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    Discrete Structures
    GE-167
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    Topics
    1. Mathematical Reasoning: Propositional and Predicate Logic2. Propositional Logic: Logical Operators3. Translations Between Symbolic Expressions and Formal English Expression4. Logical Equivalences5. Predicate Logic: Quantifiers6. Nested Quantification7. Equivalences in Predicate Logic8. Translations Between Symbolic Forms and Formal English9. Rules of Inference: Proof Methods and Strategies10. Direct Proof11. Proof by Contraposition12. Proof by Induction13. Proof by Implication14. Existence Proof15. Uniqueness Proofs16. Trivial Proofs17. Vacuous Proofs18. Sets: Notations and Set Operations19. Venn Diagrams20. Countable and Uncountable Sets21. Relations: Equivalence Relations and Partitions22. Partial Orderings23. Recurrence Relations24. Functions: Injective, Surjective, Bijective25. Special Types of Functions26. Function Composition27. Inverse Functions28. Recursive Functions29. Compositions30. Number Theory: Sequences and Series31. Counting: Inclusion and Exclusion Principle32. Pigeonhole Principle33. Permutations and Combinations34. Integers and Divisibility: Division Theorem35. Modular Arithmetic36. LCM and GCD37. Euclidean and Extended Euclidean Method38. Finding Solutions to Congruence39. Primes: Fundamental Theorem of Arithmetic40. Characterizations of Primes41. Mersenne Primes42. Induction: Weak Induction43. Strong Induction44. Recursion and Recurrences: Formulation of Recurrences45. Closed Formulas46. Counting: Product Rule and Sum Rule47. Principle of Inclusion-Exclusion48. Binomial Coefficients49. Pascal's Identity and Pascal’s Triangle50. Binomial Theorem51. Relations: Reflexive, Symmetric, Transitive, and Antisymmetric52. Equivalence Relations and Equivalence Classes53. Partial Orders54. Graph Theory: Terminologies55. Elements of Graph Theory56. Planar Graphs57. Graph Coloring58. Euler Graph59. Hamiltonian Path60. Rooted Trees61. Graph Traversals62. Handshaking Lemma and Corollary63. Special Families of Graphs64. Graph Isomorphism65. Planarity in Graphs66. Eulerian and Hamiltonian Graphs67. Trees in Graph Theory
    GE-167›Planarity in Graphs
    Discrete StructuresTopic 65 of 67

    Planarity in Graphs

    6 minread
    1,032words
    Intermediatelevel

    Planarity in Graphs

    In graph theory, a graph is considered planar if it can be embedded in the plane (i.e., drawn on a flat surface) such that no edges intersect or cross each other except at their endpoints. Essentially, a planar graph is a graph that can be drawn without any edges crossing, where each vertex is represented as a point and each edge as a curve connecting two points.

    Key Concepts Related to Planarity:

    1. Planar Graph: A graph is planar if it can be drawn on a plane without any of its edges crossing.
    2. Non-Planar Graph: A graph is non-planar if it cannot be drawn on a plane without edge crossings.
    3. Embedding: The process of drawing a graph in the plane, where an embedding ensures no edges cross each other except at vertices.
    4. Faces: In the context of planar graphs, the regions formed by edges, including the outer infinite region, are called faces. A planar graph divides the plane into a number of regions (faces).

    Key Properties of Planar Graphs:

    • Euler's Formula: Euler's formula is a fundamental result in planar graph theory, which states that for any connected planar graph, the following relationship holds:

      V−E+F=2V - E + F = 2V−E+F=2

      where:

      • VVV is the number of vertices,
      • EEE is the number of edges,
      • FFF is the number of faces (regions formed by edges, including the outer region).

      This formula provides an important check for whether a graph can be planar. If a graph satisfies this formula for its number of vertices, edges, and faces, it is likely planar.


    Kuratowski’s Theorem

    A fundamental result for identifying non-planarity is Kuratowski's Theorem, which provides a criterion for determining whether a graph is non-planar. According to this theorem:

    • A graph is non-planar if and only if it contains a subgraph that is a subdivision of either:
      • K₅: The complete graph on 5 vertices (a graph where every pair of distinct vertices is connected by a unique edge).
      • K₃,₄: The complete bipartite graph between 3 and 4 vertices (a graph where the vertices are divided into two disjoint sets, and every vertex in one set is connected to every vertex in the other set).

    In other words, if a graph contains a subgraph that can be transformed into K5K_5K5​ or K3,4K_{3,4}K3,4​ through edge contractions (subdividing edges into multiple edges), the graph is non-planar.


    Planarity Testing:

    To determine if a graph is planar, you can use several methods:

    1. Drawing the Graph: This is the simplest but most tedious method, where you attempt to draw the graph in the plane without edge crossings. If successful, the graph is planar.

    2. Kuratowski’s Theorem: As mentioned earlier, you check if the graph contains a subgraph that is a subdivision of K5K_5K5​ or K3,4K_{3,4}K3,4​. If such a subgraph exists, the graph is non-planar.

    3. Planarity Algorithms: There are efficient algorithms to test planarity, such as:

      • The Hopcroft-Karp Algorithm: A planarity testing algorithm with linear time complexity, used to check if a graph is planar or not.
      • The Boyer-Myrvold Algorithm: An algorithm that tests planarity in linear time and constructs an embedding if the graph is planar.

    Planar Graphs and Embeddings:

    If a graph is planar, it means there exists at least one way to embed it in the plane without edges crossing. The embedding represents the graph's layout on a plane. Here are a few important concepts regarding planar embeddings:

    • Face: A face is a region bounded by edges in a planar graph, including the outer infinite region.
    • Dual Graph: The dual of a planar graph is another graph where each face of the original graph is represented by a vertex, and two vertices in the dual graph are connected by an edge if and only if their corresponding faces in the original graph are adjacent.
    • Crossing Number: The crossing number of a graph is the minimum number of edge crossings required in any embedding of the graph in the plane.

    Examples of Planar and Non-Planar Graphs:

    1. Planar Graph:

      • Cycle Graph C4C_4C4​ (a square) is planar because it can easily be drawn in the plane without any edges crossing.
      • Tree: Any tree is planar because there is no cycle, and thus, there is no possibility of edge crossings.
    2. Non-Planar Graph:

      • K5K_5K5​ (Complete graph on 5 vertices) is non-planar because it cannot be drawn in the plane without edges crossing. It is the simplest non-planar graph.
      • K3,4K_{3,4}K3,4​ (Complete bipartite graph between 3 and 4 vertices) is also non-planar by Kuratowski's Theorem.

    Applications of Planarity:

    1. Geographical Mapping: Planar graphs are used to model maps where the vertices represent regions (such as countries or states), and the edges represent borders between regions. The goal is to color the map with the minimum number of colors such that no two adjacent regions share the same color (this is related to the Four Color Theorem).

    2. Circuit Design: Planar graphs are important in circuit design, especially when designing electronic circuits on a flat surface, as the layout should avoid overlapping wires.

    3. Network Layout: Planar graphs can be used to model the layout of communication networks where physical constraints require a planar arrangement of nodes and edges.


    Conclusion

    A graph is planar if it can be embedded in the plane without any edges crossing each other, and Kuratowski’s Theorem helps identify non-planar graphs by checking for subdivisions of K5K_5K5​ or K3,4K_{3,4}K3,4​. The Euler’s Formula provides an essential relationship between vertices, edges, and faces in planar graphs. Planarity testing algorithms help efficiently determine if a graph is planar, which is crucial in areas such as circuit design, map coloring, and network layout.

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    Graph Isomorphism
    Next topic 66
    Eulerian and Hamiltonian Graphs

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