Supposedly a transformation $T: V \to V$ is diagonalisable iff there exists a basis of $V$ consisting only of eigenvectors of $T$. Can someone show me why this is true? I don't really know where to even start other than "Let $[v_1, ..., v_n]$ be a basis of $V$ with $v_i$ eigenvectors".
2026-03-27 04:34:18.1774586058
Alternative definition of diagonalisable transformation
31 Views Asked by Bumbble Comm https://math.techqa.club/user/bumbble-comm/detail At
1
There are 1 best solutions below
Related Questions in VECTOR-SPACES
- Alternate basis for a subspace of $\mathcal P_3(\mathbb R)$?
- Does curl vector influence the final destination of a particle?
- Closure and Subsets of Normed Vector Spaces
- Dimension of solution space of homogeneous differential equation, proof
- Linear Algebra and Vector spaces
- Is the professor wrong? Simple ODE question
- Finding subspaces with trivial intersection
- verifying V is a vector space
- Proving something is a vector space using pre-defined properties
- Subspace of vector spaces
Related Questions in EIGENVALUES-EIGENVECTORS
- Stability of system of parameters $\kappa, \lambda$ when there is a zero eigenvalue
- Stability of stationary point $O(0,0)$ when eigenvalues are zero
- Show that this matrix is positive definite
- Is $A$ satisfying ${A^2} = - I$ similar to $\left[ {\begin{smallmatrix} 0&I \\ { - I}&0 \end{smallmatrix}} \right]$?
- Determining a $4\times4$ matrix knowing $3$ of its $4$ eigenvectors and eigenvalues
- Question on designing a state observer for discrete time system
- Evaluating a cubic at a matrix only knowing only the eigenvalues
- Eigenvalues of $A=vv^T$
- A minimal eigenvalue inequality for Positive Definite Matrix
- Construct real matrix for given complex eigenvalues and given complex eigenvectors where algebraic multiplicity < geometric multiplicity
Related Questions in LINEAR-TRANSFORMATIONS
- Unbounded linear operator, projection from graph not open
- I don't understand this $\left(\left[T\right]^B_C\right)^{-1}=\left[T^{-1}\right]^C_B$
- A different way to define homomorphism.
- Linear algebra: what is the purpose of passive transformation matrix?
- Find matrix representation based on two vector transformations
- Is $A$ satisfying ${A^2} = - I$ similar to $\left[ {\begin{smallmatrix} 0&I \\ { - I}&0 \end{smallmatrix}} \right]$?
- Let $T:V\to W$ on finite dimensional vector spaces, is it possible to use the determinant to determine that $T$ is invertible.
- Basis-free proof of the fact that traceless linear maps are sums of commutators
- Assuming that A is the matrix of a linear operator F in S find the matrix B of F in R
- For what $k$ is $g_k\circ f_k$ invertible?
Related Questions in DIAGONALIZATION
- Determining a $4\times4$ matrix knowing $3$ of its $4$ eigenvectors and eigenvalues
- Show that $A^m=I_n$ is diagonalizable
- Simultaneous diagonalization on more than two matrices
- Diagonalization and change of basis
- Is this $3 \times 3$ matrix diagonalizable?
- Matrix $A\in \mathbb{R}^{4\times4}$ has eigenvectors $\bf{u_1,u_2,u_3,u_4}$ satisfying $\bf{Au_1=5u_1,Au_2=9u_2}$ & $\bf{Au_3=20u_3}$. Find $A\bf{w}$.
- Block diagonalizing a Hermitian matrix
- undiagonizable matrix and annhilating polynom claims
- Show that if $\lambda$ is an eigenvalue of matrix $A$ and $B$, then it is an eigenvalue of $B^{-1}AB$
- Is a complex symmetric square matrix with zero diagonal diagonalizable?
Trending Questions
- Induction on the number of equations
- How to convince a math teacher of this simple and obvious fact?
- Find $E[XY|Y+Z=1 ]$
- Refuting the Anti-Cantor Cranks
- What are imaginary numbers?
- Determine the adjoint of $\tilde Q(x)$ for $\tilde Q(x)u:=(Qu)(x)$ where $Q:U→L^2(Ω,ℝ^d$ is a Hilbert-Schmidt operator and $U$ is a Hilbert space
- Why does this innovative method of subtraction from a third grader always work?
- How do we know that the number $1$ is not equal to the number $-1$?
- What are the Implications of having VΩ as a model for a theory?
- Defining a Galois Field based on primitive element versus polynomial?
- Can't find the relationship between two columns of numbers. Please Help
- Is computer science a branch of mathematics?
- Is there a bijection of $\mathbb{R}^n$ with itself such that the forward map is connected but the inverse is not?
- Identification of a quadrilateral as a trapezoid, rectangle, or square
- Generator of inertia group in function field extension
Popular # Hahtags
second-order-logic
numerical-methods
puzzle
logic
probability
number-theory
winding-number
real-analysis
integration
calculus
complex-analysis
sequences-and-series
proof-writing
set-theory
functions
homotopy-theory
elementary-number-theory
ordinary-differential-equations
circles
derivatives
game-theory
definite-integrals
elementary-set-theory
limits
multivariable-calculus
geometry
algebraic-number-theory
proof-verification
partial-derivative
algebra-precalculus
Popular Questions
- What is the integral of 1/x?
- How many squares actually ARE in this picture? Is this a trick question with no right answer?
- Is a matrix multiplied with its transpose something special?
- What is the difference between independent and mutually exclusive events?
- Visually stunning math concepts which are easy to explain
- taylor series of $\ln(1+x)$?
- How to tell if a set of vectors spans a space?
- Calculus question taking derivative to find horizontal tangent line
- How to determine if a function is one-to-one?
- Determine if vectors are linearly independent
- What does it mean to have a determinant equal to zero?
- Is this Batman equation for real?
- How to find perpendicular vector to another vector?
- How to find mean and median from histogram
- How many sides does a circle have?
You have the right idea. If $[v_1, ..., v_n]$ is a basis of $V$ with $v_i$ eigenvectors, let us try to understand how $T$ would look in this basis (I'm assuming you already know how to find a representing matrix of a linear transofrmation, given some basis). Since $T$ acts on the basis element $v_1$ by scaling it by a factor of $\lambda_1$ (since it is an eigenvector), the first column of $T$ would be - $\begin{pmatrix} \lambda_1 \\ 0 \\ \vdots \\ 0 \end{pmatrix}$. Similarly, the second column of $T$ would be - $\begin{pmatrix} 0 \\ \lambda_2 \\ \vdots \\ 0 \end{pmatrix}$, and so on. Overall, you will get a diagonal matrix.
For the other way around - if $T$ is diagonal in some basis, you know that it acts on the first basis vector by scaling it by the factor on the corresponding part of the diagonal (again, I'm assuming you know the general method of finding a representing matrix, given some basis). Similarly, each basis vector is scaled by the corresponding part of the diagonal. Since $T$ acts on each basis vector by scaling it, we conclude that the basis consists only of eigenvectors of $T$.