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This overshoot advantage is not seen with the half mean first passage time.
The resulting mean first passage time (MFPT) has 'U' curve dependence on the temperature.
This decrease in variability leads to a substantial increase in the mean first passage time, a measure of the long-term metastability of a stochastic dynamical system.
We also compute the mean first passage time of the unfolded states and show that the computed values correlate with experimentally determined folding rates.
Numerical and stochastic aspects, including mean first passage time and extreme statistics, are discussed in detail and relevant applications are presented in parallel with the theory.
Finally, we note that the mean first passage time can be used as a departure point for measuring the roughness of the landscape.
Similar(15)
Stochastic resonance (SR) phenomena in a time-delayed feedback tristable system driven by Gaussian white noise are investigated by simulating the potential function, mean first-passage time (MFPT), and signal-to-noise ratio (SNR) of the system.
If the user chooses to perform more simulations with the given number of walkers, mean first-passage times are averaged further and standard deviation of this mean over the number of simulations, with the given number of walkers, is calculated.
Then, the dynamical programming equations and their boundary and final time conditions for the control problems of maximizing reliability and of maximizing mean first-passage time are formulated from the averaged Itô equations by using the dynamical programming principle.
Our main results are designed to reveal the fact that the resonant phenomenon of the mean first-passage time (MFPT) takes place in the vegetation growth model because of the interaction of different types of noises and time delay.
It is shown that migration energy is significantly lower near a cluster surface than near a cluster core, and the mean first-passage time for migration of a vacancy decreases with cluster size.
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