Noise is generally a nuisance that drowns out small signals. However, it is known that living organisms find it easier to detect predators in noisy environments since noise enhances the sensitivity of the sensory organs. This phenomenon, called stochastic resonance, is considered to be of great use for engineering devices and addressing noise problems in various other fields. However, there have not been convincing explanations as to why noise enhances sensitivity to weak signals since initial report of the phenomenon in 1981.
One stumbling block preventing researchers from fully understanding the phenomenon is the complexity in nonlinear theories involving friction and fluctuation, both considered to be essential for the phenomenon.
To address this problem, the team, comprising Hokkaido University Professor Seiya Kasai, Associate Professor Akihisa Ichiki of Nagoya University, and Senior Researcher Yukihiro Tadokoro of Toyota Central R&D Labs., Inc., established a simple model that excluded friction force, a parameter that they consider negligible in nano- and molecular-scale systems.
The researchers found correlations between sensitivity and noise in a bistable system, a nonlinear system that has two stable states and allows the transition between them depending on input values, like a seesaw. They also figured out the role of white Gaussian noise, the most standard noise widely found in the natural world.