Bose–Einstein statistics

In statistical mechanics, Bose-Einstein statistics (or more colloquially B-E statistics) determines the statistical distribution of identical indistinguishable bosons over the energy states in thermal equilibrium.

Concept
Bosons, unlike fermions, are not subject to the Pauli exclusion principle: an unlimited number of particles may occupy the same state at the same time. This explains why, at low temperatures, bosons can behave very differently from fermions; all the particles will tend to congregate together at the same lowest-energy state, forming what is known as a Bose–Einstein condensate.

B-E statistics was introduced for photons in 1920 by Bose and generalized to atoms by Einstein in 1924.

The expected number of particles in an energy state i for B-E statistics is:



n_i = \frac {g_i} {e^{(\varepsilon_i-\mu)/kT} - 1} $$

with $$\varepsilon_i > \mu$$ and where:


 * ni is the number of particles in state i
 * gi is the degeneracy of state i
 * εi is the energy of the i-th state
 * μ is the chemical potential
 * k is Boltzmann's constant
 * T is absolute temperature

This reduces to M-B statistics for energies ( εi &minus; μ ) >> kT.

History
In the early 1920s Satyendra Nath Bose, a professor of University of Dhaka was intrigued by Einstein's theory of light waves being made of particles called photons. Bose was interested in deriving Planck's radiation formula, which Planck obtained largely by guessing. In 1900 Max Planck had derived his formula by manipulating the math to fit the empirical evidence. Using the particle picture of Einstein, Bose was able to derive the radiation formula by systematically developing a statistics of massless particles without the constraint of particle number conservation. Bose derived Planck's Law of Radiation by proposing different states for the photon. Instead of statistical independence of particles, Bose put particles into cells and described statistical independence of cells of phase space. Such systems allow two polarization states, and exhibit totally symmetric wavefunctions.

He developed a statistical law governing the behaviour pattern of photons quite successfully. However, he was not able to publish his work; no journals in Europe would accept his paper, being unable to understand it. Bose sent his paper to Einstein, who saw the significance of it and used his influence to get it published.

A derivation of the Bose–Einstein distribution
Suppose we have a number of energy levels, labeled by index $$\displaystyle i$$, each level having energy $$\displaystyle \varepsilon_i$$ and containing a total of $$\displaystyle n_i$$ particles. Suppose each level contains $$\displaystyle g_i$$ distinct sublevels, all of which have the same energy, and which are distinguishable. For example, two particles may have different momenta, in which case they are distinguishable from each other, yet they can still have the same energy. The value of $$\displaystyle g_i$$ associated with level $$\displaystyle i$$ is called the "degeneracy" of that energy level. Any number of bosons can occupy the same sublevel.

Let $$\displaystyle w(n,g)$$ be the number of ways of distributing $$\displaystyle n$$ particles among the $$\displaystyle g$$ sublevels of an energy level. There is only one way of distributing $$\displaystyle n$$ particles with one sublevel, therefore $$\displaystyle w(n,1)=1$$. It is easy to see that there are $$\displaystyle (n+1)$$ ways of distributing $$\displaystyle n$$ particles in two sublevels which we will write as:



w(n,2)=\frac{(n+1)!}{n!1!}. $$

With a little thought (See Notes below) it can be seen that the number of ways of distributing $$\displaystyle n$$ particles in three sublevels is


 * $$w(n,3) = w(n,2) + w(n-1,2) + \cdots + w(1,2) + w(0,2)

$$ so that



w(n,3)=\sum_{k=0}^n w(n-k,2) = \sum_{k=0}^n\frac{(n-k+1)!}{(n-k)!1!}=\frac{(n+2)!}{n!2!} $$

where we have used the following theorem involving binomial coefficients:



\sum_{k=0}^n\frac{(k+a)!}{k!a!}=\frac{(n+a+1)!}{n!(a+1)!}. $$

Continuing this process, we can see that $$\displaystyle w(n,g)$$ is just a binomial coefficient (See Notes below)



w(n,g)=\frac{(n+g-1)!}{n!(g-1)!}. $$

The number of ways that a set of occupation numbers $$\displaystyle n_i$$ can be realized is the product of the ways that each individual energy level can be populated:



W = \prod_i w(n_i,g_i) = \prod_i \frac{(n_i+g_i-1)!}{n_i!(g_i-1)!} \approx\prod_i \frac{(n_i+g_i)!}{n_i!(g_i)!} $$

where the approximation assumes that $$g_i \gg 1$$. Following the same procedure used in deriving the Maxwell–Boltzmann statistics, we wish to find the set of $$\displaystyle n_i$$ for which $$\displaystyle W$$ is maximised, subject to the constraint that there be a fixed number of particles, and a fixed energy. The maxima of $$\displaystyle W$$ and $$\displaystyle \ln(W)$$ occur at the value of $$\displaystyle N_i$$ and, since it is easier to accomplish mathematically, we will maximise the latter function instead. We constrain our solution using Lagrange multipliers forming the function:



f(n_i)=\ln(W)+\alpha(N-\sum n_i)+\beta(E-\sum n_i \varepsilon_i) $$

Using the $$g_i \gg 1$$ approximation and using Stirling's approximation for the factorials $$\left(\ln(x!)\approx x\ln(x)-x\right)$$ gives


 * $$f(n_i)=\sum_i (n_i + g_i) \ln(n_i + g_i) - n_i \ln(n_i) - g_i \ln (g_i) +\alpha\left(N-\sum n_i\right)+\beta\left(E-\sum n_i \varepsilon_i\right).

$$

Taking the derivative with respect to $$\displaystyle n_i$$, and setting the result to zero and solving for $$\displaystyle n_i$$, yields the Bose–Einstein population numbers:



n_i = \frac{g_i}{e^{\alpha+\beta \varepsilon_i}-1}. $$

It can be shown thermodynamically that

$$\displaystyle \beta = \frac{1}{kT}$$, where

$$\displaystyle k$$ is Boltzmann's constant and

$$\displaystyle T$$ is the temperature.

It can also be shown that

$$\displaystyle \alpha = - \frac{\mu}{kT}$$, where

$$\displaystyle \mu$$ is the chemical potential, so that finally:



n_i = \frac{g_i}{e^{(\varepsilon_i-\mu)/kT}-1}. $$

Note that the above formula is sometimes written:



n_i = \frac{g_i}{e^{\varepsilon_i/kT}/z-1}, $$

where $$\displaystyle z=\exp(\mu/kT)$$ is the absolute activity.

Information Retrieval
In recent years, Bose Einstein statistics have also been used as a method for term weighting in information retrieval. The method is one of a collection of DFR ("Divergence From Randomness") models, the basic notion being that Bose Einstein statistics may be a useful indicator in cases where a particular term and a particular document have a significant relationship that would not have occurred purely by chance. Source code for implementing this model is available from the Terrier project at the University of Glasgow.