Synopsis

Synchronized Rolling

Physics 6, s23
Complex networks of disk bearings rotating in unison have an easier time maintaining this synchronization when the mass and radius of each bearing obeys a simple relationship.
N. A. M. Araújo et al., Phys. Rev. Lett. (2013)

Synchronized behavior occurs when different elements (or oscillators) interact in a way that coordinates their movements. A new model of closely packed bearings shows that these mechanical disks act like a complex network of interacting oscillators. The work, presented in Physical Review Letters, finds that bearings tuned with a particular mass-radius relationship will have a stronger (more stable) synchronization.

Common examples of synchronization include contraction of heart muscles and the rhythmic unison of musicians. Recent interest in synchronization focuses on which interactions might enhance or reduce coordination. One prediction is that a synchronized state is most stable when the interaction strength is inversely proportional to the number of interacting partners that a particular oscillator has.

To provide a test bed for this theory, Nuno Araújo of the Swiss Federal Institute of Technology (ETH) in Zurich and his colleagues turned to complex bearing networks. They devised a model in which two-dimensional bearings of various sizes fit together to fill a given volume. This system is synchronized when all the elements have the same tangential velocity (i.e., no slipping). The team calculated how such a synchronized state responds to perturbations and found the most stable case was when the mass of each bearing was directly proportional to its radius. As such, larger bearings, which typically touch (interact with) more of their neighbors, have a larger moment of inertia and thus are less affected by these interactions. In other words, elements with more partners compensate with weaker interactions, just as predicted. – Michael Schirber


Subject Areas

Complex Systems

Related Articles

Assessing the Brain at a Range of Frequencies
Biological Physics

Assessing the Brain at a Range of Frequencies

A new frequency-based analysis of recordings from neurons in the brain may give insight into brain pathologies such as Parkinson’s disease. Read More »

<i>Nobel Prize:</i> Mimicking Human Intelligence with Neural Networks
Complex Systems

Nobel Prize: Mimicking Human Intelligence with Neural Networks

The 2024 Nobel Prize in Physics honors pioneering work on artificial neural networks, which provided the foundation for many of the artificial intelligence technologies in use today. Read More »

Identifying Phases in Low-Speed Human Movement
Complex Systems

Identifying Phases in Low-Speed Human Movement

By observing the motion of preschool children, researchers have developed a thermodynamic description of human movement that pinpoints collective phases emerging when social interactions are strong. Read More »

More Articles