How Do Dimensions of Kernel Relate in Composite Linear Operators?

In summary, the conversation discusses proving that if T1 and T2 are linear operators, then the sum of their kernel dimensions is greater than or equal to the kernel dimension of their composition. The conversation includes a hint to show that ker(T1oT2) is a subset of ker(T1), which is incorrect. Instead, it is shown that ker(T2) is a subset of ker(T1oT2). The conversation also mentions using the dimension formula dim(ImT)+dim(KerT)=dimV to solve the problem.
  • #1
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I need to prove that if T1 and T2 are linear operators, then
dim(kerT1)+dim(KerT2)>=dim(Ker(T1oT2)).

now, i thought to show that Ker(T1oT2) is a subset of ker(T1), and then it obviously follows, but here I am stuck: if u in ker(T1oT2) then T1(T2(u))=0 so T2(u) is in Ker(T1) but i need to show that u is in kerT1, if it's correct.

any hints.
 
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  • #2
Can I change it to S and T, rather than T1 and T2, which, let's face it, is a very bad notation.

ker(ST) is certainly not a subset (or even subspace) of ker(S). There is no reason to suppose that T maps ker(S) into ker(S), which is what you are trying (and therefore failing) to show.

u is in ker(ST) if either T(u)=0, or T(u) lies in ker(S). Of course T(u)=0 implies that T(u) is in ker(S), thus all you need to do is to work out the dimension of the preimage of ker(S) under T.

The pre-image of any subspace V under a map T is a subspace of the form U+ker(T), with the sum not necessarily direct, and T mapping U isomorphically to V. (This is just the isomorphism theorems in action.) This completely solves your problem, and was just writing out the definitions.
 
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  • #3
loop quantum gravity said:
I need to prove that if T1 and T2 are linear operators, then
dim(kerT1)+dim(KerT2)>=dim(Ker(T1oT2)).

now, i thought to show that Ker(T1oT2) is a subset of ker(T1), ...
any hints.

You have things reversed.
[tex]\mathop{ker}(T_2) \subseteq \mathop{ker}(T_1\circ T_2)[/tex]

But that won't prove your inequality either but it is one step. Also consider the space
[tex] \mathbf{N}= \mathop{ker}(T_1\circ T_2) - \mathop{ker}(T_2)[/tex]
and its image:
[tex]\mathbf{N}'= T_2(\mathbf{N})[/tex]
 
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  • #4
so you mean i need to find the dimension of T^-1(kerS), right?
 
  • #5
ah, ok i see it's only an application of dim(ImT)+dim(KerT)=dimV.
 
  • #6
loop quantum gravity said:
ah, ok i see it's only an application of dim(ImT)+dim(KerT)=dimV.

There you go.
 

FAQ: How Do Dimensions of Kernel Relate in Composite Linear Operators?

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