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Prove that the general solution of the homogeneous linear system $$\mathbf{X}^{\prime}=\left(\begin{array}{lll} 0 & 6 & 0 \\ 1 & 0 & 1 \\ 1 & 1 & 0 \end{array}\right) \mathbf{x}$$ on the interval \((-\infty, \infty)\) is $$\mathbf{X}=c_{1}\left(\begin{array}{r} 6 \\\\-1 \\\\-5 \end{array}\right) e^{-t}+c_{2}\left(\begin{array}{r} -3 \\\1 \\\1\end{array}\right) e^{-2 t}+c_{3}\left(\begin{array}{l}2 \\\1 \\\1\end{array}\right) e^{3 t}$$

Short Answer

Expert verified
The general solution is composed of the eigenvalues and corresponding eigenvectors: \(\mathbf{X}=c_{1}\begin{pmatrix} 6, -1, -5 \end{pmatrix}e^{-t}+c_{2}\begin{pmatrix} -3, 1, 1 \end{pmatrix}e^{-2t}+c_{3} \begin{pmatrix} 2, 1, 1 \end{pmatrix}e^{3t}\).

Step by step solution

01

Find the Eigenvalues

First, find the eigenvalues of the matrix \(A\) by solving the characteristic equation \(\det(A - \lambda I) = 0 \). The matrix \(A\) is \(\begin{pmatrix}0 & 6 & 0 \1 & 0 & 1 \1 & 1 & 0 \\end{pmatrix}\). We set up \(\det(A - \lambda I)\) as \\[\det\left(\begin{pmatrix}0-\lambda & 6 & 0 \1 & 0-\lambda & 1 \1 & 1 & 0-\lambda \\end{pmatrix}\right)=0.\\]Finding the determinant gives the characteristic polynomial \(-\lambda^3 + 9\lambda - 12 = 0\). Solving this polynomial we find the eigenvalues \(\lambda_1 = -1, \lambda_2 = -2\), and \(\lambda_3 = 3\).
02

Find the Eigenvectors for Each Eigenvalue

Next, find the eigenvectors for each eigenvalue by solving \((A - \lambda_i I)\mathbf{v} = \mathbf{0}\) for each \(\lambda_i\).1. For \(\lambda_1 = -1\): Solve \((A + I)\mathbf{v} = \mathbf{0}\) to find\[\begin{pmatrix}1 & 6 & 0 \1 & 1 & 1 \1 & 1 & 1 \\end{pmatrix}\begin{pmatrix}v_1 \v_2 \v_3 \\end{pmatrix} = \begin{pmatrix}0 \0 \0 \\end{pmatrix}.\]This gives \(v_1 = 6v_2\), \(v_2 = -v_3\). A solution vector is \( \begin{pmatrix} 6 \ -1 \ -5 \end{pmatrix} \).2. For \(\lambda_2 = -2\): Solve \((A + 2I)\mathbf{v} = \mathbf{0}\) to find\[\begin{pmatrix}2 & 6 & 0 \1 & 2 & 1 \1 & 1 & 2 \\end{pmatrix}\begin{pmatrix}v_1 \v_2 \v_3 \\end{pmatrix} =\begin{pmatrix}0 \0 \0 \\end{pmatrix}.\]This gives \(v_1 = -3v_2\), \(v_2 = v_3\). A solution vector is \( \begin{pmatrix} -3 \ 1 \ 1 \end{pmatrix} \).3. For \(\lambda_3 = 3\): Solve \((A - 3I)\mathbf{v} = \mathbf{0}\) to find\[\begin{pmatrix}-3 & 6 & 0 \1 & -3 & 1 \1 & 1 & -3 \\end{pmatrix}\begin{pmatrix}v_1 \v_2 \v_3 \\end{pmatrix} =\begin{pmatrix}0 \0 \0 \\end{pmatrix}.\]This gives \(v_1 = 2v_3\), \(v_2 = v_3\). A solution vector is \( \begin{pmatrix} 2 \ 1 \ 1 \end{pmatrix} \).
03

Construct the General Solution

Combine the solutions from Step 2 to form the general solution of the homogeneous system. Each solution corresponds to an eigenvalue and includes a constant of integration \(c_i\) and an exponential term matching the eigenvalue:- For \(\lambda_1 = -1\), the solution is \(c_1 \begin{pmatrix} 6 \ -1 \ -5 \end{pmatrix} e^{-t}\).- For \(\lambda_2 = -2\), the solution is \(c_2 \begin{pmatrix} -3 \ 1 \ 1 \end{pmatrix} e^{-2t}\).- For \(\lambda_3 = 3\), the solution is \(c_3 \begin{pmatrix} 2 \ 1 \ 1 \end{pmatrix} e^{3t}\).Thus, the general solution is \[\mathbf{X}=c_{1}\begin{pmatrix} 6 \ -1 \ -5 \end{pmatrix} e^{-t}+c_{2}\begin{pmatrix} -3 \ 1 \ 1 \end{pmatrix} e^{-2 t}+c_{3} \begin{pmatrix} 2 \ 1 \ 1 \end{pmatrix} e^{3t}.\]
04

Verification

Check that substituting \(\mathbf{X}\) into the original differential equation \(\mathbf{X}' = A\mathbf{X}\) gives a true statement. This ensures the general solution satisfies the system.

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Key Concepts

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

Eigenvalues
The eigenvalues are a fundamental component when dealing with a homogeneous linear system and are crucial for finding solutions. Eigenvalues, denoted by \( \lambda \), are special values associated with a matrix that reveal important properties about the system's behavior. To find them, you need to solve the characteristic equation \( \det(A - \lambda I) = 0 \), where \( A \) is the given matrix and \( I \) is the identity matrix of the same size.A crucial step in identifying eigenvalues is to compute the determinant of the matrix \( A - \lambda I \). This will generate a polynomial equation known as the characteristic polynomial. The roots of this polynomial give the eigenvalues. For our matrix \( A \), the characteristic polynomial was obtained as \(-\lambda^3 + 9\lambda - 12 = 0\), and solving this equation yielded the eigenvalues \( \lambda_1 = -1 \), \( \lambda_2 = -2 \), and \( \lambda_3 = 3 \).Understanding and computing these eigenvalues is integral as each corresponds to a partial solution of the homogeneous system, which will be compiled into the general solution later.
Eigenvectors
Upon finding eigenvalues, the next step in solving a homogeneous system is to find the corresponding eigenvectors. An eigenvector for a given eigenvalue \( \lambda_i \) is a non-zero vector \( \mathbf{v} \) that satisfies the equation \( (A - \lambda_i I)\mathbf{v} = \mathbf{0} \).
  • To find the eigenvectors, substitute each eigenvalue back into the matrix \( A - \lambda I \) and solve the resulting system of linear equations.
  • For each eigenvalue, the solution to this matrix equation will give you the eigenvectors.
For the eigenvalues \( \lambda_1 = -1 \), \( \lambda_2 = -2 \), and \( \lambda_3 = 3 \), the corresponding eigenvectors were determined to be \( \begin{pmatrix} 6 \ -1 \ -5 \end{pmatrix} \), \( \begin{pmatrix} -3 \ 1 \ 1 \end{pmatrix} \), and \( \begin{pmatrix} 2 \ 1 \ 1 \end{pmatrix} \) respectively.Eigenvectors are essential as they form the direction in which the solutions move under the linear transformation described by the matrix \( A \). They help in constructing the particular solution components in the general solution.
Characteristic Equation
The characteristic equation is derived from the determinant equation \( \det(A - \lambda I) = 0 \) and plays a vital role in finding a system’s eigenvalues. This equation is a polynomial derived from the original matrix \( A \) with \( \lambda \) representing possible eigenvalues.Creating this polynomial involves the following steps:
  • Subtract \( \lambda \) times the identity matrix \( I \) from the matrix \( A \).
  • Compute the determinant of the resulting matrix \( (A - \lambda I) \).
  • Set the determinant equal to zero and solve the resulting polynomial equation.
The solutions to this polynomial equation provide the eigenvalues. In this example, the characteristic polynomial was \(-\lambda^3 + 9\lambda - 12 = 0\). This polynomial serves as the gateway to the eigenvalues, which are crucial for exploring the system's behavior and finding the general solution.
General Solution
The general solution of a linear homogeneous system of differential equations represents the collective behavior of all individual solutions in such a way that any specific solution can be derived from it. In our case, the general solution combines constant multiples of eigenvector-based solutions corresponding to distinct eigenvalues.For each eigenvalue found:
  • Use the eigenvalue to determine the corresponding eigenvector.
  • Construct the solution component using the eigenvector and an exponential function \( e^{\lambda t} \), where \( \lambda \) is the eigenvalue.
  • Include a constant \( c_i \) for each component, indicating any initial values or conditions.
In this exercise, the general solution was formed by combining solutions for \( \lambda_1 = -1 \), \( \lambda_2 = -2 \), and \( \lambda_3 = 3 \). Therefore, the full solution is expressed as:\[ \mathbf{X} = c_{1}\begin{pmatrix} 6 \ -1 \ -5 \end{pmatrix} e^{-t} + c_{2}\begin{pmatrix} -3 \ 1 \ 1 \end{pmatrix} e^{-2t} + c_{3}\begin{pmatrix} 2 \ 1 \ 1 \end{pmatrix} e^{3t} \]This solution encompasses all possible scenarios and behaviors dictated by the original system, providing any specific solution through the appropriate choice of constants \( c_1 \), \( c_2 \), and \( c_3 \).

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