Intrinsic stochastic resonance via set-point variation.

Area of Science:

• Nonlinear dynamics
• Chemical kinetics
• Stochastic processes

Background:

• The Brusselator model is a key mathematical framework for studying nonlinear chemical reactions.
• Stochastic resonance (SR) is a phenomenon where a non-zero level of noise can enhance the detection of weak signals.
• Understanding intrinsic noise is crucial for accurately modeling chemical systems.

Purpose of the Study:

• To investigate the possibility of inducing stochastic resonance (SR) by regulating system parameters in the Brusselator model.
• To explore the effects of intrinsic noise on SR under both periodic and aperiodic stimuli.
• To analyze how set-point variations influence the resonance phenomenon.

Main Methods:

• Utilized the Brusselator model, a mathematical representation of nonlinear chemical reactions.
• Employed the Gillespie algorithm for exact stochastic simulation of chemical reaction dynamics.
• Analyzed the dependence of the resonance point on intrinsic noise strength and proximity to bifurcation points.
• Investigated SR using both periodic and aperiodic external stimuli.

Main Results:

• Stochastic resonance (SR) was successfully induced in the Brusselator model by varying the set point, which can be adjusted via source concentration or rate constants.
• Resonance was observed for both periodic and aperiodic stimuli, occurring at different set-point values even for a fixed system size.
• The resonance lines in the set-point versus system-size plane exhibited different slopes for periodic and aperiodic scenarios.
• Semianalytic treatment revealed that intrinsic noise is affected differently by various set-point variation methods for a given system size.

Conclusions:

• Set-point regulation is an effective method for achieving stochastic resonance in the Brusselator model.
• The interplay between intrinsic noise, set-point variation, and stimulus type significantly impacts SR.
• Different methods of set-point variation lead to distinct effects on intrinsic noise, influencing SR outcomes.