Stochastic resonance for nonequilibrium systems

Lucarini, Valerio

doi:10.1103/physreve.100.062124

Cited by 25 publications

(13 citation statements)

References 68 publications

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“…We conclude noting that a straightforward extension exists to the case of potentials U (r, λ(t )) that depend on time through a prescribed protocol λ(t ) [58,59]. The variations of U should take place on time scales much larger than the largest equilibration time within basins, preserve the number N of minima, and be consistent with the assumptions of weak noise, i.e., U (r (ν) i , λ(t )) − U (r i , λ(t )) T for all i and t. Under this condition, the escape events take place in a fixed force field, and the variations of the potential happen quasistatically while the system fluctuates in a minimum ri .…”

Section: Discussion Of the Weak Forcing Conditionmentioning

confidence: 99%

Local detailed balance across scales: From diffusions to jump processes and beyond

Falasco

Esposito

2021

Phys. Rev. E

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Diffusive dynamics in presence of deep energy minima and weak nongradient forces can be coarse grained into a mesoscopic jump process over the various basins of attraction. Combining standard weak-noise results with a path integral expansion around equilibrium, we show that the emerging transition rates satisfy local detailed balance (LDB). Namely, the log ratio of the transition rates between nearby basins of attractions equals the free-energy variation appearing at equilibrium, supplemented by the work done by the nonconservative forces along the typical transition path. When the mesoscopic dynamics possesses a large-size deterministic limit, it can be further reduced to a jump process over macroscopic states satisfying LDB. The persistence of LDB under coarse graining of weakly nonequilibrium states is a generic consequence of the fact that only dissipative effects matter close to equilibrium.

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Section: Discussion Of the Weak Forcing Conditionmentioning

confidence: 99%

Local detailed balance across scales: From diffusions to jump processes and beyond

Falasco

Esposito

2021

Phys. Rev. E

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“…However, our algorithm is based on temporal statistics and so not applicable, even in the case of quasistatically slow forcing, when snapshot objects closely trace their stationary counterparts in autonomous variants of the system. We remark that the latter setting can provide a generalised theory of stochastic resonance [39], which is relevant to approaches dealing with long paleoclimatic time series [34].…”

Section: Example 2: the Ghil-sellers Energy Balance Climate Model (Gsmentioning

confidence: 99%

An Efficient Algorithm to Estimate the Potential Barrier Height from Noise-Induced Escape Time Data

Bódai

2020

J Stat Phys

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An algorithm is developed for determining the potential barrier height experimentally, provided that we have control over the noise strength σ. We are concerned with the situation when the laboratory or numerical experiment requires large resources of time or computational power, respectively, and wish to find a protocol that provides the best estimate in a given amount of time. The optimal noise strength σ * to use is found to be very simply related to the potential barrier height as: y * = −1 , y = σ −2 − σ −2 a , with some "anchor point" σ −2 a ; and, as a second ingredient, an iterative method is proposed for the estimation. For a numerical verification of the optimality, we apply the algorithm to a simple system of an over-damped particle confined to a double-well potential, when it is feasible to evaluate statistics of the estimator. Subsequently, we also apply it to a high-dimensional case of a diffusive energy balance model, when the potential barrier height-concerning e.g. the warm-to-snowball-climate transition-cannot be determined analytically, but we would have to resort to more sophisticated numerical methods.

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“…The SR system is mainly composed of weak signal, background noise, and nonlinear system [4]. SR theory was first proposed by R.Benzi et al in 1981 [5], which explained a phenomenon that the glacial and warm climates occurred periodically in ancient climate. Then SR theory has been further developed.…”

Section: Introductionmentioning

confidence: 99%

A New Index for Detecting Frequency of Unknown Underwater Weak Signals with Genetic Algorithm

Yu¹,

Li²

2022

IJACSA

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In this paper, a new index is proposed for detecting the frequency of unknown underwater signals based on the stochastic resonance theory. When the received weak signal is input into the stochastic resonance system, first, by frequency analysis, the frequency with the highest amplitude Am of the output signal spectrum is considered as the pre-detection frequency. Then a cosine signal with the pre-detection frequency and unit amplitude is constructed. Define the pre-signal-to-noiseratio as the logarithm of the squared amplitude Am over the mean of signal amplitudes in all other frequencies. The new index is defined as the product of the pre-signal-to-noise-ratio and the correlation coefficient between the received unknown signal and the constructed cosine signal. The new index is featured by taking into account the signal characteristics in both time and frequency domain, and it will yield better signal frequency detection performance. In addition, to improve the time efficiency of the frequency detection, a method to bound the searching range, keyed to the genetic algorithm, of the stochastic resonance system parameters is proposed. The method can be used to detect the frequency of both single frequency and frequency-hopping unknown signals. With the designed new index and system parameter bounding method, the simulations and experiments for the weak underwater unknown signals are conducted. Compared to the piecewise mean value index and weighted power spectral kurtosis index, the new index yields a higher detection probability at varied input signal-to-noise ratios and signal frequencies. With bounding system parameter searching ranges, the time efficiency is improved. The main purpose of this paper is to detect the frequency of unknown underwater weak signals by stochastic resonance system with genetic algorithm. The main contributions are summarized as follows. First, the detection probability of weak signals is improved by stochastic resonance system with the proposed signal detection index than some other indexes. Second, to improve the time efficiency of the signal frequency detection, a method to bound the searching range of system parameters is proposed.

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Stochastic resonance for nonequilibrium systems

Cited by 25 publications

References 68 publications

Local detailed balance across scales: From diffusions to jump processes and beyond

Local detailed balance across scales: From diffusions to jump processes and beyond

An Efficient Algorithm to Estimate the Potential Barrier Height from Noise-Induced Escape Time Data

A New Index for Detecting Frequency of Unknown Underwater Weak Signals with Genetic Algorithm

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