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Compute the matrix exponential \(e^{\mathrm{A} t}\) for each system \(\mathrm{x}^{\prime}=\mathrm{Ax}\) given. $$ x_{1}^{\prime}=11 x_{1}-15 x_{2}, x_{2}^{\prime}=6 x_{1}-8 x_{2} $$

Short Answer

Expert verified
The matrix exponential is found using diagonalization: \( e^{\mathbf{A}t} = \mathbf{P} e^{\mathbf{D}t} \mathbf{P}^{-1} \), with calculated \( \mathbf{P}, \mathbf{D} \).

Step by step solution

01

Write the System in Matrix Form

The given system of differential equations can be expressed as a matrix equation. Write the system as \( \mathbf{x}' = \mathbf{A} \mathbf{x} \), where \( \mathbf{A} \) is the coefficient matrix:\[ \mathbf{A} = \begin{pmatrix} 11 & -15 \ 6 & -8 \end{pmatrix} \]
02

Eigenvalues of the Matrix

To find the eigenvalues of \( \mathbf{A} \), solve the characteristic equation \( \det(\mathbf{A} - \lambda \mathbf{I}) = 0 \). Calculate the determinant:\[ \det(\begin{pmatrix} 11 - \lambda & -15 \ 6 & -8 - \lambda \end{pmatrix}) = (11 - \lambda)(-8 - \lambda) - (-15)(6) = 0 \]Simplify and solve the resulting quadratic equation for \( \lambda \).
03

Solve the Quadratic Equation

The characteristic equation becomes:\[ (11 - \lambda)(-8 - \lambda) + 90 = \lambda^2 - 3\lambda + 2 = 0 \]Solve for \( \lambda \) using the quadratic formula:\[ \lambda = \frac{-b \pm \sqrt{b^2 - 4ac}}{2a} = \frac{3 \pm \sqrt{1}}{2} \]The eigenvalues are \( \lambda_1 = 2 \) and \( \lambda_2 = 1 \).
04

Compute the Matrix Exponential

Since \( \mathbf{A} \) has distinct eigenvalues, we can use the formula for diagonalizable matrices. If \( \mathbf{A} = \mathbf{PDP}^{-1} \), where \( \mathbf{D} \) is the diagonal matrix of eigenvalues, then \( e^{\mathbf{A}t} = \mathbf{P} e^{\mathbf{D}t} \mathbf{P}^{-1} \).First, confirm that \( \mathbf{A} \) is diagonalizable:1. Find eigenvectors corresponding to \( \lambda = 2 \) and \( \lambda = 1 \).2. Form matrix \( \mathbf{P} \) with these eigenvectors as columns.3. Compute \( e^{\mathbf{D}t} \) where \( \mathbf{D} = \begin{pmatrix} 2 & 0 \ 0 & 1 \end{pmatrix} \) and \( e^{\mathbf{D}t} = \begin{pmatrix} e^{2t} & 0 \ 0 & e^{t} \end{pmatrix} \).4. Finally calculate \( e^{\mathbf{A}t} = \mathbf{P} e^{\mathbf{D}t} \mathbf{P}^{-1} \).

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Key Concepts

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

Eigenvalues
Eigenvalues are fundamental to understanding matrix characteristics. They tell us about the behavior of certain matrix transformations, particularly in linear systems.
To find eigenvalues, you solve the characteristic equation, which is derived from the formula \( \det(\mathbf{A} - \lambda \mathbf{I}) = 0 \). Here, \( \lambda \) represents the eigenvalues, \( \mathbf{A} \) is the matrix, and \( \mathbf{I} \) is the identity matrix of the same size as \( \mathbf{A} \).
  • This equation leads to a polynomial whose solutions give the eigenvalues.
  • In our case, solving the characteristic equation for matrix A provided the eigenvalues \( \lambda_1 = 2 \) and \( \lambda_2 = 1 \).
Understanding eigenvalues gives insight into the stability and dynamics of systems described by matrices. Eigenvalues are critical when working with diagonalizable matrices and evaluating matrix exponentials.
Diagonalizable Matrices
A matrix is said to be diagonalizable if it can be expressed in the form \( \mathbf{A} = \mathbf{PDP}^{-1} \), where \( \mathbf{D} \) is a diagonal matrix containing the eigenvalues of \( \mathbf{A} \), and \( \mathbf{P} \) is the matrix of eigenvectors.
  • Diagonalization simplifies complex matrix calculations by transforming the matrix to a simpler, equivalent diagonal form.
  • This simplification is particularly useful for calculating matrix exponentials, a powerful tool in solving linear systems of differential equations, as it avoids needing complex integrations.
For the given system, we confirmed diagonalizability since \( \mathbf{A} \) had two distinct eigenvalues, suggesting that it can be diagonalized. Therefore, the matrix exponential \( e^{\mathbf{A}t} \) can be computed using the diagonal form, which involves less computational effort and lessens potential for error in calculations.
Systems of Differential Equations
Systems of differential equations describe how multiple functions change with respect to one or more variables, typically time. They are commonly written in the matrix form \( \mathbf{x}' = \mathbf{A} \mathbf{x} \), where \( \mathbf{x} \) is a vector of functions dependent on time, and \( \mathbf{A} \) is a matrix of coefficients.
  • This form allows the use of linear algebra techniques to analyze the system's behavior and solve for unknown functions.
  • The matrix exponential \( e^{\mathbf{A}t} \) is a key concept in solving these systems, as it provides a general solution that describes the evolution of the system's state over time.
For the exercise presented, we organized the differential equations into this matrix form, facilitating the use of matrix operations to derive solutions. With proper understanding of matrix exponentials and diagonalization, this method proves not only efficient but also enhances comprehension of complex dynamic systems.

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Most popular questions from this chapter

Deal with the open three-tank system Fig. 5.2.2. Fresh water flows into tank 1 ; mixed brine flows om tank 1 into tank 2 , from tank 2 into tank 3 , and out of tank all at the given flow rate \(r\) gallons per minute. The initial mounts \(x_{1}(0)=x_{0}(l b), x_{2}(0)=0\), and \(x_{3}(0)=0\) of salt the three tanks are given, as are their volumes \(V_{1}, V_{2}\), and \(\mathrm{V}_{\mathrm{a}}\) (in gallons). First solve for the amounts of salt in the three tanks at time \(t\), then determine the maximal amount of salt that tank 3 ever contains. Finally, construct a figure showing the graphs of \(x_{1}(t), x_{2}(t)\), and \(x_{3}(t) .\) $$ r=60, x_{0}=40, V_{1}=20, V_{2}=12, V_{3}=60 $$

Show that the matrix \(A\) is nilpotent and then use this fact to find (as in Example 3) the matrix exponential \(e^{\mathrm{A} l}\). $$ \mathbf{A}=\left[\begin{array}{ll} 1 & -1 \\ 1 & -1 \end{array}\right] $$

Apply the eigenvalue method of this section to find a general solution of the given system. If initial values are given, find also the corresponding particular solution. For each problem, use a computer system or graphing calculator to construct a direction field and typical solution curves for the given system. $$ x_{1}^{\prime}=x_{1}+2 x_{2}, x_{2}^{\prime}=2 x_{1}+x_{2} $$

Problems deal with the mass-and-spring system shown in Fig. 5.3.11 with stiffness matrix $$ \mathbf{K}=\left[\begin{array}{cc} -\left(k_{1}+k_{2}\right) & k_{2} \\ k_{2} & -\left(k_{2}+k_{3}\right) \end{array}\right] $$ and with the given mks values for the masses and spring constants. Find the two natural frequencies of the system and describe its two natural modes of oscillation. $$ m_{1}=m_{2}=1 ; k_{1}=1, k_{2}=2, k_{3}=1 $$

Find general solutions of the systems in Problems 1 through 22\. In Problems I through 6, use a computer system or graphing calculator to construct a direction field and typical solution curves for the given system. \(\mathbf{x}^{\prime}=\left[\begin{array}{rrr}0 & 0 & 1 \\ -5 & -1 & -5 \\ 4 & 1 & -2\end{array}\right] \mathbf{x}\)

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