Chapter 7: Problem 9
Suppose \(T \in \mathcal{L}(V)\) and \(m\) is a nonnegative integer such that range \(T^{m}=\) range \(T^{m+1}\). Prove that range \(T^{k}=\) range \(T^{m}\) for all \(k>m\).
Short Answer
Expert verified
By induction, we have proved that range \(T^{k}=\) range \(T^{m}\) for all \(k > m\).
Step by step solution
01
Introduce terminology
We want to demonstrate that range \(T^{k}=\) range \(T^{m}\) for all \(k > m\). Let \(v \in V\) be an arbitrary element in the vector space V.
02
We show the result holds for k=m+1 and any arbitrary v from V
Given the condition that range \(T^m =\) range \(T^{m+1}\), we can find \(v' \in V\), such that
\(T^{m+1}(v') = T^m(v)\)
03
Prove the result holds for k > m
We want to show that for all \(k > m\), range \(T^{k}=\) range \(T^{m}\). We will use induction.
1. Base Case (k=m+1): As given, the condition holds for k = m+1 by definition.
Now we assume the condition holds for some \(k = p\) where \(p > m\) and show that it will also hold for \(k = p+1\).
2. Inductive Hypothesis: Assume that range \(T^p =\) range \(T^m\).
3. Induction step: We need to show that range \(T^{p+1} =\) range \(T^m\).
Let \(T^m(v_p) = T^p(v')\) for some \(v_p, v' \in V\). Now, we apply the operator T to both sides of the equation:
\(T^{m+1}(v_p) = T^{p+1}(v')\)
Since we have assumed the condition to be true for \(k = p\), we know that range \(T^p =\) range \(T^m\). Therefore, there exists a vector \(v'' \in V\) such that \(T^m(v'') = T^{m+1}(v_p)\). By substitution, we get
\(T^m(v'') = T^{p+1}(v')\)
Which means range \(T^{p+1} =\) range \(T^m\). Thus, our induction step is completed.
By induction, we can conclude that range \(T^{k}=\) range \(T^{m}\) for all \(k > m\).
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Vector Space
A vector space is a fundamental concept in linear algebra. It is a collection of objects called vectors, which can be added together and multiplied by scalars (numbers), such as real numbers or complex numbers. In a vector space, there are certain properties that must be satisfied:
- Closure under Addition: If you add two vectors in the space, the result is also in the space.
- Closure under Scalar Multiplication: If you multiply a vector by a scalar, the result is still in the space.
- Associative and Commutative Properties: Adding vectors is both associative and commutative.
- Existence of an Identity Element: There is a zero vector in the space which, when added to any vector, does not change the vector.
- Inverse Elements: For every vector, there's an inverse vector such that their sum is the zero vector.
Range of an Operator
The range of an operator, often denoted as range(T), is a critical concept in functional analysis and linear algebra. It refers to the set of all possible outputs (or images) of a linear operator when applied to every vector in the given vector space. If we have a linear operator \( T \) acting on vector space \( V \), the range of \( T \) consists of all vectors \( w \) such that \( w = T(v) \) for some vector \( v \) in \( V \).
Key points include:
Key points include:
- Subset of the Codomain: The range is always a subset of the vector space that the operator maps to, called the codomain.
- Linear Subspace: The range itself is a vector space.
- Describes Image: It's essentially the image that the operator produces from the domain space.
Induction Proof
Induction proof is a commonly used mathematical technique to prove statements that are formulated for all natural numbers. It works in two main steps:
- Base Case: Show that a statement holds for the initial value, often \( n = 1 \) or some starting point given in the problem.
- Inductive Step: Assume the statement is true for some arbitrary natural number \( n = k \), then prove it is true for \( n = k+1 \).
Functional Analysis
Functional analysis is a branch of mathematical analysis that studies spaces of functions and their transformations. It often explores infinite-dimensional vector spaces and investigates linear operators acting upon them. This branch of analysis is where operators like \( T^k \) exist and is crucial for exploring concepts like the range of an operator.
Key features of functional analysis include:
Key features of functional analysis include:
- Banach and Hilbert Spaces: These are specific types of vector spaces used frequently in functional analysis, where the operators perform actions similar to functions.
- Spectral Theory: This is another important area, focusing on the spectrum of operators, much like eigenvalues in finite-dimensional space.
- Applications: Functional analysis has vast applications in quantum mechanics, signal processing, and other fields involving complex, typically infinite-dimensional systems.