Brownian motion

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This article is about the physical phenomenon. For the sports team, please see Brownian Motion (Ultimate).

Image:BrownianMotion.png

The term Brownian motion (in honor of the botanist Robert Brown) refers to either

  1. The physical phenomenon that minute particles immersed in a fluid move about randomly; or
  2. The mathematical models used to describe those random movements.

The mathematical model can also be used to describe many phenomena not resembling (other than mathematically) the random movements of minute particles. An often quoted example is stock market fluctuations. Another example is the evolution of physical characteristics in the fossil record.

Brownian motion is among the simplest stochastic processes on a continuous domain, and it is a limit of both simpler (see random walk) and more complicated stochastic processes. This universality is closely related to the universality of the normal distribution. In both cases, it is often mathematical convenience rather than accuracy as models that motivates their use. All three quoted examples of Brownian motion are cases of this:

  1. It has been argued that Lévy flights are a more accurate, if still imperfect, model of stock-market fluctuations.
  2. The physical Brownian motion can be modelled more accurately by a more general diffusion process.
  3. The dust hasn't settled yet on what the best model for the fossil record is, even after correcting for non-Gaussian data.

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History

Jan Ingenhousz made some observations of the irregular motion of carbon dust on alcohol in 1765 but Brownian motion is generally regarded as having been discovered by the botanist Robert Brown in 1827. The story goes that Brown was studying pollen particles floating in water under the microscope. He then observed minute particles within vacuoles in the pollen grains executing the jittery motion that now bears his name. By doing the same with particles of dust, he was able to rule out that the motion was due to pollen being "alive", but it remained to explain the origin of the motion. The first to give a theory of Brownian motion was Louis Bachelier in 1900 in his PhD thesis "The theory of speculation", but it was Albert Einstein's independent solution of the problem in his 1905 paper that brought the solution to the attention of physicists. (Bachelier's thesis presented a stochastic analysis of the stock and option markets.)

At that time the atomic nature of matter was still a controversial idea. Einstein and Marian Smoluchowski observed that, if the kinetic theory of fluids was right, then the molecules of water would move at random and so a small particle would receive a random number of impacts of random strength and from random directions in any short period of time. This random bombardment by the molecules of the fluid would cause a sufficiently small particle to move in exactly the way described by Brown. Theodor Svedberg made important demonstrations of Brownian motion in colloids and Felix Ehrenhaft, of particles of silver in air. Jean Perrin carried out experiments to test the new mathematical models, and his published results finally put an end two thousand year-old dispute about the reality of atoms and molecules.

The atomic dispute had started with Democritus (about 460 BCE or 490 BCE) and Anaxagoras (born about 500 BCE, the teacher of Socrates). The philosophers had opposing atomic theories, distinguished by the question of whether, for example, a drop of water could be divided repeatedly without limit, with each sub-division preserving the properties of the original. The atomic school of Democritus held that the subdivisions could not continue indefinitely. The doctrine of homoiomereia (homogeneity) followed by Anaxagoras held that the division of the drop could continue without end, because the size of a body did not reflect the nature of its substance.[1]

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Intuitive metaphor for Brownian motion

Consider a big balloon (of, say, 10 meters in diameter). Imagine now this big balloon in a football stadium (or any wide crowded place) among the supporters. The balloon is so big that it lies on top of many supporters. Because they are excited, these supporters hit the balloon at different times and in different directions (all possible directions actually). In the end, the balloon is pushed in all directions, so it should not move on average. Consider now the force exerted at a certain time. We might have 20 supporters pushing more to the right, and 21 other supporters pushing more to the left. In this case, the forces exerted from the left side and the right side are unbalanced in favour of the left side, then the balloon will move slightly to the left. This unbalance exists at all times, and favours each time a random direction. If we look at this situation from above (from a helicopter for example), so that we cannot see the supporters, but we see the big balloon as a small object animated by an erratic movement. Now return to Brown’s pollen particle swimming randomly in water. A water molecule is about 1 nm, where the pollen particle is roughly 1 µm in diameter,1000 times bigger than a water molecule . So the pollen particle can be considered as a very big balloon constantly pushed by water molecules, and these molecules are excited by temperature. In the end, the Brownian motion of particles in a liquid is due to the instantaneous unbalance in the force exerted by the small liquid molecules on the particle.

A Java applet animating this idea is available here

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Description of the mathematical model

Mathematically, Brownian motion is a Wiener process in which the conditional probability distribution of the particle's position at time t + dt, given that its position at time t is p, is a normal distribution with a mean of p + μ dt and a variance of σ2 dt; the parameter μ is the drift velocity, and the parameter σ2 is the power of the noise. These properties clearly establish that Brownian motion is Markovian (i.e. it satisfies the Markov property). Brownian motion is related to the random walk problem and it is generic in the sense that many different stochastic processes reduce to Brownian motion in suitable limits.

In fact, the Wiener process is the only time-homogeneous stochastic process with independent increments that has continuous trajectories. These are all reasonable approximations to the physical properties of Brownian motion.

The mathematical theory of Brownian motion has been applied in contexts ranging far beyond the movement of particles in fluids. For example, in the modern theory of option pricing, asset classes are sometimes modeled as if they move according to a closely related process, geometric Brownian motion.

It turns out that the Wiener process is not a physically realistic model of the motion of Brownian particles. More sophisticated formulations of the problem have led to the mathematical theory of diffusion processes. The accompanying equation of motion is called the Langevin equation or the Fokker-Planck equation depending on whether it is formulated in terms of random trajectories or probability densities.

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Modelling the Brownian motion using differential equations

The equations governing Brownian motion related slightly differently to the each of the two definitions of brownian motion given at the start of this article.

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Mathematical Brownian motion

For a particle experiencing a brownian motion corresponding to the mathematical definition, the equation governing the time evolution of the probability density function associated to the position of the Brownian particle is the diffusion equation, a partial differential equation.

The time evolution of the position of the Brownian particle itself can be described approximately by Langevin equation, an equation which involves a random force field representing the effect of the thermal fluctuations of the solvent on the Brownian particle. On long timescales, the mathematical Brownian motion is well described by Langevin equation. On small timescales, Inertial effects are prevalent in Langevin equation. However the mathematical brownian motion is exempt of such inertial effects. Note that inertial effects have to be considered in Langevin equation, otherwise the equation becomes singular, so that simply removing the inertia term from this equation would not yield an exact description, but rather a singular behavior in which the particle doesn't move at all...

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Physical Brownian motion

The diffusion equation yields an approximation of the time evolution of the probability density function associated to the position of the particle undergoing a Brownian movement under the physical definition. The approximation is valid on long timescales (see Langevin equation for details).

The time evolution of the position of the Brownian particle itself is best described using Langevin equation, an equation which involves a random force field representing the effect of the thermal fluctuations of the solvent on the particle.

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See also

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References

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Video 

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External links

ca:Moviment brownià cs:Brownův pohyb de:Brownsche Molekularbewegung es:Movimiento browniano fr:Mouvement brownien it:Moto browniano lt:Brauno judėjimas nl:Brownse beweging ja:ブラウン運動 no:Brownsk bevegelse nn:Brownske rørsler pl:Ruchy Browna pt:Movimento browniano ru:Броуновское движение sk:Brownov pohyb sl:Brownovo gibanje su:Gerak Brown fi:Brownin liike sv:Brownsk rörelse ta:பிரௌனியன் இயக்கம் zh:布朗運動

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