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Partitions of an Integer

A recurring theme in this course has been to count the number of integer solutions to an equation of the form x_1+x_2+\cdots + x_k = n. What if we wanted to count the number of such solutions but didn't care what k was?

Partitions of an Integer

A recurring theme in this course has been to count the number of integer solutions to an equation of the form \(x_1+x_2+\cdots + x_k = n\). What if we wanted to count the number of such solutions but didn't care what \(k\) was? How about if we took this new question and required that the \(x_i\) be distinct (, \(x_i\neq x_j\) for \(i\neq j\))? What about if we required that each \(x_i\) be odd? These certainly don't seem like easy questions to answer at first, but generating functions will allow us to say something very interesting about the answers to the last two questions.

By a partition \(P\) of an integer, we mean a collection of (not necessarily distinct) positive integers such that \(\sum_{i\in P} i = n\). (By convention, we will write the elements of \(P\) from largest to smallest.) For example, \(2+2+1\) is a partition of \(5\). For each \(n\ge0\), let \(p_n\) denote the number of partitions of the integer \(n\) (with \(p_0=1\) by convention). Note that \(p_8=22\) as evidenced by the list in .

Note that there are \(6\) partitions of \(8\) into distinct parts. Also there are \(6\) partitions of \(8\) into odd parts. While it might seem that this is a coincidence, it in fact is always the case as states. Before looking at that theorem and its proof, let's think about what a generating function for \(p_n\), the number of partitions of \(n\), would look like. Given a partition of \(n\), we can count how many \(1\)'s appear, how many \(2\)'s appear, and so on. This suggests a similarity with our fruit basket problems earlier in the chapter, leading to the generating function \[\begin{aligned}\end{aligned}\] Here the factor whose sum contains terms \(x^{km}\) is accounting for the number of \(k\)'s in the partition. While \(P(x)\) has a quite elegant form, that doesn't mean that it's terribly useful for computing \(p_n\). In fact, providing an asymptotic estimate for \(p_n\) was a notoriously difficult problem, finally addressed by Hardy and Ramanujan in 1918. A popular account of this can be found in Robert Kanigel's 1991 book The Man who Knew Infinity or the 2016 film with the same title.

Proving the relationship between the number of partitions into distinct parts and the number of partitions into odd parts will involve restricted versions of the generating function \(P(x)\) from above.

Condensed — the full section is in Keller & Trotter, Applied Combinatorics.

Symbols used here

\sum_{k=1}^{n} a_k
summation
Add a_k for k = 1 up to n.
x \in A,\ A \subseteq B
element of, subset
x belongs to A; every element of A is in B.
P(A),\ P(A \mid B)
probability, conditional probability
Chance of A; chance of A given that B happened.
i
imaginary unit
i² = −1.
\leq,\ \geq
less/greater than or equal
Inequalities that allow equality; < and > exclude it.
\neq
not equal
The two sides are different.
n!
factorial
n × (n−1) × … × 1; the number of orderings of n things. 0! = 1.
\binom{n}{k}
binomial coefficient, "n choose k"
Number of k-element subsets of n things: n!/(k!(n−k)!).
\prod_{k=1}^{n} a_k
product
Multiply a_k for k = 1 up to n.
\emptyset,\ |A|
empty set, cardinality
The set with no elements; the number of elements of A.

Questions people ask

Permutation or combination?

Ask whether order matters. A lock code is a permutation (order matters); a hand of cards is a combination (it does not).

What is a graph in this sense?

Dots (vertices) joined by lines (edges) — not a plot. Road maps, social networks and molecules are graphs; questions like "is there a route" and "how few colours" are graph theory.

Cobalah sendiri

Parts of this page are adapted from Keller & Trotter, Applied Combinatorics (CC BY-SA 4.0). Condensed and re-explained here; errors are ours.

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