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Find the cizenvalues and eigenvectors of the matrices(5445)

Short Answer

Expert verified
Eigenvalues: 9 and 1, Eigenvectors: (1 1) and (1 1)

Step by step solution

01

- Write Down the Matrix

First, look at the given matrix: A=(54 45)
02

- Set Up the Characteristic Equation

The characteristic equation is found using the formula det(AλI)=0 where I is the identity matrix and λ represents the eigenvalues. For matrix A, this becomes: |5λ4 45λ|=0
03

- Calculate the Determinant

Calculate the determinant of the matrix (5λ4 45λ). Expand this determinant: (5λ)(5λ)(4)(4)=λ210λ+2516=λ210λ+9
04

- Solve the Characteristic Polynomial

Set the characteristic polynomial equal to zero and solve for λ: λ210λ+9=0 Solving this quadratic equation using the quadratic formula λ=b±b24ac2a, where a=1, b=10, and c=9. λ=10±100362=10±82 Thus, the eigenvalues are: λ1=9andλ2=1
05

- Find the Eigenvectors

For each eigenvalue, solve the equation (AλI)x=0. First, for λ1=9: (594 459)(x1 x2)=(0 0) Simplifying: (44 44)(x1 x2)=(0 0) This gives 4x14x2=0, which simplifies to x1=x2. Choose x2=t, then: x1=t Therefore, an eigenvector for λ1=9 is: (1 1). Similarly, for λ2=1: (514 451)(x1 x2)=(0 0) Simplifying: (44 44)(x1 x2)=(0 0) This gives 4x14x2=0, which simplifies to x1=x2. Choose x2=t, then: x1=t Therefore, an eigenvector for λ2=1 is: (1 1).

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

matrix algebra
Matrix algebra is a branch of mathematics that deals with matrices and their operations. Matrices are rectangular arrays of numbers, symbols, or expressions arranged in rows and columns. You can add, subtract, and multiply matrices under certain conditions. In this exercise, we work with a 2x2 matrix:
  • To add or subtract matrices, ensure they are of the same dimension.
  • Matrix multiplication involves the dot product of rows and columns and requires the number of columns in the first matrix to equal the number of rows in the second matrix.
  • The identity matrix, denoted as I, is a special matrix with 1s on the diagonal and 0s elsewhere.
Matrix algebra is fundamental in linear algebra, and it forms the basis for understanding concepts like eigenvalues and eigenvectors.
characteristic equation
The characteristic equation is essential for finding the eigenvalues of a matrix. It is derived from the determinant of the matrix AλI, where λ represents the eigenvalues and I is the identity matrix of the same size as A.In this exercise, we set up the characteristic equation for the given matrix as follows:|5λ4\-45λ|=0Calculate the determinant and expand:(5λ)(5λ)(4)(4)=λ210λ+2516This simplifies to the characteristic polynomial:λ210λ+9=0Solving this equation gives us the eigenvalues of the matrix.
determinant
A determinant is a scalar value associated with a square matrix and is used in various matrix operations, including finding eigenvalues via the characteristic equation. For a 2x2 matrix (ab cd), the determinant is calculated as:det(A)=adbcIn our exercise, the determinant of the matrix (5λ4 45λ) is found by calculating:(5λ)(5λ)(4)(4)=λ210λ+2516The result is the characteristic polynomial that we set to zero to find the eigenvalues. Determinants help determine if a matrix is invertible and play a crucial role in linear transformations.
quadratic equation
A quadratic equation is a second-order polynomial equation in a single variable x, with the general form ax2+bx+c=0. Quadratic equations can be solved using methods like factoring, completing the square, or the quadratic formula:λ=b±b24ac2aIn our exercise, we solve the characteristic polynomial λ210λ+9=0 using the quadratic formula. Here, a=1, b=10, and c=9:λ=10±100362=10±82This gives us the eigenvalues λ1=9 and λ2=1. Understanding quadratic equations is vital for solving characteristic polynomials and finding eigenvalues.

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