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A Faster Parameterized Algorithm for Treedepth Felix Reidl, Peter - - PowerPoint PPT Presentation

A Faster Parameterized Algorithm for Treedepth Felix Reidl, Peter Rossmanith, Fernando S anchez Villaamil Somnath Sikdar RWTH Aachen University July 11, 2014 Fernando S anchez Villaamil (RWTH) Parameterized Algorithm for Treedepth July


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A Faster Parameterized Algorithm for Treedepth

Felix Reidl, Peter Rossmanith, Fernando S´ anchez Villaamil Somnath Sikdar

RWTH Aachen University

July 11, 2014

Fernando S´ anchez Villaamil (RWTH) Parameterized Algorithm for Treedepth July 11, 2014 1 / 51

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Treedepth

Treedepth is a width measure.

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Treedepth Fernando S´ anchez Villaamil (RWTH) Parameterized Algorithm for Treedepth July 11, 2014 3 / 51

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Treedepth Fernando S´ anchez Villaamil (RWTH) Parameterized Algorithm for Treedepth July 11, 2014 3 / 51

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Treedepth Fernando S´ anchez Villaamil (RWTH) Parameterized Algorithm for Treedepth July 11, 2014 3 / 51

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Treedepth

7 3 5 2 6 1 4 8

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Treedepth

7 3 5 2 6 1 4 8 7 3 5 2 6 1 4 8

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Treedepth

7 3 5 2 6 1 4 8 7 3 5 2 6 1 4 8

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Treedepth

Definition (Treedepth decomposition)

A treedepth decomposition of a graph G is a rooted forest F such that V (G) ⊆ V (F) and E(G) ⊆ E(clos(F)).

Definition (Treedepth)

The treedepth td(G) of a graph G is the minimum height of any treedepth decomposition of G.

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Treedepth

A strange width measure...

“So many choices”

—Dr. Dre

A graph G has treedepth at most t if G is a subgraph the closure of a tree (forest) of height ≤ t G has a centered coloring with t colors G has a ranked coloring with t colors G is the subgraph of a trivially perfect graph with clique size ≤ t

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Treedepth

Centered Coloring

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Treedepth

Centered Coloring

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Treedepth

Centered Coloring

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Treedepth

Ranked Coloring

1 1 1 1 2 2 3 4 5

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Treedepth

Ranked Coloring

1 1 1 1 2 2 3 4 5

1 1 1 1 2 2 3 4 5

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Treedepth

Trivially Perfect Graphs

G is the subgraph of a trivially perfect graph with clique size at most t.

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Treedepth

Trivially Perfect Graphs

G is the subgraph of a trivially perfect graph with clique size at most t.

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Treedepth

Arises again and again

Introduced as... minimum elimination tree by Pothen [1988]

  • rdered coloring by Katchalski et al. [1995]

vertex ranking by Bodlaender et al. [1998] again as treedepth by Neˇ setˇ ril and Ossona de Mendez [2008]

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Treedepth

Arises again and again

Introduced as... minimum elimination tree by Pothen [1988]

  • rdered coloring by Katchalski et al. [1995]

vertex ranking by Bodlaender et al. [1998] again as treedepth by Neˇ setˇ ril and Ossona de Mendez [2008] Related to... layouting of VLSI chips star height of regular languages characterizing bounded expansion graph classes counting subgraphs [New results coming]

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Treedepth

Arises again and again

Introduced as... minimum elimination tree by Pothen [1988]

  • rdered coloring by Katchalski et al. [1995]

vertex ranking by Bodlaender et al. [1998] again as treedepth by Neˇ setˇ ril and Ossona de Mendez [2008] Related to... layouting of VLSI chips star height of regular languages characterizing bounded expansion graph classes counting subgraphs [New results coming] Personal opinion: Treedepth is the most useful definition.

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Treedepth

7 3 5 2 6 1 4

7 3 5 2 6 1 4 Treedepth t → Maximal path length 2t − 1.

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Treedepth

Treedepth t → Maximal path length 2t − 1.

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Treedepth

Treedepth t → Maximal path length 2t − 1.

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Treedepth Basic results

A DFS is a Treedepth decomposition

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Treedepth Basic results

A DFS is a Treedepth decomposition

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Treedepth Basic results

A DFS is a Treedepth decomposition

Treedepth t ⇒ Maximal path length 2t − 1 ⇒ 2t-approximation

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

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Treedepth Basic results

Treedepth to pathwidth

tw(G) ≤ pw(G) ≤ td(G) − 1 Treedepth t ⇒ Path decomposition of width 2t − 2

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Treedepth Basic results Fernando S´ anchez Villaamil (RWTH) Parameterized Algorithm for Treedepth July 11, 2014 16 / 51

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Treedepth Basic results Fernando S´ anchez Villaamil (RWTH) Parameterized Algorithm for Treedepth July 11, 2014 16 / 51

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Treedepth Basic results

Treedepth by bruteforce

G

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Treedepth Basic results

Treedepth by bruteforce

G S

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Treedepth Basic results

Treedepth by bruteforce S

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Treedepth Basic results

Treedepth by bruteforce

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Treedepth Basic results

Treedepth by bruteforce

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Treedepth Basic results

Parameterized algorithms

Open problem by Neˇ setˇ ril and Ossona de Mendez [2012]

Is there a simple linear time algorithm to check td(G) ≤ t for fixed t?

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Treedepth Basic results

Parameterized algorithms

Open problem by Neˇ setˇ ril and Ossona de Mendez [2012]

Is there a simple linear time algorithm to check td(G) ≤ t for fixed t? In f (t) · n3 time by Robertson and Seymour. tw(G) ≤ td(G) − 1 ⇒ By Courcelle’s Theorem 222...t · n. Algorithm by Bodlaender et. al. with running time 2O(w2t) · n2.

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Treedepth Basic results

Our results: A (relatively) simple direct algorithm in time 22O(t) · n. A fast algorithm in time 2O(t2) · n.

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Treedepth Basic results

Our results: A (relatively) simple direct algorithm in time 22O(t) · n. A fast algorithm in time 2O(t2) · n. Both results follow from an algorithm on tree decompositions which runs in time 2O(wt) · n.

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The algorithm Fernando S´ anchez Villaamil (RWTH) Parameterized Algorithm for Treedepth July 11, 2014 20 / 51

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The algorithm

Where could the introduced node u be?

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The algorithm

Definition (Nice treedepth decomposition)

We say that T is nice if for every vertex x ∈ V (T), the subgraph of G induced by the vertices in Tx is connected.

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The algorithm

Lemma

For any graph there exists a treedepth decomposition of minimal depth which is nice.

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The algorithm

Where could the introduced node u be?

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The algorithm

Theorem

Given a graph G with n nodes and a tree decomposition of G of width w the treedepth t of G can be decided in time 2O(wt) · n.

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The algorithm Simple algorithm

Simple algorithm

1 Depth-first-search to construct treedepth decomposition T. 2 If depth greater than 2t − 1 say NO. 3 Construct path decomposition P from T of width 2t. 4 Run algorithm on P.

Theorem

There is a (simple) algorithm to decide if a graph G with n nodes has treedepth t which runs in time 22O(t) · n.

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The algorithm Fast algorithm

Fast algorithm

1 Use single exponential 5-approximation for treewidth1. 2 Remember tw(G) ≤ pw(G) ≤ td(G) − 1. 3 If width is greater than 5t say NO. 4 Else run algorithm on tree decomposition.

Theorem

There is a algorithm to decide if a graph G with n nodes has treedepth t which runs in time 2O(t2) · n.

1Very useful result by Hans Bodlaender, P˚

al G. Drange, Markus S. Dregi, Fedor V. Fomin, Daniel Lokshtanov and Micha l Pilipczuk

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The End

Thank you for listening. Questions?

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