Animated Solution for Mathematics - Matrices and Determinants: The set of all values of λ for which the system of linear equations x−2y−2z=λx, x+2y+z=λy, −x−y=λz has a non-trivial solution.
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Visualized Solution
System of Equations
Given system of equations:
x−2y−2z=λx
x+2y+z=λy
−x−y=λz
Homogeneous Form AX=0
Rearranging terms to the left side:
(1−λ)x−2y−2z=0
x+(2−λ)y+z=0
−x−y−λz=0
Condition ∣A∣=0
For a non-trivial solution of AX=0, the determinant of the coefficient matrix must be zero.
Condition: ∣A∣=0
Setting up Determinant D=0
The determinant D is given by:
D=1−λ1−1−22−λ−1−21−λ=0
Expanding D along R1
Expanding along R1:
(1−λ)[(2−λ)(−λ)−(−1)(1)]
+2[(1)(−λ)−(−1)(1)]
−2[(1)(−1)−(−1)(2−λ)]=0
Simplifying First Term
Simplifying the first part:
(1−λ)[λ2−2λ+1]
=(1−λ)(λ−1)2
Simplifying Remaining Terms
Simplifying the second and third parts:
+2(−λ+1)−2(−1+2−λ)
=2(1−λ)−2(1−λ)=0
Combining and Solving
Combining the simplified terms:
(1−λ)(λ−1)2=0
−(λ−1)(λ−1)2=0
−(λ−1)3=0
Final Result
Solving for λ:
λ=1
The set of values is {1}, which is a singleton set.
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The Sigma Insight: Solution of System of Linear Equations (Matrix Method and Cramer's Rule)
The Elegance of Linear Systems
Welcome, fellow traveler on the path to JEE mastery! Today, we are diving into the heart of linear algebra. We are presented with a system of equations that, at first glance, looks like a tangled mess of variables and parameters.
But remember, in mathematics, complexity is often just a mask for underlying symmetry. Let us peel back that mask together.
Phase 1
The Homogeneous Transformation
We start with the system:
x−2y−2z=λx
x+2y+z=λy
−x−y=λz
Our first instinct might be to panic at the sight of λ scattered across the right-hand side. But take a breath. We need to bring order to this chaos.
By subtracting the λ terms from both sides, we group the variables into a beautiful, homogeneous structure:
(1−λ)x−2y−2z=0
x+(2−λ)y+z=0
−x−y−λz=0
Now, we have the classic form AX=0. This is the language of linear transformations.
We are asking: for what values of λ does this transformation collapse the space such that a non-zero vector X is mapped to the origin? This happens if and only if the matrix A is not invertible, which is equivalent to saying its determinant is zero: det(A)=0.
Phase 2
The Determinant's Power
Let us construct our matrix A and set its determinant to zero:
D=1−λ1−1−22−λ−1−21−λ=0
This determinant represents the volume of the parallelepiped formed by the column vectors of A. If this volume is zero, the vectors are linearly dependent, and the system has non-trivial solutions.
Now, let us simplify this step-by-step. It looks intimidating, but watch how the terms dance together.
First term: (1−λ)[−λ2+2λ+1]. Inside the bracket: (2−λ)(−λ)=−2λ+λ2. So, λ2−2λ+1, which is (λ−1)2. Thus, the first term is (1−λ)(λ−1)2.
Second term: 2(−λ+1)=2(1−λ).
Third term: −2(−1+2−λ)=−2(1−λ).
Look at that! The second and third terms are 2(1−λ) and −2(1−λ). They vanish into thin air!
We are left with:
(1−λ)(λ−1)2=0
Since (1−λ)=−(λ−1), this becomes:
−(λ−1)(λ−1)2=−(λ−1)3=0
Conclusion
The Singleton Set
Solving −(λ−1)3=0 gives us exactly one solution: λ=1. The set of all values of λ is simply {1}.
Because this set contains only one element, it is, by definition, a singleton set.
Isn't it beautiful? We started with a system that seemed to have many moving parts, and through the rigorous application of linear algebra, we found that only one specific value of λ allows for a non-trivial solution. Keep this mindset—look for the structure, trust the process, and the math will always reveal its secrets.