MA 511, Session 10. The Four Fundamental Subspaces of a Matrix

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1 MA 5, Session The Four Fundamental Subspaces of a Matrix Let A be a m n matrix. (i) The row space C(A T )ofais the subspace of R n spanned by the rows of A. (ii) The null space N (A) ofa is the subspace of R n of solutions of Ax =. (iii) The column space C(A) ofa is the subspace of R m spanned by the columns of A. (iv) The left null space N (A T )ofa is the subspace of R m of solutions of A T x =. Let us discuss how to find bases for these vector spaces and determine their dimensions.

2 (i) We consider the row space first. Note that if B is obtained from A by elementary row operations, then the rows of B are linear combinations of the rows of A. Since the elementary row operations can all be reversed, we also have the rows of A are linear combinations of the rows of B, i.e. C(A T )=C(B T ). In particular, if we take A to its row echelon form U by elementary row operations, then the nonzero rows of U form a basis for its row space and hence for the row space of A. Ifweletr =ranka, then dim C(A T )=r. (ii) As for the null space, we can quickly see that elementary row operations do not change this space: if A = LU with L lower triangular with all coefficients on its diagonal equal to, then Indeed, Ax = Ux =. Ax = LUx = L LUx = L =.

3 Then, a basis for N (A) is actually found as a basis for N (U) using the general method we described in session 9 from the free variables in the system Ux =. IfrankA = r, then the number of pivots is r and the number of free variables is n r. Thus, dim N (A) =n r. (iii) We now turn to the column space. Since elementary row operations do change the column space, it is not obvious even that dim C(A) =dimc(a T ). This follows from the following nontrivial observation: Suppose that U is the row echelon form of A. Then U = EA, where E is a product of elementary matrices. Let us write this relation in terms of the columns of U, u,...,u n R n and those of A, v,...,v n R n ( u u 2... u n )=E ( v v 2... v n ) =(Ev Ev 2... Ev n ) that is, Ev j = u j for j n. We shall prove below that invertible matrices transform linearly independent vectors into linearly independent vectors.

4 Hence, as we know that the columns of U that contain the pivots are linearly independent, it follows that the corresponding columns of A are also linearly independent and the other columns of A are dependent from these so that they also span C(A) and thus they form a basis for this space. Hence, dim C(A) =r. Lemma: Assume E is a nonsingular matrix. Then, v,...,v k l.i. Ev,...,Ev k l.i. Proof: Necessity (only if): Let c Ev + + c k Ev k =. Wemustprovethatc = = c k =. First note that E(c v + + c k v k )=. Set x = c v + + c k v k and we immediately see that Ex =. SinceE is nonsingular, this implies = E =E Ex = x, thatisx = c v + + c k v k =. Since v,...,v k are linearly independent, then c = = c k =, proving the linear independence of Ev,...,Ev k.

5 Sufficiency (if): Assume u = Ev,...,u k = Ev k linearly independent and let v = E u,...,v k = E u k. We need to prove v,...,v k are linearly independent. We can reverse the roles of v,...,v k and Ev,...,Ev k in the necessity part and see (using E in place of E) thatu,...,u k linearly independent implies E u,...,e u k linearly independent, which completes the proof. (iv) As for the left null space N (A T ), it is clear that dim N (A T )=m r, since rank A =ranka T. To find a basis for N (A T ), we take A T to its row echelon form and using the m r free variables generate m r basis vectors in the usual way (giving each free variable in turn the value while all other independent variables take on the value ).

6 Example: Find bases and the dimensions of the four fundamental spaces of A = Solution: We find the row echelon form of A: (i) Basis for row space R(A T ): (iii) Basis for column space R(A): 2 3 4, ,

7 (ii) Basis for N (A): We note that in solving Ux = thefreevariablesarex and x 4. Using x =and x 4 =weobtainx 3 = 2andx 2 = 3( 2) 4() 2 =, giving the vector 2 x 4 =, which give the vector basis for N (A): 2.Nextwetakex =and, We have just established that..thus, dim R(A T )=dimr(a) =dimn (A) =2.

8 (iv) Basis for N (A T ): Since dim N (A T )=3 2 =, it follows that in order to find a basis for the left null space of A we only need one nonzero vector x R 3 such that A T x =. WetakeA T to row echelon form: and now see that x 3 =givesx 2 = 2 andx =. Thus, basis for N (A T ): 2.

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