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Predicting the unpredictable

Modeling random motion may sound like an oxymoron. But Associate Professor of Physics Jay Tang is using the predictability of randomness to explain the movement of bacteria swimming in water. His work could have implications in public health or environmental studies.

The model, known as Brownian motion, has significant historical roots, dating back to 1827 when Robert Brown observed particles of pollen drifting in a random pattern when he looked at them under a microscope. The term Brownian motion was later coined to describe the random movement of particles in a liquid or gas, and several physicists, including Albert Einstein, helped develop a mathematical model to describe this motion.

Now, over a hundred years later, Tang said he is using a "physics angle to explain basic biology and make predictions." Using new imaging processes, Tang and his team were able to see Brownian motion in the way bacteria move through water.

The team observed that the bacteria make tighter turns when they are near the water's surface, and it occurred to the researchers that in addition to the usual physical forces acting on the bacteria, Brownian motion might also contribute to the observed movement.

The mathematical model is versatile, demonstrating everything from stock market fluctuations to the way a drunk person walks, but Tang said he is one of the first to use it to explain swimming patterns of bacteria, which could have important consequences for public health.

The reason that Brownian motion plays a role in the swimming patterns of bacteria but not those of humans is the difference in scale. The effect is caused by individual water molecules knocking into the swimming object, changing the direction of a bacterium. A swimming person is too large for this effect to take place. For a person to experience this effect would be like trying to walk in a straight line while strong gusts of wind are blowing from all directions.

Using their observations, Tang and his team were able to create a model that could predict the movement of bacteria. Particularly interesting to the researchers was the combination of predictable and random processes, which allowed them to simulate a real-life situation.

"It is intriguing because Brownian motion is random (and) thermodynamics is predictable ... (but) we found a coupling," Tang said.

In his lab, researchers have been studying the swimming patterns of a particular bacterium called Caulobacter crescentus, which is one of the "simplest systems to study," according to Tang, because it only has one flagellum, or tail. While Tang said that this bacterium is the "most common contaminant in water," it is not harmful to humans.

Studying this system is important, Tang said, because "if you understand this, you can understand other species that are more dangerous," which is important for "public health and environmental issues."




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