Podcast
Questions and Answers
What is the condition to find an eigenvalue and an associated eigenvector of an n × n matrix A?
What is the condition to find an eigenvalue and an associated eigenvector of an n × n matrix A?
- Av = 0
- Av = λ + v
- Av = vλ
- Av = λv (correct)
What does the determinant of A - λI being equal to zero signify?
What does the determinant of A - λI being equal to zero signify?
- The matrix A is singular
- The system has no solution
- The system has a nontrivial solution (correct)
- The matrix A has no eigenvalues
What is the characteristic polynomial of a matrix A?
What is the characteristic polynomial of a matrix A?
- p(λ) = det(A) + det(λI)
- p(λ) = det(A + λI)
- p(λ) = det(A - λI) (correct)
- p(λ) = det(A)
What does the equation p(λ) = 0 represent?
What does the equation p(λ) = 0 represent?
In the context provided, if a root λ is found for the characteristic polynomial, what is it called?
In the context provided, if a root λ is found for the characteristic polynomial, what is it called?
When a nonzero column vector v satisfies Av = λv, what is it termed in relation to the matrix A?
When a nonzero column vector v satisfies Av = λv, what is it termed in relation to the matrix A?
What is the characteristic polynomial of the given matrix?
What is the characteristic polynomial of the given matrix?
Which of the following are roots of the characteristic polynomial?
Which of the following are roots of the characteristic polynomial?
When finding eigenvectors, for which eigenvalue do we solve the homogeneous system?
When finding eigenvectors, for which eigenvalue do we solve the homogeneous system?
In the context of the matrix A, what does λ represent in the characteristic polynomial?
In the context of the matrix A, what does λ represent in the characteristic polynomial?
What is the value of λ2, one of the roots of the characteristic polynomial?
What is the value of λ2, one of the roots of the characteristic polynomial?
What is the determinant used to find the characteristic polynomial?
What is the determinant used to find the characteristic polynomial?
What is the condition for a matrix to be singular?
What is the condition for a matrix to be singular?
What is the definition of diagonalization?
What is the definition of diagonalization?
How many linearly independent eigenvectors do we have when choosing z = 0?
How many linearly independent eigenvectors do we have when choosing z = 0?
When λ = 3, what is the eigenvector left as an exercise?
When λ = 3, what is the eigenvector left as an exercise?
What is an eigenspace?
What is an eigenspace?
For an n × n matrix A, how does the determinant relate to eigenvalues?
For an n × n matrix A, how does the determinant relate to eigenvalues?
What is the value of y in the system of equations after Gaussian elimination?
What is the value of y in the system of equations after Gaussian elimination?
What is the value of z in the system of equations after Gaussian elimination?
What is the value of z in the system of equations after Gaussian elimination?
What is the value of x in the eigenvector obtained by choosing x = 1?
What is the value of x in the eigenvector obtained by choosing x = 1?
What is the value of λ in the homogeneous system (A − λI )⃗ v = 0?
What is the value of λ in the homogeneous system (A − λI )⃗ v = 0?
What is the relationship between y and z in the system of equations after Gaussian elimination and interchange of rows?
What is the relationship between y and z in the system of equations after Gaussian elimination and interchange of rows?
What is the value of z in the general eigenvector x −3z −3 −3 y = 3z/2 = z 3/2 = 3/2 z z 1 1 (43)?
What is the value of z in the general eigenvector x −3z −3 −3 y = 3z/2 = z 3/2 = 3/2 z z 1 1 (43)?
What is the value of the eigenvalue λ in the given example?
What is the value of the eigenvalue λ in the given example?
What is the general form of the eigenvector for the given matrix A?
What is the general form of the eigenvector for the given matrix A?
What is the characteristic polynomial of the given matrix A?
What is the characteristic polynomial of the given matrix A?
What is the eigenvector corresponding to the eigenvalue λ = 1 in the given example?
What is the eigenvector corresponding to the eigenvalue λ = 1 in the given example?
What is the determinant of the matrix (A − λI ) in the given example?
What is the determinant of the matrix (A − λI ) in the given example?
What is the matrix A in the given example?
What is the matrix A in the given example?
Study Notes
Finding Eigenvalues and Eigenvectors
- To find eigenvalues and eigenvectors, we need to solve the homogeneous system (A - λI)v = 0, which is equivalent to det(A - λI) = 0.
- The determinant of A - λI is a polynomial of degree n, so we need to find the roots of the polynomial p(λ) = det(A - λI).
Characteristic Polynomial and Equation
- The polynomial p(λ) = det(A - λI) is called the characteristic polynomial of A.
- The equation p(λ) = 0 is termed the characteristic equation.
- If λ is a root of p, it is termed an eigenvalue of A.
Eigenvectors
- If v is a nonzero column vector satisfying Av = λv, it is an eigenvector of A.
- We say that v is an eigenvector corresponding to the eigenvalue λ.
Example 1
- Let A = [[2, -0.4707], [0.7481, 1.7481]], and v = [[0.2898], [0.9571]].
- Then, Av = 2v, so v is an eigenvector of A corresponding to eigenvalue 2.
Example 2
- Find the eigenvalues and eigenvectors of the matrix A = [[4, 8, 3], [0, -1, 0], [0, -2, 2]].
- The characteristic polynomial is p(λ) = (-1 - λ)(4 - λ)(2 - λ) = 0.
- The roots of the characteristic polynomial are λ1 = 4, λ2 = -1, and λ3 = 2.
Eigenvectors for λ = 4
- We solve the homogeneous system (A - λI)v = 0 to find the eigenvectors.
- The eigenvectors are [[-1, 1, 0]^T] and [[-1, 0, 1]^T].
Eigenvectors for λ = -1
- We solve the homogeneous system (A - λI)v = 0 to find the eigenvectors.
- The eigenvectors are [[-3z/2, 3z/2, z]^T], where z is a nonzero scalar.
Eigenvectors for λ = 2
- We solve the homogeneous system (A - λI)v = 0 to find the eigenvectors.
- The eigenvectors are [[-3z/2, 0, z]^T], where z is a nonzero scalar.
The Case of Repeated Roots
- Some Properties of Eigenvalues and Eigenvectors:
- A matrix A is singular if and only if it has a 0 eigenvalue.
- The eigenvectors corresponding to λ form a subspace called an eigenspace.
- If A is an n × n matrix, then det A = ∏λi, i = 1 to n.
Diagonalization
- Diagonalization involves using the eigenvectors of a matrix A to transform A into a diagonal matrix of eigenvalues.
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Description
Learn about the definition of eigenvalues and eigenvectors in linear algebra, and how to find them using the homogeneous system. Understand the conditions for a matrix to have eigenvalues and associated eigenvectors.