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Matrices & Determinants
Matrices and Determinants
Medium

Question

If the system of linear equations 7x+11y+αz=135x+4y+7z=β175x+194y+57z=361\begin{aligned} & 7 x+11 y+\alpha z=13 \\\\ & 5 x+4 y+7 z=\beta \\\\ & 175 x+194 y+57 z=361 \end{aligned} has infinitely many solutions, then α+β+2\alpha+\beta+2 is equal to :

Options

Solution

1. Key Concepts and Formulas

  • System of Linear Equations: A system of nn linear equations in nn variables, typically represented as AX=BAX=B, has infinitely many solutions if and only if:
    • The determinant of the coefficient matrix AA is zero (det(A)=0\det(A) = 0). This implies that the rows (and columns) of AA are linearly dependent.
    • The rank of the coefficient matrix AA is equal to the rank of the augmented matrix [AB][A|B], and this rank is less than the number of variables (nn).
  • Linear Dependence and Consistency: For a system to have infinitely many solutions, it means that at least one equation is a linear combination of the other equations, and this linear relationship must also hold true for the constant terms. If the determinant is zero but the constant terms do not follow the same linear relationship, the system is inconsistent (no solution).

2. Step-by-Step Solution

Let the given system of equations be: (1) 7x+11y+αz=137x + 11y + \alpha z = 13 (2) 5x+4y+7z=β5x + 4y + 7z = \beta (3) 175x+194y+57z=361175x + 194y + 57z = 361

Step 1: Identify the Linear Relationship Between Equations For the system to have infinitely many solutions, the third equation must be a linear combination of the first two equations. This means there exist constants k1k_1 and k2k_2 such that: Equation (3)=k1×Equation (1)+k2×Equation (2)\text{Equation (3)} = k_1 \times \text{Equation (1)} + k_2 \times \text{Equation (2)} We find k1k_1 and k2k_2 by comparing the coefficients of xx and yy from the three equations.

Comparing coefficients of xx: 175=k17+k25(Equation A)175 = k_1 \cdot 7 + k_2 \cdot 5 \quad \text{(Equation A)} Comparing coefficients of yy: 194=k111+k24(Equation B)194 = k_1 \cdot 11 + k_2 \cdot 4 \quad \text{(Equation B)}

Now, we solve this system of two linear equations for k1k_1 and k2k_2: Multiply Equation A by 4: 4×(7k1+5k2)=4×175    28k1+20k2=700(Equation C)4 \times (7k_1 + 5k_2) = 4 \times 175 \implies 28k_1 + 20k_2 = 700 \quad \text{(Equation C)} Multiply Equation B by 5: 5×(11k1+4k2)=5×194    55k1+20k2=970(Equation D)5 \times (11k_1 + 4k_2) = 5 \times 194 \implies 55k_1 + 20k_2 = 970 \quad \text{(Equation D)} Subtract Equation C from Equation D: (55k1+20k2)(28k1+20k2)=970700(55k_1 + 20k_2) - (28k_1 + 20k_2) = 970 - 700 27k1=27027k_1 = 270 k1=27027    k1=10k_1 = \frac{270}{27} \implies k_1 = 10 Substitute k1=10k_1 = 10 back into Equation A: 7(10)+5k2=1757(10) + 5k_2 = 175 70+5k2=17570 + 5k_2 = 175 5k2=175705k_2 = 175 - 70 5k2=1055k_2 = 105 k2=1055    k2=21k_2 = \frac{105}{5} \implies k_2 = 21 Thus, we have found the linear relationship: Equation (3) is 10×Equation (1)+21×Equation (2)10 \times \text{Equation (1)} + 21 \times \text{Equation (2)}. This relationship must hold for all coefficients and the constant terms for infinitely many solutions to exist.

**Step 2: Calculate the value of α\alpha} Using the derived linear relationship 10×Equation (1)+21×Equation (2)=Equation (3)10 \times \text{Equation (1)} + 21 \times \text{Equation (2)} = \text{Equation (3)}, we compare the coefficients of zz: 10α+217=5710 \cdot \alpha + 21 \cdot 7 = 57 10α+147=5710\alpha + 147 = 57 10α=5714710\alpha = 57 - 147 10α=7010\alpha = -70 α=7\alpha = -7

**Step 3: Calculate the value of β\beta} Next, we use the same linear relationship for the constant terms: 10×13+21×β=36110 \times 13 + 21 \times \beta = 361 130+21β=361130 + 21\beta = 361 21β=36113021\beta = 361 - 130 21β=23121\beta = 231 β=23121\beta = \frac{231}{21} β=11\beta = 11

Step 4: Final Calculation We need to find the value of α+β+2\alpha + \beta + 2. Substitute the values we found for α\alpha and β\beta: α+β+2=(7)+(11)+2\alpha + \beta + 2 = (-7) + (11) + 2 α+β+2=4+2\alpha + \beta + 2 = 4 + 2 α+β+2=6\alpha + \beta + 2 = 6

3. Common Mistakes & Tips

  • Linear Dependence Check: Always verify the linear combination for all coefficients (x, y, z) and the constant term. If the relationship holds for the variable coefficients but not for the constant terms, the system is inconsistent (no solution), not infinitely many solutions.
  • Arithmetic Precision: Be meticulous with calculations, especially when solving systems of equations. A small error can lead to incorrect values for k1,k2,α,k_1, k_2, \alpha, or β\beta.
  • Determinant Method vs. Linear Combination: While Cramer's rule conditions (det(A)=0\det(A)=0 and Δx=Δy=Δz=0\Delta_x=\Delta_y=\Delta_z=0) are fundamental, identifying linear dependence through inspection or row operations is often more efficient for 3x3 systems, especially when coefficients are related.

4. Summary

For a system of linear equations to have infinitely many solutions, one equation must be a linear combination of the others, and this linear dependence must extend to the constant terms. By comparing the coefficients of xx and yy, we found that the third equation was 10×Equation (1)+21×Equation (2)10 \times \text{Equation (1)} + 21 \times \text{Equation (2)}. Applying this relationship to the zz-coefficients and constant terms, we determined α=7\alpha = -7 and β=11\beta = 11. Finally, calculating the expression α+β+2\alpha + \beta + 2 yields (7)+(11)+2=6(-7) + (11) + 2 = 6.

The final answer is 6\boxed{6}, which corresponds to option (A).

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