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1. Algebraic System
An algebraic system is a non-empty set together with one or more operations (like addition or multiplication) defined on it.
Example: A set AAA with an operation ∗*∗ is written as (A,∗)(A, *)(A,∗).
2. Semigroup
A semigroup is a set SSS with a binary operation ∗*∗ that is associative:
(a∗b)∗c=a∗(b∗c),∀a,b,c∈S(a * b) * c = a * (b * c), \quad \forall a,b,c \in S(a∗b)∗c=a∗(b∗c),∀a,b,c∈S
3. Monoid
A monoid is a semigroup that has an identity element eee, such that:
a∗e=e∗a=a,∀a∈Sa * e = e * a = a, \quad \forall a \in Sa∗e=e∗a=a,∀a∈S
4. Group
A group is a monoid in which every element has an inverse.
So it satisfies:
- Closure
- Associativity
- Identity element
- Inverse element
5. Abelian Group
An Abelian group (or commutative group) is a group where the operation is commutative:
a∗b=b∗a,∀a,b∈Ga * b = b * a, \quad \forall a,b \in Ga∗b=b∗a,∀a,b∈G
6. Generation of Subgroups
If HHH is a subgroup of GGG, then generation means forming HHH from a subset A⊆GA \subseteq GA⊆G.
The subgroup generated by AAA, denoted ⟨A⟩\langle A \rangle⟨A⟩, is the smallest subgroup containing AAA.
7. Cyclic Group
A cyclic group is a group generated by a single element ggg:
G=⟨g⟩={gn∣n∈Z}G = \langle g \rangle = \{ g^n \mid n \in \mathbb{Z} \}G=⟨g⟩={gn∣n∈Z}
8. Coset
Let HHH be a subgroup of GGG and a∈Ga \in Ga∈G.
- Left coset: aH={ah∣h∈H}aH = \{ ah \mid h \in H \}aH={ah∣h∈H}
- Right coset: Ha={ha∣h∈H}Ha = \{ ha \mid h \in H \}Ha={ha∣h∈H}
9. Normal Subgroup
A subgroup NNN of GGG is normal if:
gN=Ng,∀g∈GgN = Ng, \quad \forall g \in GgN=Ng,∀g∈G
Denoted by N⊴GN \trianglelefteq GN⊴G
10. Ring
A ring is a set RRR with two operations (+ and ×) such that:
- RRR is an Abelian group under addition
- Multiplication is associative
- Distributive laws hold:
a(b+c)=ab+ac,(a+b)c=ac+bca(b+c) = ab + ac, \quad (a+b)c = ac + bca(b+c)=ab+ac,(a+b)c=ac+bc
11. Field
A field is a ring in which:
- Every non-zero element has a multiplicative inverse
- Multiplication is commutative
12. Integral Domain
An integral domain is a commutative ring with:
- No zero divisors (i.E., ab=0⇒a=0ab = 0 \Rightarrow a = 0ab=0⇒a=0 or b=0b = 0b=0)
- Multiplicative identity
Here are clear definitions followed by the proof:
Definitions
1. Tree In Graph Theory, a tree is a connected graph with no cycles
It connects all its vertices
It has no closed loops
2. Binary Tree
A binary tree is a hierarchical data structure in which each node has at most two children, usually called:
left child
right child
3. M-ary Tree An M-ary tree (or n-ary tree) is a tree in which each node has at most M children
If ( M = 2 ), it becomes a binary tree
Used in structures like heaps and search trees
4. Spanning Tree Given a connected graph, a spanning tree is a subgraph that:
includes all vertices of the original graph
is a tree (no cycles, connected)
has the minimum number of edges needed to connect all vertices
5. Root In a rooted tree, the root is the topmost node from which all nodes descend
It has no parent
Every other node is reachable from it
Theorem
A tree with ( n ) vertices has exactly ( n – 1 ) edges.
Proof (by Induction)
Base Case
For ( n = 1 ):
A tree with one vertex has 0 edges
( n – 1 = 1 – 1 = 0 ) ✔️ True
Inductive Hypothesis
Assume that any tree with ( k ) vertices has ( k – 1 ) edges.
Inductive Step
Consider a tree with ( k + 1 ) vertices.
A fundamental property of trees:
Every tree has at least one leaf (a vertex with degree 1)Remove one leaf and its edge:
Remaining graph has ( k ) vertices
By hypothesis → it has ( k – 1 ) edges
Add back the removed vertex and edge:
Total edges = ( (k – 1) + 1 = k )
Thus, a tree with ( k + 1 ) vertices has ( k = (k+1 – 1) ) edges.
Definitions
1. Tree In Graph Theory, a tree is a connected graph with no cycles
It connects all its vertices
It has no closed loops
2. Binary Tree
A binary tree is a hierarchical data structure in which each node has at most two children, usually called:
left child
right child
3. M-ary Tree An M-ary tree (or n-ary tree) is a tree in which each node has at most M children
If M=2M=2, it becomes a binary tree
Used in structures like heaps and search trees
4. Spanning Tree Given a connected graph, a spanning tree is a subgraph that:
includes all vertices of the original graph
is a tree (no cycles, connected)
has the minimum number of edges needed to connect all vertices
5. Root In a rooted tree, the root is the topmost node from which all nodes descend
It has no parent
Every other node is reachable from it
Theorem
A tree with nn vertices has exactly n−1n−1 edges.
Proof (by Induction)
Base Case
For n=1n=1:
A tree with one vertex has 0 edges
n−1=1−1=0n−11−10 ✔️ True
Inductive Hypothesis
Assume that any tree with kk vertices has k−1k−1 edges.
Inductive Step
Consider a tree with k+1k+1 vertices.
A fundamental property of trees:
Every tree has at least one leaf (a vertex with degree 1)Remove one leaf and its edge:
Remaining graph has kk vertices
By hypothesis → it has k−1k−1 edges
Add back the removed vertex and edge:
Total edges = (k−1)+1=k(k−11=k
Thus, a tree with k+1k+1 vertices has k=(k+1−1)k=(1−1 edges.
Conclusion
By induction, a tree with nn vertices has:
n−1 edgesn−1 edgesIf you want, I can also show a visual example or give an alternative proof using graph properties.
Here are concise definitions with examples for each term:
1. Isomorphism of Graphs
Two graphs are isomorphic if there is a one-to-one correspondence between their vertices and edges that preserves adjacency.
Example:
Graph G1G1: A—B—C
Graph G2G2: X—Y—Z
Mapping: A→X, B→Y, C→Z → same structure ⇒ isomorphic
2. Simple Graph
A graph with:
no loops
no multiple edges between the same pair of vertices
Example:
Triangle with vertices A, B, C and edges AB, BC, CA
3. Degree of a Vertex
The degree is the number of edges incident to a vertex.
Example:
If vertex A connects to B, C, D → degree of A = 3
4. Complete Graph
A graph where every pair of vertices is connected.
Example:
For 4 vertices (called K4K4), every vertex connects to the other 3
5. Directed Graph (Digraph)
A graph where edges have a direction.
Example:
A → B, B → C (edges are arrows, not just lines)
6. Connected Graph
A graph in which there is a path between every pair of vertices.
Example:
A—B—C—D is connected
7. Tree
A connected graph with no cycles.
Example:
A—B, A—C, B—D (no loops, fully connected)
8. Cyclic Graph
A graph that contains at least one cycle.
Example:
A—B—C—A (forms a loop)
9. Null Graph
A graph with vertices but no edges.
Example:
Vertices: A, B, C but no connections
10. Strongly Connected Graph
(For directed graphs)
A graph is strongly connected if every vertex is reachable from every other vertex following direction.
Example:
A → B → C → A (you can reach any vertex from any other)
11. Loop
An edge that connects a vertex to itself.
Example:
A → A
12. Pendent Vertex (Leaf)
A vertex with degree 1.
Example:
In A—B—C, vertices A and C are pendent
13. Isolated Vertex
A vertex with degree 0 (no edges).
Example:
Vertex D in a graph where A—B—C are connected but D is separate
14. Weighted Graph
A graph where edges have weights (costs, distances, etc.).
Example:
A—B (weight 5), B—C (weight 3)
15. Path
A sequence of vertices where each adjacent pair is connected by an edge.
Example:
A → B → C → D
16. Circuit (Cycle)
A path that starts and ends at the same vertex with no repeated edges.
Example:
A → B → C → A
