2.4 Irreducible Matrices

1. 2.4 Irreducible Matrices

2. Reducible is reducible if there is a permutation P such that where A11 and A22 are square matrices each of size at least one; otherwise A is called irreducible.

3. 1 x 1 matrix: irr or reducible By definition, every 1 x 1 matrix is irreducible. Some authors refer to irreducible if a≠0 reducible if a=0

4. digraph Let the digraph of A is the digraph with denoted by G(A).

5. Example for diagraph Let G(A) is 1 2

6. strongly connected A digraph is called strongly connected if any vertices x,y, there is a directed path from x to y , and vice versa.

7. Remark 2.4.1 Let Given If ,then there is a directed walk in G(A) of lengthlfrom vertex i to vertex j. If A is nonnegative, then converse also holds

9. An Equivalent relation on V Define a relation ~ on V by i~j if i=j or i≠j and there is a directed walk from vertex i to vertex j and vice versa. ~ is an equivalent relation.

10. Strongly Connected Component The strongly connected components are precisely the subgraphs induced by vertices that belong to a equivalent class.

11. How many strongly connected components are there ? see next page

12. final strongly connected component There are five strongly connected components. final strongly connected component

13. Theorem 2.4.2 Let The following conditions are equivalent: (a) A is irreducible. (b) There does not exist a nonempty proper subset I of <n> such that (c) The graph G(A) is strongly connected.

18. Exercise 2.4.3 p.1 (a) Show that a square matrix A is reducible if and only if there exists a permutation such that where A11,A22 are square matrices each of size at least one.

21. Exercise 2.4.3 p.2 (b) Deduce that if A is reducible, then so is AT

23. Theorem 2.4.4 Let The following conditions are equivalent: (a) A is irreducible. (b) A has no eigenvector which is semipositive but not positive.i.e. every semipositive eigenvector of A is positive (c)

29. Remark If the degree of minimal polynomial of is m,then

31. Theorem 2.4.5 Let A is irreducible if and only if where m is the degree of minimal polynomial of A.

33. Exercise 2.4.6 Let A is irreducible if and only if for any semipositive vector x, if then x>0

36. Theorem 2.2.1 p.1 (Perron’s Thm) (a) (b) (c)

37. (d) (e) A has no nonnegative eigenvector other than (multiples of) u. (f) (g)

38. Theorem 2.3.5 (Perron-Frobenius Thm) If , then and

39. Corollary 2.4.7 Let If A is irreducible, then the conclusions (a),(b),(c),(d) and (f) of Perron Thm all hold.

44. Exercisse 2.4.8 Let Prove that if u is positive and y is nonzero then there is a unique real scalar c such that u+cy is semipositive but not positive.

47. Remark 2.4.9 If A is nonnegative irreducible matrix and if x is nonzero nonnegative vector such that , then x must be the Perron vector of A.

49. Exercise 2.4.10 Show that the nxn permutation matrix with 1’s in positions (1,2), (2,3), …, (n-1,n) and (n,1) is irreducible.