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\( \begin{array}{l}\text { d all values of } a \text { for which the linear system } \\ \qquad \begin{aligned} x_{1}+2 x_{2}+x_{3} & =3 \\ 2 x_{1}+3 x_{2}+3 x_{3} & =4\end{aligned} \\ \qquad 3 x_{1}+3 x_{2}+\left(a^{2}-3\right) x_{3}=a\end{array} ~=~ \) (a) no solution, (b) a unique solution and (c) infinitely many solutions.

Ask by Bond Lewis. in South Africa
Mar 15,2025

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The system has: - (a) no solution when \( a = -3 \), - (b) a unique solution when \( a \neq 3 \) and \( a \neq -3 \), - (c) infinitely many solutions when \( a = 3 \).

Solución

We start with the linear system \[ \begin{array}{rcl} x_1 + 2x_2 + x_3 & = & 3, \\ 2x_1 + 3x_2 + 3x_3 & = & 4, \\ 3x_1 + 3x_2 + (a^2-3)x_3 & = & a. \end{array} \] **Step 1. Solve the first two equations.** From the first equation, express \(x_1\) in terms of \(x_2\) and \(x_3\): \[ x_1 = 3 - 2x_2 - x_3. \] Substitute \(x_1\) into the second equation: \[ 2(3-2x_2-x_3)+3x_2+3x_3=4. \] Simplify the equation: \[ 6 - 4x_2 - 2x_3 + 3x_2 + 3x_3 = 4, \] \[ 6 - x_2 + x_3 = 4. \] Solve for \(x_2\): \[ -x_2 = 4 - 6 - x_3 = -2 - x_3, \] \[ x_2 = 2 + x_3. \] Now substitute \(x_2 = 2+x_3\) back into \[ x_1 = 3 - 2x_2 - x_3: \] \[ x_1 = 3 - 2(2+x_3) - x_3 = 3 - 4 - 2x_3 - x_3 = -1 - 3x_3. \] Thus, the general solution of the first two equations is given by \[ x_1 = -1 - 3t,\quad x_2 = 2 + t,\quad x_3 = t, \] where \(t\) is a free parameter. **Step 2. Substitute into the third equation.** Substitute \(x_1 = -1-3t\), \(x_2 = 2+t\) and \(x_3 = t\) into the third equation: \[ 3(-1-3t) + 3(2+t) + (a^2-3)t = a. \] Simplify: \[ -3 - 9t + 6 + 3t + (a^2-3)t = a. \] Combine like terms: \[ 3 + \bigl[-9t+3t+(a^2-3)t\bigr] = a. \] Calculate the coefficient of \(t\): \[ -9t+3t=( -6t), \quad \text{so} \quad -6t + (a^2-3)t = (a^2-9)t. \] Thus, we have \[ 3 + (a^2-9)t = a. \] Solve for \(t\): \[ (a^2-9)t = a - 3. \] Now, we consider two main cases. **Case (i): \(a^2-9 \neq 0\).** Since \[ a^2-9 = (a-3)(a+3), \] this condition means \(a\neq 3\) and \(a\neq -3\). Then we have \[ t = \frac{a-3}{a^2-9} = \frac{a-3}{(a-3)(a+3)} = \frac{1}{a+3} \quad \text{(provided \(a\neq 3\))}. \] In this case, \(t\) (and hence \(x_1, x_2, x_3\)) is uniquely determined. Therefore, the system has a unique solution. **Case (ii): \(a^2-9 = 0\).** This gives \(a=3\) or \(a=-3\). - **Subcase (a): \(a=3\).** Substitute \(a=3\) into \[ 3 + (a^2-9)t = a: \] Since \(3^2-9 = 9-9=0\), the equation becomes \[ 3 = 3. \] This identity holds for all \(t\). Hence, there is no new restriction on \(t\) and infinitely many solutions occur. - **Subcase (b): \(a=-3\).** For \(a=-3\), note that \((-3)^2-9=9-9=0\) and the equation becomes \[ 3 = -3, \] which is a contradiction. Therefore, the system has no solution for \(a=-3\). **Answer Summary:** - (a) The system has no solution when \(a = -3\). - (b) The system has a unique solution when \(a \neq 3\) and \(a \neq -3\). - (c) The system has infinitely many solutions when \(a = 3\).

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Mind Expander

To determine the values of \( a \) that correspond to the three scenarios (no solution, unique solution, infinitely many solutions), we can analyze the augmented matrix corresponding to the linear system: \[ \begin{bmatrix} 1 & 2 & 1 & | & 3 \\ 2 & 3 & 3 & | & 4 \\ 3 & 3 & a^2 - 3 & | & a \end{bmatrix} \] By applying row reduction (Gaussian elimination), we can transform this matrix to investigate the conditions for each scenario. For a unique solution to exist, the matrix must have a rank equal to the number of variables (which is 3 in this case). For infinitely many solutions, the rank must be less than 3, but the system must still be consistent. Conversely, for there to be no solutions, the system must be inconsistent. Calculating the determinant of the coefficient matrix will help us assess these scenarios. If the determinant is zero, we will check for consistency via the augmented part. 1. **No solution:** This occurs when the system has contradictory equations. It can happen, for example, if \( a \) is chosen such that the last row indicates a contradiction (like \( 0 = 1 \)). 2. **Unique solution:** For a unique solution, ensure the determinant of the coefficient matrix is non-zero. This is valid for specific ranges of \( a \) not leading to contradictions in the third row. 3. **Infinitely many solutions:** Occurs when we have fewer than 3 pivot positions in the reduced row echelon form, suggesting dependence among the equations. Now let’s outline the findings for the given system: - **For (a) no solution:** It occurs when \( a = 3 \). - **For (b) a unique solution:** Values like \( -1 \) and other non-specific values resulting in a non-zero determinant. - **For (c) infinitely many solutions:** It occurs for certain values like \( 0 \). A complete solution would require solving for these conditions in detail. Would you like to explore one of these scenarios further?

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