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Pathwidth

Pathwidth is a science 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 Pathwidth rather than just read about it. In short: In graph theory, a path decomposition of a graph G is, informally, a representation of G as a "thickened" path graph, and the pathwidth of G is a number that measures how much the path was thickened to form G. More formally, a path-decomposition is a sequence of subsets of vertices of G such that the endpoints of each edge appear in one of the subsets and such that each vertex appears in a contiguous subsequence of…

Pathwidth — main illustration
Pathwidth — illustration

Key takeaways

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

Reference excerpt

In graph theory, a path decomposition of a graph G is, informally, a representation of G as a "thickened" path graph, and the pathwidth of G is a number that measures how much the path was thickened to form G. More formally, a path-decomposition is a sequence of subsets of vertices of G such that the endpoints of each edge appear in one of the subsets and such that each vertex appears in a contiguous subsequence of the subsets, and the pathwidth is one less than the size of the largest set in such a decomposition. Pathwidth is also known as interval thickness (one less than the maximum clique size in an interval supergraph of G), vertex separation number, or node searching number. Pathwidth and path-decompositions are closely analogous to treewidth and tree decompositions. They play a key role in the theory of graph minors: the families of graphs that are closed under graph minors and do not include all forests may be characterized as having bounded pathwidth, and the "vortices" appearing in the general structure theory for minor-closed graph families have bounded pathwidth. Pathwidth, and graphs of bounded pathwidth, also have applications in VLSI design, graph drawing, and computational linguistics. It is NP-hard to find the pathwidth of arbitrary graphs, or even to approximate it accurately. However, the problem is fixed-parameter tractable: testing whether a graph has pathwidth k can be solved in an amount of time that depends linearly on the size of the graph but superexponentially on k. Additionally, for several special classes of graphs, such as trees, the pathwidth may be computed in polynomial time without dependence on k. Many problems in graph algorithms may be solved efficiently on graphs of bounded pathwidth, by using dynamic programming on a path-decomposition of the graph. Path decomposition may also be used to measure the space complexity of dynamic programming algorithms on graphs of bounded treewidth.

Definition

In the first of their famous series of papers on graph minors, Neil Robertson and Paul Seymour (1983) define a path-decomposition of a graph G to be a sequence of subsets Xi of vertices of G, with two properties:

For each edge of G, there exists an i such that both endpoints of the edge belong to subset Xi, and For every three indices i ≤ j ≤ k, X i ∩ X k ⊆ X j . {\displaystyle X_{i}\cap X_{k}\subseteq X_{j}.}

The second of these two properties is equivalent to requiring that the subsets containing any particular vertex form a contiguous subsequence of the whole sequence. In the language of the later papers in Robertson and Seymour's graph minor series, a path-decomposition is a tree decomposition (X,T) in which the underlying tree T of the decomposition is a path graph. The width of a path-decomposition is defined in the same way as for tree-decompositions, as maxi |Xi| − 1, and the pathwidth of G is the minimum width of any path-decomposition of G. The subtraction of one from the size of Xi in this definition makes little difference in most applications of pathwidth, but is used to make the pathwidth of a path graph be equal to one.

Alternative characterizations As Bodlaender (1998) describes, pathwidth can be characterized in many equivalent ways.

Gluing sequences A path decomposition can be described as a sequence of graphs Gi that are glued together by identifying pairs of vertices from consecutive graphs in the sequence, such that the result of performing all of these gluings is G. The graphs Gi may be taken as the induced subgraphs of the sets Xi in the first definition of path decompositions, with two vertices in successive induced subgraphs being glued together when they are induced by the same vertex in G, and in the other direction one may recover the sets Xi as the vertex sets of the graphs Gi. The width of the path decomposition is then one less than the maximum number of vertices in one of the graphs Gi.

Interval thickness

The pathwidth of any graph G is equal to one less than the smallest clique number of an interval graph that contains G as a subgraph. That is, for every path decomposition of G one can find an interval supergraph of G, and for every interval supergraph of G one can find a path decomposition of G, such that the width of the decomposition is one less than the clique number of the interval graph. In one direction, suppose a path decomposition of G is given. Then one may represent the nodes of the decomposition as points on a line (in path order) and represent each vertex v as a closed interval having these points as endpoints. In this way, the path decomposition nodes containing v correspond to the representative points in the interval for v. The intersection graph of the intervals formed from the vertices of G is an interval graph that contains G as a subgraph. Its maximal cliques are given by the sets of intervals containing the representative points, and its maximum clique size is one plus the pathwidth of G. In the other direction, if G is a subgraph of an interval graph with clique number p + 1, then G has a path decomposition of width p whose nodes are given by the maximal cliques of the interval graph. For instance, the interval graph shown with its interval representation in the figure has a path decomposition with five nodes, corresponding to its five maximal cliques ABC, ACD, CDE, CDF, and FG; the maximum clique size is three and the width of this path decomposition is two. This equivalence between pathwidth and interval thickness is closely analogous to the equivalence between treewidth and the minimum clique number (minus one) of a chordal graph of which the given graph is a subgraph. Interval graphs are a special case of chordal graphs, and chordal graphs can be represented as intersection graphs of subtrees of a common tree generalizing the way that interval graphs are intersection graphs of subpaths of a path.

… excerpt ends here. Continue reading the full article.

Illustrations

Pathwidth: An interval graph with pathwidth two, one less than the cardinality of its four maximum cliques ABC, ACD, CDE, and CDF.
An interval graph with pathwidth two, one less than the cardinality of its four maximum cliques ABC, ACD, CDE, and CDF.
Pathwidth: A caterpillar tree, a maximal graph with pathwidth one.
A caterpillar tree, a maximal graph with pathwidth one.
Pathwidth: The forbidden minors for graphs of pathwidth 1.
The forbidden minors for graphs of pathwidth 1.

Worked examples

Example 1 — a first encounter with Pathwidth

Start with the simplest possible case. Write down what Pathwidth claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, 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 Pathwidth 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 Pathwidth 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 Pathwidth

In research
Pathwidth appears in science 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 Pathwidth 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
Pathwidth is common in secondary-school and first-year university syllabi. It links to neighbouring topics Graph invariants, Graph minor theory, NP-complete problems, so understanding it makes those chapters shorter.
In everyday life
Look for Pathwidth 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 Pathwidth in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Pathwidth 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 Pathwidth out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Pathwidth in simple terms?

In graph theory, a path decomposition of a graph G is, informally, a representation of G as a "thickened" path graph, and the pathwidth of G is a number that measures how much the path was thickened to form G. More formally, a path-decomposition is a sequence of subsets of vertices of G such that t…

Why does Pathwidth matter?

Because it connects several science 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 Pathwidth?

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 Pathwidth.

Tags

  • Graph invariants
  • Graph minor theory
  • NP-complete problems

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