study the partition functions at arbitrary points of the Kaehler moduli space. This rewriting in terms of symmetric functions leads to a unitary one-matrix model representation for Donaldson-Thomas theory. We describe explicitly how this result is related to the unitary matrix model description of Chern-Simons gauge theory. This representation is used to show that the generating functions for Donaldson-Thomas invariants are related to tau-functions of the integrable Toda and Toeplitz lattice hierarchies. The matrix model also leads to an interpretation of Donaldson-Thomas theory in terms of non-intersecting paths in the lock-step model of vicious walkers. We further show that these generating functions can be interpreted as normalization constants of a corner growth/last-passage stochastic model.

Matrix models and stochastic growth in Donaldson-Thomas theory

International Nuclear Information System (INIS)

Szabo, Richard J.; Tierz, Miguel

2012-01-01

We show that the partition functions which enumerate Donaldson-Thomas invariants of local toric Calabi-Yau threefolds without compact divisors can be expressed in terms of specializations of the Schur measure. We also discuss the relevance of the Hall-Littlewood and Jack measures in the context of BPS state counting and study the partition functions at arbitrary points of the Kähler moduli space. This rewriting in terms of symmetric functions leads to a unitary one-matrix model representation for Donaldson-Thomas theory. We describe explicitly how this result is related to the unitary matrix model description of Chern-Simons gauge theory. This representation is used to show that the generating functions for Donaldson-Thomas invariants are related to tau-functions of the integrable Toda and Toeplitz lattice hierarchies. The matrix model also leads to an interpretation of Donaldson-Thomas theory in terms of non-intersecting paths in the lock-step model of vicious walkers. We further show that these generating functions can be interpreted as normalization constants of a corner growth/last-passage stochastic model.

Transport in Stochastic Media

International Nuclear Information System (INIS)

Haran, O.; Shvarts, D.; Thieberger, R.

1998-01-01

Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption

Stochastic Stability of Endogenous Growth: Theory and Applications

OpenAIRE

Boucekkine, Raouf; Pintus, Patrick; Zou, Benteng

2015-01-01

We examine the issue of stability of stochastic endogenous growth. First, stochastic stability concepts are introduced and applied to stochastic linear homogenous differen- tial equations to which several stochastic endogenous growth models reduce. Second, we apply the mathematical theory to two models, starting with the stochastic AK model. It’s shown that in this case exponential balanced paths, which characterize optimal trajectories in the absence of uncertainty, are not robust to uncerta...

Stochastic models: theory and simulation.

Energy Technology Data Exchange (ETDEWEB)

Field, Richard V., Jr.

2008-03-01

Many problems in applied science and engineering involve physical phenomena that behave randomly in time and/or space. Examples are diverse and include turbulent flow over an aircraft wing, Earth climatology, material microstructure, and the financial markets. Mathematical models for these random phenomena are referred to as stochastic processes and/or random fields, and Monte Carlo simulation is the only general-purpose tool for solving problems of this type. The use of Monte Carlo simulation requires methods and algorithms to generate samples of the appropriate stochastic model; these samples then become inputs and/or boundary conditions to established deterministic simulation codes. While numerous algorithms and tools currently exist to generate samples of simple random variables and vectors, no cohesive simulation tool yet exists for generating samples of stochastic processes and/or random fields. There are two objectives of this report. First, we provide some theoretical background on stochastic processes and random fields that can be used to model phenomena that are random in space and/or time. Second, we provide simple algorithms that can be used to generate independent samples of general stochastic models. The theory and simulation of random variables and vectors is also reviewed for completeness.

Stochastic simulation of ecohydrological interactions between vegetation and groundwater

Science.gov (United States)

Dwelle, M. C.; Ivanov, V. Y.; Sargsyan, K.

2017-12-01

The complex interactions between groundwater and vegetation in the Amazon rainforest may yield vital ecophysiological interactions in specific landscape niches such as buffering plant water stress during dry season or suppression of water uptake due to anoxic conditions. Representation of such processes is greatly impacted by both external and internal sources of uncertainty: inaccurate data and subjective choice of model representation. The models that can simulate these processes are complex and computationally expensive, and therefore make it difficult to address uncertainty using traditional methods. We use the ecohydrologic model tRIBS+VEGGIE and a novel uncertainty quantification framework applied to the ZF2 watershed near Manaus, Brazil. We showcase the capability of this framework for stochastic simulation of vegetation-hydrology dynamics. This framework is useful for simulation with internal and external stochasticity, but this work will focus on internal variability of groundwater depth distribution and model parameterizations. We demonstrate the capability of this framework to make inferences on uncertain states of groundwater depth from limited in situ data, and how the realizations of these inferences affect the ecohydrological interactions between groundwater dynamics and vegetation function. We place an emphasis on the probabilistic representation of quantities of interest and how this impacts the understanding and interpretation of the dynamics at the groundwater-vegetation interface.

Stochastic diffusion models for substitutable technological innovations

NARCIS (Netherlands)

Wang, L.; Hu, B.; Yu, X.

2004-01-01

Based on the analysis of firms' stochastic adoption behaviour, this paper first points out the necessity to build more practical stochastic models. And then, stochastic evolutionary models are built for substitutable innovation diffusion system. Finally, through the computer simulation of the

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)

Numerical Simulation of the Heston Model under Stochastic Correlation

Directory of Open Access Journals (Sweden)

Long Teng

2017-12-01

Full Text Available Stochastic correlation models have become increasingly important in financial markets. In order to be able to price vanilla options in stochastic volatility and correlation models, in this work, we study the extension of the Heston model by imposing stochastic correlations driven by a stochastic differential equation. We discuss the efficient algorithms for the extended Heston model by incorporating stochastic correlations. Our numerical experiments show that the proposed algorithms can efficiently provide highly accurate results for the extended Heston by including stochastic correlations. By investigating the effect of stochastic correlations on the implied volatility, we find that the performance of the Heston model can be proved by including stochastic correlations.

Stochastic Finite Elements in Reliability-Based Structural Optimization

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Engelund, S.

1995-01-01

Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...... to optimization variables can be performed. A computer implementation is described and an illustrative example is given....

Stochastic hyperfine interactions modeling library

Science.gov (United States)

Zacate, Matthew O.; Evenson, William E.

2011-04-01

The stochastic hyperfine interactions modeling library (SHIML) provides a set of routines to assist in the development and application of stochastic models of hyperfine interactions. The library provides routines written in the C programming language that (1) read a text description of a model for fluctuating hyperfine fields, (2) set up the Blume matrix, upon which the evolution operator of the system depends, and (3) find the eigenvalues and eigenvectors of the Blume matrix so that theoretical spectra of experimental techniques that measure hyperfine interactions can be calculated. The optimized vector and matrix operations of the BLAS and LAPACK libraries are utilized; however, there was a need to develop supplementary code to find an orthonormal set of (left and right) eigenvectors of complex, non-Hermitian matrices. In addition, example code is provided to illustrate the use of SHIML to generate perturbed angular correlation spectra for the special case of polycrystalline samples when anisotropy terms of higher order than A can be neglected. Program summaryProgram title: SHIML Catalogue identifier: AEIF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL 3 No. of lines in distributed program, including test data, etc.: 8224 No. of bytes in distributed program, including test data, etc.: 312 348 Distribution format: tar.gz Programming language: C Computer: Any Operating system: LINUX, OS X RAM: Varies Classification: 7.4 External routines: TAPP [1], BLAS [2], a C-interface to BLAS [3], and LAPACK [4] Nature of problem: In condensed matter systems, hyperfine methods such as nuclear magnetic resonance (NMR), Mössbauer effect (ME), muon spin rotation (μSR), and perturbed angular correlation spectroscopy (PAC) measure electronic and magnetic structure within Angstroms of nuclear probes through the hyperfine interaction. When

Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons.

Science.gov (United States)

Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang

2011-11-01

The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by sampling, which can explain a large number of macroscopic experimental data in neuroscience and cognitive science. But it has turned out to be surprisingly difficult to create a link between these abstract models for stochastic computations and more detailed models of the dynamics of networks of spiking neurons. Here we create such a link and show that under some conditions the stochastic firing activity of networks of spiking neurons can be interpreted as probabilistic inference via Markov chain Monte Carlo (MCMC) sampling. Since common methods for MCMC sampling in distributed systems, such as Gibbs sampling, are inconsistent with the dynamics of spiking neurons, we introduce a different approach based on non-reversible Markov chains that is able to reflect inherent temporal processes of spiking neuronal activity through a suitable choice of random variables. We propose a neural network model and show by a rigorous theoretical analysis that its neural activity implements MCMC sampling of a given distribution, both for the case of discrete and continuous time. This provides a step towards closing the gap between abstract functional models of cortical computation and more detailed models of networks of spiking neurons.

Environmental vs Demographic Stochasticity in Population Growth

OpenAIRE

Braumann, C. A.

2010-01-01

Compares the effect on population growth of envinonmental stochasticity (random environmental variations described by stochastic differential equations) with demographic stochasticity (random variations in births and deaths described by branching processes and birth-and-death processes), in the density-independent and the density-dependent cases.

Role of phase breaking processes on resonant spin transfer torque nano-oscillators

Science.gov (United States)

Sharma, Abhishek; Tulapurkar, Ashwin A.; Muralidharan, Bhaskaran

2018-05-01

Spin transfer torque nano-oscillators (STNOs) based on magnetoresistance and spin transfer torque effects find potential applications in miniaturized wireless communication devices. Using the non-coherent non-equilibrium Green's function spin transport formalism self-consistently coupled with the stochastic Landau-Lifshitz-Gilbert-Slonczewski's equation and the Poisson's equation, we elucidate the role of elastic phase breaking on the proposed STNO design featuring double barrier resonant tunneling. Demonstrating the immunity of our proposed design, we predict that despite the presence of elastic dephasing, the resonant tunneling magnetic tunnel junction structures facilitate oscillator designs featuring a large enhancement in microwave power up to 8μW delivered to a 50Ω load.

Alternative Asymmetric Stochastic Volatility Models

NARCIS (Netherlands)

M. Asai (Manabu); M.J. McAleer (Michael)

2010-01-01

textabstractThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is

First Test of Stochastic Growth Theory for Langmuir Waves in Earth's Foreshock

Science.gov (United States)

Cairns, Iver H.; Robinson, P. A.

1997-01-01

This paper presents the first test of whether stochastic growth theory (SGT) can explain the detailed characteristics of Langmuir-like waves in Earth's foreshock. A period with unusually constant solar wind magnetic field is analyzed. The observed distributions P(logE) of wave fields E for two intervals with relatively constant spacecraft location (DIFF) are shown to agree well with the fundamental prediction of SGT, that P(logE) is Gaussian in log E. This stochastic growth can be accounted for semi-quantitatively in terms of standard foreshock beam parameters and a model developed for interplanetary type III bursts. Averaged over the entire period with large variations in DIFF, the P(logE) distribution is a power-law with index approximately -1; this is interpreted in terms of convolution of intrinsic, spatially varying P(logE) distributions with a probability function describing ISEE's residence time at a given DIFF. Wave data from this interval thus provide good observational evidence that SGT can sometimes explain the clumping, burstiness, persistence, and highly variable fields of the foreshock Langmuir-like waves.

Transport stochastic multi-dimensional media

International Nuclear Information System (INIS)

Haran, O.; Shvarts, D.

1996-01-01

Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors)

Transport stochastic multi-dimensional media

Energy Technology Data Exchange (ETDEWEB)

Haran, O; Shvarts, D [Israel Atomic Energy Commission, Beersheba (Israel). Nuclear Research Center-Negev; Thiberger, R [Ben-Gurion Univ. of the Negev, Beersheba (Israel)

1996-12-01

Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors).

Magnetic resonance imaging

International Nuclear Information System (INIS)

Sigal, R.

1988-01-01

This book is an introduction to magnetic resonance imaging (MRI). The basic principles for the interpretation of MR images are developed. The book is divided into five chapters: introduction, tissue, parameters, acquisition parameters, contribution to diagnosis, and practical management of an MR examination. Eight exercises allow the reader to test the knowledge he has acquired. Signal localization and MR artefacts are reviewed in an appendix

Modelling and application of stochastic processes

CERN Document Server

1986-01-01

The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza­ tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef­ ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side,...

Turbulent response in a stochastic regime

International Nuclear Information System (INIS)

Molvig, K.; Freidberg, J.P.; Potok, R.; Hirshman, S.P.; Whitson, J.C.; Tajima, T.

1981-06-01

The theory for the non-linear, turbulent response in a system with intrinsic stochasticity is considered. It is argued that perturbative Eulerian theories, such as the Direct Interaction Approximation (DIA), are inherently unsuited to describe such a system. The exponentiation property that characterizes stochasticity appears in the Lagrangian picture and cannot even be defined in the Eulerian representation. An approximation for stochastic systems - the Normal Stochastic Approximation - is developed and states that the perturbed orbit functions (Lagrangian fluctuations) behave as normally distributed random variables. This is independent of the Eulerian statistics and, in fact, we treat the Eulerian fluctuations as fixed. A simple model problem (appropriate for the electron response in the drift wave) is subjected to a series of computer experiments. To within numerical noise the results are in agreement with the Normal Stochastic Approximation. The predictions of the DIA for this mode show substantial qualitative and quantitative departures from the observations

Stochastic modeling and analysis of telecoms networks

CERN Document Server

Decreusefond, Laurent

2012-01-01

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

Stochastic modeling of soil salinity

Science.gov (United States)

Suweis, S.; Porporato, A. M.; Daly, E.; van der Zee, S.; Maritan, A.; Rinaldo, A.

2010-12-01

A minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The equations for the probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equations to a single stochastic differential equation (generalized Langevin equation) driven by multiplicative Poisson noise. Generalized Langevin equations with multiplicative white Poisson noise pose the usual Ito (I) or Stratonovich (S) prescription dilemma. Different interpretations lead to different results and then choosing between the I and S prescriptions is crucial to describe correctly the dynamics of the model systems. We show how this choice can be determined by physical information about the timescales involved in the process. We also show that when the multiplicative noise is at most linear in the random variable one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We then apply these results to the generalized Langevin equation that drives the salt mass dynamics. The stationary analytical solutions for the probability density functions of salt mass and concentration provide insight on the interplay of the main soil, plant and climate parameters responsible for long term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant (or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in longterm soil salinization trends, with significant consequences, e.g. for climate change impacts on rain fed agriculture.

Study of the interplay between magnetic shear and resonances using Hamiltonian models for the magnetic field lines

Science.gov (United States)

Firpo, M.-C.; Constantinescu, D.

2011-03-01

The issue of magnetic confinement in magnetic fusion devices is addressed within a purely magnetic approach. Using some Hamiltonian models for the magnetic field lines, the dual impact of low magnetic shear is shown in a unified way. Away from resonances, it induces a drastic enhancement of magnetic confinement that favors robust internal transport barriers (ITBs) and stochastic transport reduction. When low shear occurs for values of the winding of the magnetic field lines close to low-order rationals, the amplitude thresholds of the resonant modes that break internal transport barriers by allowing a radial stochastic transport of the magnetic field lines may be quite low. The approach can be applied to assess the robustness versus magnetic perturbations of general (almost) integrable magnetic steady states, including nonaxisymmetric ones such as the important single-helicity steady states. This analysis puts a constraint on the tolerable mode amplitudes compatible with ITBs and may be proposed as a possible explanation of diverse experimental and numerical signatures of their collapses.

Trajectory averaging for stochastic approximation MCMC algorithms

KAUST Repository

Liang, Faming

2010-10-01

The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400-407]. After five decades of continual development, it has developed into an important area in systems control and optimization, and it has also served as a prototype for the development of adaptive algorithms for on-line estimation and control of stochastic systems. Recently, it has been used in statistics with Markov chain Monte Carlo for solving maximum likelihood estimation problems and for general simulation and optimizations. In this paper, we first show that the trajectory averaging estimator is asymptotically efficient for the stochastic approximation MCMC (SAMCMC) algorithm under mild conditions, and then apply this result to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic approximation MLE algorithm for missing data problems, is also considered in the paper. © Institute of Mathematical Statistics, 2010.

Is human failure a stochastic process?

International Nuclear Information System (INIS)

Dougherty, Ed M.

1997-01-01

Human performance results in failure events that occur with a risk-significant frequency. System analysts have taken for granted the random (stochastic) nature of these events in engineering assessments such as risk assessment. However, cognitive scientists and error technologists, at least those who have interest in human reliability, have, over the recent years, claimed that human error does not need this stochastic framework. Yet they still use the language appropriate to stochastic processes. This paper examines the potential for the stochastic nature of human failure production as the basis for human reliability analysis. It distinguishes and leaves to others, however, the epistemic uncertainties over the possible probability models for the real variability of human performance

Stochastic singular optics

CSIR Research Space (South Africa)

Roux, FS

2013-09-01

Full Text Available Roux Presented at the International Conference on Correlation Optics 2013 Chernivtsi, Ukraine 18-20 September 2013 CSIR National Laser Centre, Pretoria, South Africa – p. 1/24 Contents ⊲ Defining Stochastic Singular Optics (SSO) ⊲ Tools of Stochastic... of vortices: topological charge ±1 (higher order are unstable). Positive and negative vortex densities np(x, y, z) and nn(x, y, z) ⊲ Vortex density: V = np + nn ⊲ Topological charge density: T = np − nn – p. 4/24 Subfields of SSO ⊲ Homogeneous, normally...

Dynamics of non-holonomic systems with stochastic transport

Science.gov (United States)

Holm, D. D.; Putkaradze, V.

2018-01-01

This paper formulates a variational approach for treating observational uncertainty and/or computational model errors as stochastic transport in dynamical systems governed by action principles under non-holonomic constraints. For this purpose, we derive, analyse and numerically study the example of an unbalanced spherical ball rolling under gravity along a stochastic path. Our approach uses the Hamilton-Pontryagin variational principle, constrained by a stochastic rolling condition, which we show is equivalent to the corresponding stochastic Lagrange-d'Alembert principle. In the example of the rolling ball, the stochasticity represents uncertainty in the observation and/or error in the computational simulation of the angular velocity of rolling. The influence of the stochasticity on the deterministically conserved quantities is investigated both analytically and numerically. Our approach applies to a wide variety of stochastic, non-holonomically constrained systems, because it preserves the mathematical properties inherited from the variational principle.

Computer Assisted Instruction (Cain) For Nuclear Magnetic Resonance Spectroscopy

International Nuclear Information System (INIS)

Jaturonrusmee, Wasna; Arthonvorakul, Areerat; Assateranuwat, Adisorn

2005-10-01

A computer assisted instruction program for nuclear magnetic resonance spectroscopy was developed by using Author ware 5.0, Adobe Image Styler 1.0, Adobe Photo shop 7.0 and Flash MX. The contents included the basic theory of 1H and 13C nuclear magnetic resonance (NMR) spectroscopy, the instrumentation of NMR spectroscopy, the two dimensional (2D) NMR spectroscopy and the interpretation of NMR spectra. The program was also provided examples, and exercises, with emphasis on NMR spectra interpretation to determine the structure of unknown compounds and solutions for self study. The questionnaire from students showed that they were very satisfied with the software

Stochastic cooling at Fermilab

International Nuclear Information System (INIS)

Marriner, J.

1986-08-01

The topics discussed are the stochastic cooling systems in use at Fermilab and some of the techniques that have been employed to meet the particular requirements of the anti-proton source. Stochastic cooling at Fermilab became of paramount importance about 5 years ago when the anti-proton source group at Fermilab abandoned the electron cooling ring in favor of a high flux anti-proton source which relied solely on stochastic cooling to achieve the phase space densities necessary for colliding proton and anti-proton beams. The Fermilab systems have constituted a substantial advance in the techniques of cooling including: large pickup arrays operating at microwave frequencies, extensive use of cryogenic techniques to reduce thermal noise, super-conducting notch filters, and the development of tools for controlling and for accurately phasing the system

Stochastic inflation in phase space: is slow roll a stochastic attractor?

Energy Technology Data Exchange (ETDEWEB)

Grain, Julien [Institut d' Astrophysique Spatiale, UMR8617, CNRS, Univ. Paris Sud, Université Paris-Saclay, Bt. 121, Orsay, F-91405 (France); Vennin, Vincent, E-mail: julien.grain@ias.u-psud.fr, E-mail: vincent.vennin@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO13FX (United Kingdom)

2017-05-01