The Wedderburn–Etherington numbers are an integer sequence named for Ivor Malcolm Haddon Etherington[1] [2] and Joseph Wedderburn[3] that can be used to count certain kinds of binary trees. The first few numbers in the sequence are
0, 1, 1, 1, 2, 3, 6, 11, 23, 46, 98, 207, 451, 983, 2179, 4850, 10905, 24631, 56011, ...
These numbers can be used to solve several problems in combinatorial enumeration. The nth number in the sequence (starting with the number 0 for n = 0)counts
xn
x5
x(x(x(xx)))
x((xx)(xx))
(xx)(x(xx))
x
x
xn
The Wedderburn–Etherington numbers may be calculated using the recurrence relation
a2n-1
n-1 | |
=\sum | |
i=1 |
aia2n-i-1
a2n=
an(an+1) | |
2 |
n-1 | |
+\sum | |
i=1 |
aia2n-i
a1=1
In terms of the interpretation of these numbers as counting rooted binary trees with n leaves, the summation in the recurrence counts the different ways of partitioning these leaves into two subsets, and of forming a subtree having each subset as its leaves. The formula for even values of n is slightly more complicated than the formula for odd values in order to avoid double counting trees with the same number of leaves in both subtrees.[7]
The Wedderburn–Etherington numbers grow asymptotically as
an ≈ \sqrt{
\rho+\rho2B'(\rho2) | |
2\pi |
use the Wedderburn–Etherington numbers as part of a design for an encryption system containing a hidden backdoor. When an input to be encrypted by their system can be sufficiently compressed by Huffman coding, it is replaced by the compressed form together with additional information that leaks key data to the attacker. In this system, the shape of the Huffman coding tree is described as an Otter tree and encoded as a binary number in the interval from 0 to the Wedderburn–Etherington number for the number of symbols in the code. In this way, the encoding uses a very small number of bits, the base-2 logarithm of the Wedderburn–Etherington number.[12]
describe a similar encoding technique for rooted unordered binary trees, based on partitioning the trees into small subtrees and encoding each subtree as a number bounded by the Wedderburn–Etherington number for its size. Their scheme allows these trees to be encoded in a number of bits that is close to the information-theoretic lower bound (the base-2 logarithm of the Wedderburn–Etherington number) while still allowing constant-time navigation operations within the tree.[13]
use unordered binary trees, and the fact that the Wedderburn–Etherington numbers are significantly smaller than the numbers that count ordered binary trees, to significantly reduce the number of terms in a series representation of the solution to certain differential equations.[14]