DM Syllabus

DM Syllabus

Discrete Mathematics (4040003101)

Unit-01 Set Theory (25%)

  • Introduction to Sets: Definition of a set
  • Elements and membership
  • Set notation
  • Set Operations: Union, intersection, and complement of sets
  • Venn diagrams
  • Examples of set operations
  • Subsets and Supersets: Definition of subsets and supersets
  • Proper subsets
  • Subset relationships
  • Cartesian Products and Relations: Cartesian product of sets
  • Ordered pairs
  • Relations between sets
  • Functions: Definition of functions
  • Domain and codomain
  • Types of functions (injective, surjective, bijective)
  • Set Identities and Laws: Associative, commutative, and distributive laws, De Morgan's laws, Idempotent laws
  • Cardinality and Counting: Cardinality of sets, Finite and infinite sets, Countable and uncountable sets
  • Applications of Set Theory: Set theory in computer science, Set theory in probability and statistics
  • Real-life applications: Set theory in computer science, Set theory in probability and statistics, Real-life applications

Unit-02 Matrices and Determinant (25%)

  • Definition of a matrix
  • Row matrix
  • Column matrix
  • Square matrix
  • Diagonal matrix
  • Scalar matrix
  • Identity matrix
  • Zero matrix
  • Symmetric matrix
  • Skew-symmetric matrix
  • Introduction to Determinants
  • Invertible matrix: Definition of a determinant
  • Properties of determinants: Linearity , Multiplicativity , Transposition,
  • Special properties of determinants of triangular matrices
  • Invertible matrix: Definition, Properties of invertible matrices
  • Relationship between invertibility and the determinant
  • Computation of Inverse using Definition: Method of finding the inverse using adjoint and determinant
  • Properties of the inverse matrix
  • Examples of computing inverses for 2x2 and 3x3 matrices
  • Conditions for the existence of inverses
  • Simultaneous Solution of Set of Linear Equations using Cramer ’ s Rule
  • System of linear equations: Definition, representing linear equations in matrix form
  • Cramer's Rule for solving systems of linear equations: Statement of Cramer's Rule, Conditions for the applicability of Cramer's Rule, Advantages and limitations of Cramer's Rule
  • Application of Matrix in Various Fields and Everyday Life: Real-life examples demonstrating the use of matrices in everyday scenarios

Graph Theory and Group Theory (28%)

  • Introduction to Basic Graph Terminology: Definition of a graph, Nodes (vertices) and edges
  • Directed and undirected graphs
  • Adjacency matrix and adjacency list representation
  • Degree of a vertex, Path, cycle, and connected graphs
  • Study of Various Types of Graphs: Tree and forest graphs, Bipartite graphs, Complete graphs, Planar and non-planar graphs, Weighted graphs, Directed acyclic graphs (DAGs)
  • Euler’s Paths and Circuits
  • Hamiltonian Paths: Eulerian paths and circuits
  • Euler's theorem and criteria for existence
  • Hamiltonian paths and cycles
  • Dirac's theorem and sufficient conditions for Hamiltonian cycles
  • Application of Graphs: Network analysis and optimization, Transportation and logistics, Social network analysis, Computer science
  • Introduction to Groups, Subgroups & Semigroups: Definition of groups and their properties
  • Subgroups and subgroup criteria
  • Cyclic groups and generator elements
  • Semigroups and their operations
  • Products and Quotients of Groups: Group product and direct product
  • Quotient groups and homomorphisms
  • Isomorphism theorems for groups
  • Cosets and Lagrange's theorem
  • Applications of Group & Graph Theory: Cryptography and coding theory, Symmetry and crystallography , Graph theory in computer science, Combinatorial optimization and game theory

Unit-04 Number Theory (22%)

  • Divisibility: Understanding the concept of divisibility , prime numbers, composite numbers, and the fundamental theorem of arithmetic
  • Prime Numbers: Properties of prime numbers, prime factorization, prime counting function, distribution of prime numbers, and prime number theorems
  • Congruences: Modular arithmetic, congruence relations, solving linear congruences
  • Chinese remainder theorem, and applications in cryptography
  • Arithmetic Functions: Euler's totient function, Möbius function, divisor functions, and their properties
  • Diophantine Equations: Equations involving integer solutions, linear Diophantine equations
  • Fermat's Last Theorem, and applications in cryptography and number theory
  • Quadratic Residues: Quadratic residues and non-residues, quadratic reciprocity theorem, and applications in cryptography and number theory
  • Arithmetic Progressions: Understanding arithmetic progressions, arithmetic functions in arithmetic progressions, and Dirichlet's theorem on primes in arithmetic progressions
  • Primitive Roots and Indices: Primitive roots modulo n, index of an integer modulo n, and their properties
  • Pell's Equation: Solving Pell's equation, properties of solutions, and applications in number theory and algebra
  • Transcendental Numbers: Introduction to transcendental numbers
  • Lindemann-Weierstrass theorem, and properties of transcendental numbers.

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