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Matching polynomial

Matching polynomial is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Matching polynomial rather than just read about it. In short: In the mathematical fields of graph theory and combinatorics, a matching polynomial (sometimes called an acyclic polynomial) is a generating function of the numbers of matchings of various sizes in a graph. It is one of several graph polynomials studied in algebraic graph theory.

Key takeaways

  • Matching polynomial belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Matching polynomial to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Matching polynomial from memory before moving on to harder problems.

Reference excerpt

In the mathematical fields of graph theory and combinatorics, a matching polynomial (sometimes called an acyclic polynomial) is a generating function of the numbers of matchings of various sizes in a graph. It is one of several graph polynomials studied in algebraic graph theory.

Definition Several different types of matching polynomials have been defined. Let G be a graph with n vertices and let mk be the number of k-edge matchings. One matching polynomial of G is

m G ( x ) := ∑ k ≥ 0 m k x k . {\displaystyle m_{G}(x):=\sum _{k\geq 0}m_{k}x^{k}.}

Another definition gives the matching polynomial as

M G ( x ) := ∑ k ≥ 0 ( − 1 ) k m k x n − 2 k . {\displaystyle M_{G}(x):=\sum _{k\geq 0}(-1)^{k}m_{k}x^{n-2k}.}

A third definition is the polynomial

μ G ( x , y ) := ∑ k ≥ 0 m k x k y n − 2 k . {\displaystyle \mu _{G}(x,y):=\sum _{k\geq 0}m_{k}x^{k}y^{n-2k}.}

Each type has its uses, and all are equivalent by simple transformations. For instance,

M G ( x ) = x n m G ( − x − 2 ) {\displaystyle M_{G}(x)=x^{n}m_{G}(-x^{-2})}

and

μ G ( x , y ) = y n m G ( x / y 2 ) . {\displaystyle \mu _{G}(x,y)=y^{n}m_{G}(x/y^{2}).}

Connections to other polynomials The first type of matching polynomial is a direct generalization of the rook polynomial. The second type of matching polynomial has remarkable connections with orthogonal polynomials. For instance, if G = Km,n, the complete bipartite graph, then the second type of matching polynomial is related to the generalized Laguerre polynomial Lnα(x) by the identity:

M K m , n ( x ) = n ! L n ( m − n ) ( x 2 ) . {\displaystyle M_{K_{m,n}}(x)=n!L_{n}^{(m-n)}(x^{2}).}

If G is the complete graph Kn, then MG(x) is an Hermite polynomial:

M K n ( x ) = H n ( x ) , {\displaystyle M_{K_{n}}(x)=H_{n}(x),}

where Hn(x) is the "probabilist's Hermite polynomial" (1) in the definition of Hermite polynomials. These facts were observed by Godsil (1981). If G is a forest, then its matching polynomial is equal to the characteristic polynomial of its adjacency matrix. If G is a path or a cycle, then MG(x) is a Chebyshev polynomial. In this case μG(1,x) is a Fibonacci polynomial or Lucas polynomial respectively.

Complementation The matching polynomial of a graph G with n vertices is related to that of its complement by a pair of (equivalent) formulas. One of them is a simple combinatorial identity due to Zaslavsky (1981). The other is an integral identity due to Godsil (1981). There is a similar relation for a subgraph G of Km,n and its complement in Km,n. This relation, due to Riordan (1958), was known in the context of non-attacking rook placements and rook polynomials.

Applications in chemical informatics The Hosoya index of a graph G, its number of matchings, is used in chemoinformatics as a structural descriptor of a molecular graph. It may be evaluated as mG(1) (Gutman 1991). The third type of matching polynomial was introduced by Farrell (1980) as a version of the "acyclic polynomial" used in chemistry.

Computational complexity On arbitrary graphs, or even planar graphs, computing the matching polynomial is #P-complete (Jerrum 1987). However, it can be computed more efficiently when additional structure about the graph is known. In particular, computing the matching polynomial on n-vertex graphs of treewidth k is fixed-parameter tractable: there exists an algorithm whose running time, for any fixed constant k, is a polynomial in n with an exponent that does not depend on k (Courcelle, Makowsky & Rotics 2001). The matching polynomial of a graph with n vertices and clique-width k may be computed in time nO(k) (Makowsky et al. 2006).

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Matching polynomial

Start with the simplest possible case. Write down what Matching polynomial claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Matching polynomial before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Matching polynomial ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Matching polynomial

In research
Matching polynomial appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Matching polynomial in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Matching polynomial is common in secondary-school and first-year university syllabi. It links to neighbouring topics Algebraic graph theory, Graph invariants, Matching (graph theory), so understanding it makes those chapters shorter.
In everyday life
Look for Matching polynomial outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Matching polynomial in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Matching polynomial means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Matching polynomial out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Matching polynomial in simple terms?

In the mathematical fields of graph theory and combinatorics, a matching polynomial (sometimes called an acyclic polynomial) is a generating function of the numbers of matchings of various sizes in a graph. It is one of several graph polynomials studied in algebraic graph theory.

Why does Matching polynomial matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Matching polynomial?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Matching polynomial.

Tags

  • Algebraic graph theory
  • Graph invariants
  • Matching (graph theory)
  • Polynomials

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