Synopsis

Star-Shaped Waves

Physics 6, s34
Vertical shaking of a liquid-filled container can generate a standing wave pattern of stars and polygons.
J. Rajchenbach et al., Phys. Rev. Lett. (2013)

The ocean can produce exotic wave forms, such as “freak” waves, when normal waves combine in just the right way. These unusual wave patterns can—theoretically—take on a variety of different shapes, but researchers have so far only managed to produce a few distinct cases in the lab. As reported in Physical Review Letters, Jean Rajchenbach and colleagues at CNRS and the University of Nice in France have produced star- and polygon-shaped standing waves by vertically shaking a vessel filled with liquid oil.

Ocean waves and similar fluid waves are called surface gravity waves because the main restoring force is gravity. The basic equations describing these waves are nonlinear, which means that waves of different wavelengths can interact with each other and, under certain conditions, form unusual patterns, such as long-lasting solitary waves (solitons), U-shaped, and X-shaped waves. Such wave forms sometimes have important counterparts in other scientific domains, from optics to cold-atom physics.

To explore novel nonlinear possibilities, Rajchenbach and his collaborators placed a thin layer of silicon oil in a flat vessel and shook it up and down at a rate of around 10 hertz. They initially observed circularly symmetric standing waves, but as they increased the shaking amplitude, the wave crests formed edges and vertices in an alternating pattern of five-pointed stars and pentagons. Varying the fluid depth and the shaking parameters produced other star-polygon shapes with three, four, and six sides. However, the vessel shape was not a factor, as identical patterns appeared in both circular and rectangular vessels. The authors explain how the observed shapes could arise from a resonant nonlinear interaction between three different waves generated by the shaking action. – Michael Schirber


Subject Areas

Nonlinear Dynamics

Related Articles

Time Delays Improve Performance of Certain Neural Networks
Computational Physics

Time Delays Improve Performance of Certain Neural Networks

Both the predictive power and the memory storage capability of an artificial neural network called a reservoir computer increase when time delays are added into how the network processes signals, according to a new model. Read More »

The Neuron vs the Synapse: Which One Is in the Driving Seat?
Complex Systems

The Neuron vs the Synapse: Which One Is in the Driving Seat?

A new theoretical framework for plastic neural networks predicts dynamical regimes where synapses rather than neurons primarily drive the network’s behavior, leading to an alternative candidate mechanism for working memory in the brain. Read More »

Nonreciprocal Frustration Meets Geometrical Frustration
Nonlinear Dynamics

Nonreciprocal Frustration Meets Geometrical Frustration

New theoretical work establishes an analogy between systems that are dynamically frustrated, such as glasses, and thermodynamic systems whose members have conflicting goals, such as predator–prey ecosystems. Read More »

More Articles