#eigen value
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Well here 0 is an eigenvalue (the rank of the matrice is 2) and if L is a non zero eigenvalue you can use the fact that the trace of the matrice is the sum of the eigenvalues
why's there got to be a "short hack" ?
apply the definition of eigenvalue and check..

I meant we need to save time in exam hall soooo
then learn your definitions well so you save time by not wallowing in doubt soooo..
Eigen value says if we do |A-lambda I| then it will be 0 determinant
k is an eigenvalue of A if there exists a nonzero vector x such that Ax = kx
Yes
The problem is that i am facing difficulties with definition and their applications
Tell me how will you apply this Ax=kx
for starters just consider whether this problem is well posed
??
what's the trace of A and what do you know about the trace of similar matrices?
- show that 0 is an eigenvalue of A
- trace A is the sum of eigenvalues (why?)
- there exists nonzero eigenvalue k
- how do we get k + m = 20
It comes when we solve the determinant equation
|A-lambda I|=0
So it is like cubic equation and roots of it sum and multiplication will be Determinant
well, you wanted a shorter way
Here trace is 20 so eigen values sum will be equal to it
Let's check determinant is 0 so one eigen value is 0
correct
determinant = 0 iff 0 is an eigenvalue
Like row reduction?
i calculate determinant with elementary operations yes
but you're told k is a nonzero eigenvalue
do we know that k is not 20?
if yes, then there must be three distinct eigenvalues
otherwise the eigenvalues could also be 0,0, 20
So we don't know anything about K,M
can you exclude k = 20?
the options don't matter, you have to take m = 20 - k once you show there are three distinct eigenvalues
any other choice would be wrong
+close