An alternate protocol to achieve stochastic and deterministic resonances

Stochastic resonance via parametric adaptation: Experiments and numerics

In contrast with the conventionally observed mechanism of stochastic resonance (SR) wherein the level of additive noise is systematically varied with a fixed set-point parameter, in this work we report the emergence of the SR phenomena in an electrochemical system maintaining the same level of noise and varying the parametric distance from a homoclinic bifurcation inherent to the system. The experimental system involves the corrosion of a metal disk in an acidic medium under potentiostatic conditions. The applied potential is used as a control parameter and the anodic current generated during the electrodissolution of the metal is the accessible system variable. In the presence of noise, it was observed that the system was able to enhance its output's fidelity with a weak subthreshold input signal when the set point was kept at an optimal parametric distance from the bifurcation. Numerical simulations were performed on a model for this system to corroborate the experimental observations. This type of SR may be critical in scenarios where a biological entity has control only on its sensory parameters and not on the environmental noise amplitude.

Intrinsic stochastic resonance via set-point variation

In the present paper, the possibility of invoking stochastic resonance (SR, periodic and aperiodic) by regulating the operating value of an appropriate parameter is explored. The operating values of these parameters are defined as the set point of the system throughout the present paper. Brusselator, a mathematical model [I. Prigogine and R. Lefever, J. Chem. Phys. 48, 1695 (1968)JCPSA60021-960610.1063/1.1668896] of nonlinear chemical reactions, is used for this purpose. We consider the effect of intrinsic noise in the Brusselator due to the Markovian nature of the chemical reactions. The stochastic time evolution is studied using the Gillespie algorithm [D. T. Gillespie, J. Comput. Phys. 22, 403 (1976)JCTPAH0021-999110.1016/0021-9991(76)90041-3], which is an exact stochastic simulation algorithm. We analyze the dependence of the resonance point on both the strength of the intrinsic noise as well as the distance from the bifurcation point. Subsequently, the phenomena of SR is explored using both periodic and aperiodic stimulus. It was found that, for a given system size, in both cases, SR is achieved by variation of the set point. Set-point variation can be achieved by regulating either the source concentration or the rate constants. Resonance is observed in both cases. However, this resonance occurs at different values of the set point, even with a fixed system size. This is clearly seen in the set-point versus system-size plane, where the resonance line has different slopes for the two scenarios. Our semianalytic treatment points to the fact that for a given system size intrinsic noise is affected differently for different methods involving the variation of the set point. This is explained by writing the corresponding chemical Langevin equation and comparing the various intrinsic noise sources.