Bell polynomials

In combinatorial mathematics, the Bell polynomials, named in honor of Eric Temple Bell, are a triangular array of polynomials given by

B_{n,k}(x_1,x_2,\dots,x_{n-k%2B1})
=\sum{n! \over j_1!j_2!\cdots j_{n-k%2B1}!} \left({x_1\over 1!}\right)^{j_1}\left({x_2\over 2!}\right)^{j_2}\cdots\left({x_{n-k%2B1} \over (n-k%2B1)!}\right)^{j_{n-k%2B1}},

where the sum is taken over all sequences j1, j2, j3, ..., jn−k+1 of non-negative integers such that

j_1%2Bj_2%2B\cdots = k\quad\mbox{and}\quad j_1%2B2j_2%2B3j_3%2B\cdots=n.

Contents

Complete Bell polynomials

The sum

B_n(x_1,\dots,x_n)=\sum_{k=1}^n B_{n,k}(x_1,x_2,\dots,x_{n-k%2B1})

is sometimes called the nth complete Bell polynomial. In order to contrast them with complete Bell polynomials, the polynomials Bn, k defined above are sometimes called "partial" Bell polynomials.

The complete Bell polynomials satisfy the following identity

B_n(x_1,\dots,x_n) = \det\begin{bmatrix}x_1 & {n-1 \choose 1} x_2 & {n-1 \choose 2}x_3 & {n-1 \choose 3} x_4 & {n-1 \choose 4} x_5 & \cdots & \cdots & x_n \\ \\ -1 & x_1 & {n-2 \choose 1} x_2 & {n-2 \choose 2} x_3 & {n-2 \choose 3} x_4 & \cdots & \cdots & x_{n-1} \\ \\ 0 & -1 & x_1 & {n-3 \choose 1} x_2 & {n-3 \choose 2} x_3 & \cdots & \cdots & x_{n-2} \\ \\ 0 & 0 & -1 & x_1 & {n-4 \choose 1} x_2 & \cdots & \cdots & x_{n-3} \\ \\ 0 & 0 & 0 & -1 & x_1 & \cdots & \cdots & x_{n-4} \\ \\ 0 & 0 & 0 & 0 & -1 & \cdots & \cdots & x_{n-5} \\ \\ \vdots & \vdots & \vdots & \vdots & \vdots & \ddots & \ddots & \vdots \\ \\ 0 & 0 & 0 & 0 & 0 & \cdots & -1 & x_1 \end{bmatrix}.

Combinatorial meaning

If the integer n is partitioned into a sum in which "1" appears j1 times, "2" appears j2 times, and so on, then the number of partitions of a set of size n that collapse to that partition of the integer n when the members of the set become indistinguishable is the corresponding coefficient in the polynomial.

Examples

For example, we have

B_{6,2}(x_1,x_2,x_3,x_4,x_5)=6x_5x_1%2B15x_4x_2%2B10x_3^2

because there are

6 ways to partition a set of 6 as 5 + 1,
15 ways to partition a set of 6 as 4 + 2, and
10 ways to partition a set of 6 as 3 + 3.

Similarly,

B_{6,3}(x_1,x_2,x_3,x_4)=15x_4x_1^2%2B60x_3x_2x_1%2B15x_2^3

because there are

15 ways to partition a set of 6 as 4 + 1 + 1,
60 ways to partition a set of 6 as 3 + 2 + 1, and
15 ways to partition a set of 6 as 2 + 2 + 2.

Properties

Stirling numbers and Bell numbers

The value of the Bell polynomial Bn,k(x1,x2,...) when all xs are equal to 1 is a Stirling number of the second kind:

B_{n,k}(1,1,\dots)=S(n,k)=\left\{{n\atop k}\right\}.

The sum

\sum_{k=1}^n B_{n,k}(1,1,1,\dots) = \sum_{k=1}^n \left\{{n\atop k}\right\}

is the nth Bell number, which is the number of partitions of a set of size n.

Convolution identity

For sequences xn, yn, n = 1, 2, ..., define a sort of convolution by:

(x \diamondsuit y)_n = \sum_{j=1}^{n-1} {n \choose j} x_j y_{n-j}.

Note that the bounds of summation are 1 and n − 1, not 0 and n .

Let x_n^{k\diamondsuit}\, be the nth term of the sequence

\displaystyle\underbrace{x\diamondsuit\cdots\diamondsuit x}_{k\ \mathrm{factors}}.\,

Then

B_{n,k}(x_1,\dots,x_{n-k%2B1}) = {x_{n}^{k\diamondsuit} \over k!}.\,

For example, let us compute B_{4,3}(x_1,x_2) . We have

x = ( x_1 \ , \ x_2 \ , \ x_3 \ , \ x_4 \ , \dots )
x \diamondsuit x = ( 0,\ 2 x_1^2 \ ,\ 6 x_1 x_2 \ , \ 8 x_1 x_3 %2B 6 x_2^2 \ , \dots )
x \diamondsuit x \diamondsuit x = ( 0 \ ,\ 0 \ , \ 6 x_1^3 \ , \ 36 x_1^2 x_2 \ , \dots )

and thus,

B_{4,3}(x_1,x_2) = \frac{ ( x \diamondsuit x \diamondsuit x)_4 }{3!} = 6 x_1^2 x_2.

Applications of Bell polynomials

Faà di Bruno's formula

Main article: Faà di Bruno's formula

Faà di Bruno's formula may be stated in terms of Bell polynomials as follows:

{d^n \over dx^n} f(g(x)) = \sum_{k=0}^n f^{(k)}(g(x)) B_{n,k}\left(g'(x),g''(x),\dots,g^{(n-k%2B1)}(x)\right).

Similarly, a power-series version of Faà di Bruno's formula may be stated using Bell polynomials as follows. Suppose

f(x)=\sum_{n=1}^\infty {a_n \over n!} x^n \qquad \mathrm{and} \qquad g(x)=\sum_{n=1}^\infty {b_n \over n!} x^n.

Then

g(f(x)) = \sum_{n=1}^\infty {\sum_{k=1}^{n} b_k B_{n,k}(a_1,\dots,a_{n-k%2B1}) \over n!} x^n.

In particular, the complete Bell polynomials appear in the exponential of a formal power series:

\exp\left(\sum_{n=1}^\infty {a_n \over n!} x^n \right) = \sum_{n=0}^\infty {B_n(a_1,\dots,a_n) \over n!} x^n.

Moments and cumulants

The sum

B_n(\kappa_1,\dots,\kappa_n)=\sum_{k=1}^n B_{n,k}(\kappa_1,\dots,\kappa_{n-k%2B1})

is the nth moment of a probability distribution whose first n cumulants are κ1, ..., κn. In other words, the nth moment is the nth complete Bell polynomial evaluated at the first n cumulants.

Representation of polynomial sequences of binomial type

For any sequence a1, a2, a3, ... of scalars, let

p_n(x)=\sum_{k=1}^n B_{n,k}(a_1,\dots,a_{n-k%2B1}) x^k.

Then this polynomial sequence is of binomial type, i.e. it satisfies the binomial identity

p_n(x%2By)=\sum_{k=0}^n {n \choose k} p_k(x) p_{n-k}(y)

for n ≥ 0. In fact we have this result:

Theorem: All polynomial sequences of binomial type are of this form.

If we let

h(x)=\sum_{n=1}^\infty {a_n \over n!} x^n

taking this power series to be purely formal, then for all n,

h^{-1}\left( {d \over dx}\right) p_n(x) = n p_{n-1}(x).

Software

See also

References