Linear Map, T^p(x)=0, Show Linear Independence

In summary: Thus, x is the unique solution to the equation a_0x+ a_1T(x)+\cdot\cdot\cdot+ a_{n-2}T^{n-2}(x)+ a_{n-}T^{n-1}(x)= 0.
  • #1
joypav
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Problem:

Suppose V is a complex vector space of dimension n, and T is a linear map from V to V. Suppose $x \in V$, and p is a positive integer such that $T^p(x)=0$ but $T^{p-1}(x)\ne0$.

Show that $x, Tx, T^2x, ... , T^{p-1}x$ are linearly independent.During class my professor said it was "a fact" that

If V is a complex vector space of dimension n, and T is a linear map from V to V such that $T^n(x)=0$ but $T^{n-1}(x)\ne0$,
then there exists an x such that $x, Tx, T^2x, ... , T^{n-1}x$ are linearly independent.

Is this what I should use for this problem? If so, do I need to know how I can determine such an x?
 
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  • #2
What you assert your professor said and the theorem you state are not quite the same. You say your professor said "If V is a complex vector space of dimension n, and T is a linear map from V to V such that [tex]T^n(x)= 0[/tex] but [tex]T^{n-1}(x)[/tex] is not 0" then there exist x such that ...". If the conclusion is "there exist x" then what is that x in the hypothesis?

In any case, given that, for some linear transformation there exist vector x and integer n such that [tex]T^n(x)= 0[/tex] but that [tex]T^{n-1}(x)\ne 0[/tex] (from which it follows that [tex]T^m(x)\ne 0[/tex] for any m< n), the suppose to the contrary that x, T(x), [tex]T^2(x)[/tex], ..., [tex]T^{n-1}(x)[/tex] are NOT linearly independent. Then there exist [tex]\{a_n\}[/tex], not all 0, such that [tex]a_0x+ a_1T(x)+\cdot\cdot\cdot+ a_{n-2}T^{n-2}(x)+ a_{n-}T^{n-1}(x)= 0[/tex]. Apply T to both sides: [tex]a_0T(x)+ a_1T^2(x)+ \cdot\cdot\cdot+ a_{n-1}T^{n-1}(x)+ a_nT^n(x)= a_0T(x)+ a_1T^2(x)+ \cdot\cdot\cdot+ a_{n-1}T^{n-1}(x)= 0[/tex].

Applying T n-1 times, and repeatedly using the fact that [tex]T^n(x)= 0[/tex], we arrive at [tex]a_0T^{n-1}(x)= 0[/tex]. If [tex]a_0\ne 0[/tex] it follows that [tex]T^{n-1}(x)= 0[/tex], a contradiction. If [tex]a_0= 0[/tex], we only need to apply T n-2 times to arrive at [tex]a_1T^{n-1}(x)= 0[/tex], etc.
 

1. What is a linear map?

A linear map is a mathematical function between two vector spaces that preserves the operations of vector addition and scalar multiplication. It is also known as a linear transformation or linear operator.

2. What does T^p(x)=0 mean?

T^p(x)=0 is an expression that represents a linear map where the output of the function is equal to the zero vector. This means that the linear map transforms every input vector into the zero vector.

3. How is linear independence shown?

Linear independence is shown by proving that the only solution to the equation T^p(x)=0 is the trivial solution, where all the coefficients of the input vectors are equal to zero. This means that the linear map does not have any redundant or linearly dependent vectors in its domain.

4. What is the role of the T^p(x)=0 condition in proving linear independence?

The T^p(x)=0 condition is essential in proving linear independence because it ensures that the linear map is a one-to-one function. This means that every output vector has a unique input vector, and there are no duplicate or redundant vectors in the domain. This condition is necessary for the linear map to have a linearly independent set of vectors.

5. Can T^p(x)=0 be used to prove linear independence for any linear map?

No, T^p(x)=0 can only be used to prove linear independence for linear maps that satisfy the conditions of being one-to-one and preserving vector addition and scalar multiplication. If a linear map does not meet these conditions, other methods must be used to prove linear independence.

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