The document discusses conflict-free coloring of graphs. It first defines conflict-free coloring as assigning colors to vertices such that each vertex has a uniquely colored neighbor. It then summarizes previous work showing that conflict-free coloring planar graphs with 1 or 2 colors is NP-complete, while coloring general graphs with any number of colors is NP-complete. The document aims to determine the minimum number of colors needed for conflict-free coloring planar graphs.
This document discusses graph coloring and bipartite graphs. It defines a bipartite graph as one whose nodes can be partitioned into two sets such that no two nodes within the same set are adjacent. Bipartite graphs can be colored with two colors by coloring all nodes in one set one color and nodes in the other set the other color. The four color theorem states that any separation of a plane into contiguous regions can be colored with no more than four colors such that no two adjacent regions have the same color. Applications of graph coloring include exam scheduling, radio frequency assignment, register allocation, map coloring, and Sudoku puzzles.
A simple algorithm I devised to enumerate the disjoint paths between a pair of vertices in a given graph. This algorithm was devised as a part of my course-work for Masters [Tech.] at IIT-Banaras Hindu University.
This document provides a list of online mathematics games and videos for secondary one students to learn math concepts through fun and interactive activities. It includes links to games for rounding off numbers, arranging fractions in order, and a general math playground. Videos cover ratios, fractions, and comparing fractions. The resources are meant to supplement the mathematics syllabus through engaging media.
How to add fractions for GCSE mathematics from How2Become.com, the UK's leading careers advisor. Includes sample MATHS tests for addition of fractions.
Healthy Living and Healthy Eating EDU 290 PowerpointKris Barron
Healthy living involves eating right, exercising regularly, and staying physically active. Exercise comes in many forms, not just running, and can be fun through activities like sports. Maintaining a healthy lifestyle provides benefits such as more energy, lower disease risk, and cheaper medical costs. Eating healthy involves focusing on fruits/veggies, protein, and avoiding excess calories. Small, frequent meals and reading nutrition labels can help achieve a balanced diet. Overall, regular exercise and nutrition lead to health, cost, and quality of life advantages.
How The Love of Music has changed our Business WorldThorsten Faltings
Over the last decade, there was a Giant Refresh in the Business World:
- Many destroyed value chains,
- Business Innovation everywhere,
- Various new markets with new leaders,
- Empowered & emancipated Consumers.
This is the story about how the love of music laid the Foundation for many Innovations in the past 12 years, turning the Business World upside down.
Delivered as plenary at USENIX LISA 2013. video here: https://www.youtube.com/watch?v=nZfNehCzGdw and https://www.usenix.org/conference/lisa13/technical-sessions/plenary/gregg . "How did we ever analyze performance before Flame Graphs?" This new visualization invented by Brendan can help you quickly understand application and kernel performance, especially CPU usage, where stacks (call graphs) can be sampled and then visualized as an interactive flame graph. Flame Graphs are now used for a growing variety of targets: for applications and kernels on Linux, SmartOS, Mac OS X, and Windows; for languages including C, C++, node.js, ruby, and Lua; and in WebKit Web Inspector. This talk will explain them and provide use cases and new visualizations for other event types, including I/O, memory usage, and latency.
This document outlines the rules and procedures for Room 228A. It details 5 rules regarding punctuality, respect, preparation, honesty, and success. It then provides detailed classroom procedures for various scenarios like entering the room, being tardy, completing tasks, getting the teacher's attention, working in groups, turning in papers, finishing work, and dismissing from class. It concludes with emergency procedures and expectations for if the teacher is absent or there is a substitute. Rewards are given for following the rules, while penalties increase with each offense.
This document discusses graph coloring and bipartite graphs. It defines a bipartite graph as one whose nodes can be partitioned into two sets such that no two nodes within the same set are adjacent. Bipartite graphs can be colored with two colors by coloring all nodes in one set one color and nodes in the other set the other color. The four color theorem states that any separation of a plane into contiguous regions can be colored with no more than four colors such that no two adjacent regions have the same color. Applications of graph coloring include exam scheduling, radio frequency assignment, register allocation, map coloring, and Sudoku puzzles.
A simple algorithm I devised to enumerate the disjoint paths between a pair of vertices in a given graph. This algorithm was devised as a part of my course-work for Masters [Tech.] at IIT-Banaras Hindu University.
This document provides a list of online mathematics games and videos for secondary one students to learn math concepts through fun and interactive activities. It includes links to games for rounding off numbers, arranging fractions in order, and a general math playground. Videos cover ratios, fractions, and comparing fractions. The resources are meant to supplement the mathematics syllabus through engaging media.
How to add fractions for GCSE mathematics from How2Become.com, the UK's leading careers advisor. Includes sample MATHS tests for addition of fractions.
Healthy Living and Healthy Eating EDU 290 PowerpointKris Barron
Healthy living involves eating right, exercising regularly, and staying physically active. Exercise comes in many forms, not just running, and can be fun through activities like sports. Maintaining a healthy lifestyle provides benefits such as more energy, lower disease risk, and cheaper medical costs. Eating healthy involves focusing on fruits/veggies, protein, and avoiding excess calories. Small, frequent meals and reading nutrition labels can help achieve a balanced diet. Overall, regular exercise and nutrition lead to health, cost, and quality of life advantages.
How The Love of Music has changed our Business WorldThorsten Faltings
Over the last decade, there was a Giant Refresh in the Business World:
- Many destroyed value chains,
- Business Innovation everywhere,
- Various new markets with new leaders,
- Empowered & emancipated Consumers.
This is the story about how the love of music laid the Foundation for many Innovations in the past 12 years, turning the Business World upside down.
Delivered as plenary at USENIX LISA 2013. video here: https://www.youtube.com/watch?v=nZfNehCzGdw and https://www.usenix.org/conference/lisa13/technical-sessions/plenary/gregg . "How did we ever analyze performance before Flame Graphs?" This new visualization invented by Brendan can help you quickly understand application and kernel performance, especially CPU usage, where stacks (call graphs) can be sampled and then visualized as an interactive flame graph. Flame Graphs are now used for a growing variety of targets: for applications and kernels on Linux, SmartOS, Mac OS X, and Windows; for languages including C, C++, node.js, ruby, and Lua; and in WebKit Web Inspector. This talk will explain them and provide use cases and new visualizations for other event types, including I/O, memory usage, and latency.
This document outlines the rules and procedures for Room 228A. It details 5 rules regarding punctuality, respect, preparation, honesty, and success. It then provides detailed classroom procedures for various scenarios like entering the room, being tardy, completing tasks, getting the teacher's attention, working in groups, turning in papers, finishing work, and dismissing from class. It concludes with emergency procedures and expectations for if the teacher is absent or there is a substitute. Rewards are given for following the rules, while penalties increase with each offense.
The document discusses chromatic polynomials and planar graphs. It defines the chromatic polynomial as a polynomial that gives the number of ways to properly color a graph using a certain number of colors. The value of the chromatic polynomial for a graph G with n vertices is equal to the number of ways of coloring G using λ colors or fewer. It also discusses Euler's formula that the number of vertices - number of edges + number of faces is equal to 2 for any planar graph. An example of calculating the chromatic polynomial of a graph is also provided.
Greedy Edge Colouring for Lower Bound of an Achromatic Index of Simple Graphsinventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document discusses edge coloring and k-tuple coloring in graph theory and computer applications. It defines edge coloring as assigning colors to edges so that edges incident to a common vertex have different colors. The minimum number of colors needed is the edge chromatic number. It also defines k-tuple coloring as assigning a set of k colors to each vertex such that no two adjacent vertices share a color, with Xk(G) being the minimum number of colors needed. An example shows C4 requires at least 4 colors for 2-tuple coloring.
A study-of-vertex-edge-coloring-techniques-with-applicationIjcem Journal
This document discusses applications of graph coloring techniques. It begins with an overview of vertex coloring and edge coloring of graphs, including definitions of key terms like chromatic number and edge chromatic number. It then provides several examples of applications of graph coloring, including scheduling problems like job scheduling, aircraft scheduling, and timetabling problems. It describes how these problems can be modeled as graph coloring problems and solved using techniques like precoloring, list coloring, and minimum sum coloring. The document concludes with additional examples of applying graph coloring, such as map coloring for cellular networks.
Hello all, This is the presentation of Graph Colouring in Graph theory and application. Use this presentation as a reference if you have any doubt you can comment here.
The document discusses graph coloring and its applications. It defines graph coloring as assigning colors to graph vertices such that no adjacent vertices have the same color. It also discusses the four color theorem, which states that any planar map can be colored with four or fewer colors. Finally, it provides an overview of backtracking as an algorithmic approach for solving graph coloring problems.
The document discusses chromatic polynomials and planar graphs. It defines the chromatic polynomial as a polynomial that gives the number of ways to properly color a graph using a certain number of colors. The value of the chromatic polynomial for a graph G with n vertices is equal to the number of ways of coloring G using λ colors or fewer. It also discusses Euler's formula that the number of vertices - number of edges + number of faces is equal to 2 for any planar graph. An example of calculating the chromatic polynomial of a graph is also provided.
Greedy Edge Colouring for Lower Bound of an Achromatic Index of Simple Graphsinventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document discusses edge coloring and k-tuple coloring in graph theory and computer applications. It defines edge coloring as assigning colors to edges so that edges incident to a common vertex have different colors. The minimum number of colors needed is the edge chromatic number. It also defines k-tuple coloring as assigning a set of k colors to each vertex such that no two adjacent vertices share a color, with Xk(G) being the minimum number of colors needed. An example shows C4 requires at least 4 colors for 2-tuple coloring.
A study-of-vertex-edge-coloring-techniques-with-applicationIjcem Journal
This document discusses applications of graph coloring techniques. It begins with an overview of vertex coloring and edge coloring of graphs, including definitions of key terms like chromatic number and edge chromatic number. It then provides several examples of applications of graph coloring, including scheduling problems like job scheduling, aircraft scheduling, and timetabling problems. It describes how these problems can be modeled as graph coloring problems and solved using techniques like precoloring, list coloring, and minimum sum coloring. The document concludes with additional examples of applying graph coloring, such as map coloring for cellular networks.
Hello all, This is the presentation of Graph Colouring in Graph theory and application. Use this presentation as a reference if you have any doubt you can comment here.
The document discusses graph coloring and its applications. It defines graph coloring as assigning colors to graph vertices such that no adjacent vertices have the same color. It also discusses the four color theorem, which states that any planar map can be colored with four or fewer colors. Finally, it provides an overview of backtracking as an algorithmic approach for solving graph coloring problems.
1. Aman Gour, Phillip Keldenich
Zachery Abel, Victor Alvarez, Erik Demaine, Sándor Fekete,
Adam Hesterberg, Christian Scheffer
Three Colors Suffice:
Conflict-free Coloring of Planar Graphs
2. Planar Four-Color Theorem
Planar four-color theorem:
Every planar graph is 4-colorable.
2
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
3. Hadwiger’s Conjecture
Hugo Hadwiger (1943):
Every graph G with chromatic number χ(G) = k
has Hadwiger number H(G) ≥ k, i.e., it has Kk,
the complete graph on k vertices, as a minor.
3
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
4. Hadwiger’s Conjecture
Hugo Hadwiger (1943):
Every graph G with chromatic number χ(G) = k
has Hadwiger number H(G) ≥ k, i.e., it has Kk,
the complete graph on k vertices, as a minor.
3
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
5. Hadwiger’s Conjecture
Hugo Hadwiger (1943):
Every graph G with chromatic number χ(G) = k
has Hadwiger number H(G) ≥ k, i.e., it has Kk,
the complete graph on k vertices, as a minor.
3
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
6. Hadwiger’s Conjecture
Hugo Hadwiger (1943):
Every graph G with chromatic number χ(G) = k
has Hadwiger number H(G) ≥ k, i.e., it has Kk,
the complete graph on k vertices, as a minor.
3
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
7. Hadwiger’s Conjecture
Hugo Hadwiger (1943):
Every graph G with chromatic number χ(G) = k
has Hadwiger number H(G) ≥ k, i.e., it has Kk,
the complete graph on k vertices, as a minor.
Partial results:
k < 4: Easy to see
k = 4: 4-color theorem
k < 7: Robertson et al. (1993)
k = 7 and higher: Open
3
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
8. Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Preface: Conflict-Free Coloring
4
9. Conflict-Free Coloring
Coloring of a subset of the vertices
Conflict-free coloring:
such that every vertex v has a
conflict-free neighbor u 2 N[v] whose
color appears in N[v] exactly once.
5
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
10. Conflict-Free Coloring
v
u1
u2
u3
u4
u5
u6
u7
u8
Coloring of a subset of the vertices
Conflict-free coloring:
such that every vertex v has a
conflict-free neighbor u 2 N[v] whose
color appears in N[v] exactly once.
5
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
11. Conflict-Free Coloring
v
u1
u2
u3
u4
u5
u6
u7
u8
Coloring of a subset of the vertices
Conflict-free coloring:
such that every vertex v has a
conflict-free neighbor u 2 N[v] whose
color appears in N[v] exactly once.
5
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
12. Conflict-Free Coloring
v
u1
u2
u3
u4
u5
u6
u7
u8
Coloring of a subset of the vertices
Conflict-free coloring:
such that every vertex v has a
conflict-free neighbor u 2 N[v] whose
color appears in N[v] exactly once.
5
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
13. Conflict-Free Coloring
v
u1
u2
u3
u4
u5
u6
u7
u8
Coloring of a subset of the vertices
Conflict-free coloring:
such that every vertex v has a
conflict-free neighbor u 2 N[v] whose
color appears in N[v] exactly once.
5
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
14. Conflict-Free Coloring
v
u1
u2
u3
u4
u5
u6
u7
u8
Coloring of a subset of the vertices
Conflict-free coloring:
such that every vertex v has a
conflict-free neighbor u 2 N[v] whose
color appears in N[v] exactly once.
5
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
15. Conflict-Free Coloring
v
u1
u2
u3
u4
u5
u6
u7
u8
Coloring of a subset of the vertices
Conflict-free coloring:
such that every vertex v has a
conflict-free neighbor u 2 N[v] whose
color appears in N[v] exactly once.
5
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
16. Conflict-Free Coloring
v
u1
u2
u3
u4
u5
u6
u7
u8
Coloring of a subset of the vertices
Conflict-free coloring:
such that every vertex v has a
conflict-free neighbor u 2 N[v] whose
color appears in N[v] exactly once.
5
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
27. Conflict-Free Coloring: Questions
7
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Complexity
• Planar graphs
• General graphs
28. Conflict-Free Coloring: Questions
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Complexity
• Planar graphs
• General graphs
Sufficient number of colors
• Planar graphs
• General graphs
29. Conflict-Free Coloring: Questions
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Complexity
• Planar graphs
• General graphs
Sufficient number of colors
• Planar graphs
• General graphs
Number of colored vertices — Planar graphs
30. Conflict-Free Coloring: Answers
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Complexity
• Planar graphs: NP-complete for 1 and 2 colors
• General graphs: NP-complete for any number of colors
31. Conflict-Free Coloring: Answers
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Complexity
• Planar graphs: NP-complete for 1 and 2 colors
• General graphs: NP-complete for any number of colors
Sufficient number of colors
• Three colors suffice for planar graphs
• Conflict-free analogue of Hadwiger’s Conjecture
32. Conflict-Free Coloring: Answers
8
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Complexity
• Planar graphs: NP-complete for 1 and 2 colors
• General graphs: NP-complete for any number of colors
Sufficient number of colors
• Three colors suffice for planar graphs
• Conflict-free analogue of Hadwiger’s Conjecture
Number of colored vertices - Planar graphs
• k = 3: No constant approximation factor
• k = 4: FPT, PTAS, dom(G) always possible
33. Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Part I: Complexity
9
34. Complexity in Planar Graphs
10
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
35. Complexity in Planar Graphs
10
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
x1 x2 x3 x4 x5
c1 c2
c3 c4
36. Complexity in Planar Graphs
10
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
x1 x2 x3 x4 x5
c1 c2
c3 c4
c1
c1;1
c1;3c1
37. Complexity in Planar Graphs
10
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
x1 x2 x3 x4 x5
c1 c2
c3 c4
x1
c1
c1;1
c1;3c1
38. Complexity in Planar Graphs
10
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
x1 x2 x3 x4 x5
c1 c2
c3 c4
z1;1
c1;1
c1;3
z1;3
x1 x2 x3 x4 x5
c1
G1(Φ)
39. Complexity in Planar Graphs
11
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Proof: Reduction from planar conflict-free 1-coloring
40. Gadget G≤1
Idea: G≤1 reduces the number of colors available to 1
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
41. Gadget G≤1
Idea: G≤1 reduces the number of colors available to 1
12
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
42. Gadget G≤1
Idea: G≤1 reduces the number of colors available to 1
12
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
43. Gadget G≤1
Idea: G≤1 reduces the number of colors available to 1
12
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
v
44. From 2 Colors to 1 Color
13
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
45. From 2 Colors to 1 Color
13
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
x1 x2 x3 x4 x5
c1 c2
c3 c4
z1;1
c1;1
c1;3
z1;3
x1 x2 x3 x4 x5
c1
46. From 2 Colors to 1 Color
13
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Zi
≤ 1 Zi+1≤ 1
≤ 1
cj;3
cj;1
≤ 1
cj
Zi−1
upper
lower
left right
t f f
47. From 2 Colors to 1 Color
13
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Zi
≤ 1 Zi+1≤ 1
≤ 1
cj;3
cj;1
≤ 1
cj
Zi−1
upper
lower
left right
t f f
G2(Φ)
48. From 2 Colors to 1 Color
13
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Zi
≤ 1 Zi+1≤ 1
≤ 1
cj;3
cj;1
≤ 1
cj
Zi−1
upper
lower
left right
t f f
G2(Φ)
49. From 2 Colors to 1 Color
13
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Zi
≤ 1 Zi+1≤ 1
≤ 1
cj;3
cj;1
≤ 1
cj
Zi−1
upper
lower
left right
t f f
G2(Φ)
50. Complexity for General Graphs
14
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Proof: Reduction from proper coloring
51. Complexity for General Graphs
14
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Proof: Reduction from proper coloring
Basic Idea: Gadgets enforcing vertices in a graph to be colored
and edges to be colored with distinct colors at both end points.
Gk
Gk
. . .
. . .. . .
w
Gk 1
Gk 1
. . .
Gk
Gk
v
52. Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Part II: Sufficient number of colors
15
57. Sufficient Criterion
K 3
5
K 3
6 K5
16
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
58. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
59. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
60. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
61. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
62. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
63. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
64. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
65. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
66. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
67. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
68. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
69. Coloring Algorithm
17
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
• Iteratively construct color class (distance-3-set)
• Always choose vertices of distance exactly 3
• Remove covered vertices
• Repeat until what remains is a collection of paths
70. Proof
18
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
71. Proof
By induction:
For k=1: Collection of paths
K 3
4
18
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
72. Proof
By induction:
For k=1: Collection of paths
Induction step:
Removal of distance-3-set reduces k by one
19
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
73. Proof
Induction step:
Removal of distance-3-set reduces k by one
Unseen vertices U
20
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
74. Proof
Claim: No set U of unseen vertices is a cutset of G.
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
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75. Proof
Claim: No set U of unseen vertices is a cutset of G.
Hv0
≥ 2
≥ 3
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
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76. Proof
Claim: No set U of unseen vertices is a cutset of G.
Hv0
≥ 2 ≥ 2
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
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77. Proof
Claim: No set U of unseen vertices is a cutset of G.
Hw0
w−1
= 3
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
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78. Proof
Claim: No set U of unseen vertices is a cutset of G.
Hw0
w−1
= 3
= 2
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
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79. Proof
G[U] does not contain a Kk+1 or Kk+2 as minor-3
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
80. Proof
G[U] does not contain a Kk+1 or Kk+2 as minor-3
Uv0
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
81. Proof
G[U] does not contain a Kk+1 or Kk+2 as minor-3
Uv0
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
82. Proof
G[U] does not contain a Kk+1 or Kk+2 as minor-3
Kk+1
U
v
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
83. Proof
G[U] does not contain a Kk+1 or Kk+2 as minor-3
Kk+1
U
v
Paths could be contracted, yielding a Kk+2 minor!
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
84. Proof
G[U] does not contain a Kk+1 or Kk+2 as minor-3
Kk+1
U
v
Paths could be contracted, yielding a Kk+2 minor!
Other case analogous - we are done!
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
85. Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Future Work
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86. Future Work
Neighborhoods: Open versus closed neighborhoods
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
87. Future Work
Neighborhoods: Open versus closed neighborhoods
25
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
88. Future Work
Neighborhoods: Open versus closed neighborhoods
25
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
89. Future Work
Neighborhoods: Open versus closed neighborhoods
25
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
90. Future Work
Neighborhoods: Open versus closed neighborhoods
25
Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
91. Future Work
Neighborhoods: Open versus closed neighborhoods
Other graph classes:
Intersection graphs of geometric objects
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
92. Future Work
Neighborhoods: Open versus closed neighborhoods
Other graph classes:
Intersection graphs of geometric objects
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
93. Future Work
Conflict-free AGP:
Visibility graphs of polygons, point sets in polygons
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Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Neighborhoods: Open versus closed neighborhoods
Other graph classes:
Intersection graphs of geometric objects
94. Aman Gour | Phillip Keldenich | Three Colors Suffice: Conflict-Free Coloring of Planar Graphs | SODA 2017
Gracias!
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