Brillouin and Langevin functions


The Brillouin and Langevin functions are a pair of special functions that appear when studying an idealized paramagnetic material in statistical mechanics.

Brillouin function

The Brillouin function is a special function defined by the following equation:


The function is usually applied in the context where x is a real variable and J is a positive integer or half-integer. In this case, the function varies from -1 to 1, approaching +1 as and -1 as.
The function is best known for arising in the calculation of the magnetization of an ideal paramagnet. In particular, it describes the dependency of the magnetization on the applied magnetic field and the total angular momentum quantum number J of the microscopic magnetic moments of the material. The magnetization is given by:
where
Note that in the SI system of units given in Tesla stands for the magnetic field,, where is the auxiliary magnetic field given in A/m and is the permeability of vacuum.
. The relative probability of each of these is given by the Boltzmann factor:
where Z is a normalization constant such that the probabilities sum to unity. Calculating Z, the result is:
All told, the expectation value of the azimuthal quantum number m is
The denominator is a geometric series and the numerator is a type of arithmetico–geometric series, so the series can be explicitly summed. After some algebra, the result turns out to be
With N magnetic moments per unit volume, the magnetization density is
Takacs proposed the following approximation to the inverse of the Brillouin function:
where the constants and are defined to be

Langevin function

In the classical limit, the moments can be continuously aligned in the field and can assume all values. The Brillouin function is then simplified into the Langevin function, named after Paul Langevin:


For small values of, the Langevin function can be approximated by a truncation of its Taylor series:
An alternative better behaved approximation can be derived from the
Lambert's continued fraction expansion of :
For small enough, both approximations are numerically better than a direct evaluation of the actual analytical expression, since the latter suffers from loss of significance.
The inverse Langevin function is defined on the open interval. For small values of, it can be approximated by a truncation of its Taylor series
and by the Padé approximant
Since this function has no closed form, it is useful to have approximations valid for arbitrary values of. One popular approximation, valid on the whole range, has been published by A. Cohen:
This has a maximum relative error of 4.9% at the vicinity of. Greater accuracy can be achieved by using the formula given by R. Jedynak:
valid for. The maximal relative error for this approximation is 1.5% at the vicinity of x = 0.85. Even greater accuracy can be achieved by using the formula given by M. Kröger:
The maximal relative error for this approximation is less than 0.28%. More accurate approximation was reported by R. Petrosyan:
valid for. The maximal relative error for the above formula is less than 0.18%.
New approximation given by R. Jedynak, is the best reported approximant at complexity 11:
valid for. Its maximum relative error is less than 0.076%.
Current state-of-the-art diagram of the approximants to the inverse Langevin function
presents the figure below. It is valid for the rational/Padé approximants,
A recently published paper by R. Jedynak, provides a series of the optimal approximants to the inverse Langevin function. The table below reports the results with correct asymptotic behaviors,.
Comparison of relative errors for the different optimal rational approximations, which were computed with constraints
ComplexityOptimal approximationMaximum relative error
313
40.95
50.56
60.16
70.082

Also recently, an efficient near-machine precision approximant, based on spline interpolations, has been proposed by Benítez and Montáns, where Matlab code is also given to generate the spline-based approximant and to compare many of the previously proposed approximants in all the function domain.

High-temperature limit

When i.e. when is small, the expression of the magnetization can be approximated by the Curie's law:
where is a constant. One can note that is the effective number of Bohr magnetons.

High-field limit

When, the Brillouin function goes to 1. The magnetization saturates with the magnetic moments completely aligned with the applied field: