#Please help me get this answer for matrices
53 messages · Page 1 of 1 (latest)
Im not sure how to get the required eigenvectors
after reducing the matrix A to
| 1 -1 0 |
| 0 0 0 |
| 0 0 0 |
for A + 4*I
you just find the kernel of A-tI for the eigenvalue t
I tried to
let me show my working
good idea....
Yeah your RREF for A+4I is correct, so just solve (A+4I)x=0
clear that y and z are free, and x=y
so a vector in ker(A+4I) is [x,y,z]=[y,y,z]=y[1,1,0]+z[0,0,1]
How is Z[0,0,1]?
[y,y,z]=y[1,1,0]+z[0,0,1]
I have no idea how they got this solution
just undo the linear combination.
you take 2 linearly independent vectors from the -4-eigenspace
you're given A is diagonalizable, hence the arithmetic and geometric multiplicities must be equal, so since -4 appears twice, the -4-eigenspace is a 2 dimensional subspace
right
so any basis for the -4-eigenspace will fill the last 2 columns
they just picked not obvious ones ig.
wait wht
what?
I am still a bit stuck on the "undo the linear combination"
do you agree [y,y,z]=y[1,1,0]+z[0,0,1]?
yes
so then you're not stuck
but how does z have a value when
z is any real number
[1,-1,0] = x - y?
since y and z were free variables
x and y are scalars, so that equation is complete nonsense
right so x = y and then [y,y,z] = y[1,1,0] + z[0,0,1] then how did they procede?
so ker(A+4I)=span([1,1,0],[0,0,1]), and clearly the 2 vectors are linearly independent
so they're a basis for the -4-eigenspace
so you can put those as the columns..
or, as I said, you can take any basis for for the -4-eigenspace
they, again as I already said, took a non-obvious basis.
ah ok
Yeah
could z be any value?
.
again, as I said
literally
got it.
I wanted to make sure it was as I understood it to be mb
so another valid eigen vector could be like [-2,-2, 5] ?
yes since that's in the span
right