Animated Solution for Mathematics - Matrices and Determinants: Let A=[21−11]. If the sum of the diagonal elements of A13 is 3n, then n is equal to_________
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Visualized Solution
Understanding the Goal
Given matrix A=[21−11]
Goal: Find n such that tr(A13)=3n
Recall: tr(M) is the sum of diagonal elements of matrix M
The Characteristic Equation
Characteristic Equation: ∣A−λI∣=0
For a 2×2 matrix: λ2−tr(A)λ+det(A)=0
Forming the Quadratic
tr(A)=2+1=3
det(A)=(2)(1)−(−1)(1)=3
Substitute values: λ2−3λ+3=0
Solving for Eigenvalues
Using quadratic formula: λ=2(1)−(−3)±(−3)2−4(1)(3)
λ=23±9−12=23±i3
Conversion to Euler's Form
Modulus r=(23)2+(23)2=49+43=3
Argument θ=tan−1(33)=6π
Eigenvalues: λ=3e±i6π
Property of Trace and Powers
Property: If λ1,λ2 are eigenvalues of A, then λ1k,λ2k are eigenvalues of Ak
tr(A13)=λ113+λ213
Setting up the Sum
tr(A13)=(3ei6π)13+(3e−i6π)13
Factor out (3)13: (3)13[ei613π+e−i613π]
Simplifying the Power of 3
(3)13=(321)13=3213=36⋅3
Using eiθ+e−iθ=2cosθ
Evaluating the Cosine Term
tr(A13)=363[2cos(613π)]
cos(613π)=cos(2π+6π)=cos(6π)
cos(6π)=23
Final Calculation
tr(A13)=363⋅(2⋅23)
tr(A13)=363⋅3
tr(A13)=36⋅3=37
Finding the Value of n
Given: tr(A13)=3n
From calculation: tr(A13)=37
Comparing exponents: n=7
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The Sigma Insight: Algebraic Operations on Matrices
Solution Diagram
Analyzing the Setup
Imagine you are sitting in the examination hall. You see the matrix
A=[21−11]
and the question asks for the sum of the diagonal elements of A13.
Your first instinct might be to reach for your pen and start multiplying. A2, then A3, then A4... stop! If you do that, you have fallen into the trap.
The JEE Advanced examiners are not testing your ability to perform tedious arithmetic; they are testing your ability to see the soul of the matrix. Let us embark on a journey to solve this not with brute force, but with the elegance of linear algebra.
The Key to the Kingdom
The Characteristic Equation
The secret to understanding any matrix lies in its eigenvalues. These are the scalars that define how the matrix stretches space.
For any 2×2 matrix, we do not need to perform complex row reductions. We have a beautiful shortcut: the characteristic equation
λ2−tr(A)λ+det(A)=0
Let us calculate the trace and determinant of our matrix A. The trace, tr(A), is the sum of the diagonal elements: 2+1=3. The determinant, det(A), is (2)(1)−(−1)(1)=3.
Substituting these into our equation, we get
λ2−3λ+3=0
This quadratic equation is the key that unlocks the entire problem.
The Complex Dance
Solving for λ, we use the quadratic formula:
λ=23±9−12=23±i3
We have arrived at two complex conjugate eigenvalues. Do not be intimidated by the i. In the world of matrices, complex eigenvalues often appear when the transformation involves a rotation.
To handle these, we must step out of the Cartesian plane and into the world of Euler. We convert these eigenvalues into polar form: λ=re±iθ.
The modulus r is
r=(23)2+(23)2=49+43=3
The argument θ is
θ=tan−1(3/23/2)=tan−1(31)=6π
Thus, our eigenvalues are 3e±i6π.
The Power of Euler
Now, we invoke the Spectral Mapping Theorem. We know that the trace of A13 is simply the sum of the 13th powers of the eigenvalues:
tr(A13)=λ113+λ213
Substituting our polar forms, we get
(3ei6π)13+(3e−i6π)13
Factoring out (3)13, we are left with
(3)13[ei613π+e−i613π]
This is where the magic happens. We know that eiθ+e−iθ=2cos(θ). Our expression becomes
(3)13⋅2cos(613π)
The Grand Finale
Let us simplify the terms. (3)13 is 36.5, which is 36⋅3.
The cosine term, cos(613π), is equivalent to cos(2π+6π), which is simply cos(6π)=23.
Putting it all together:
tr(A13)=(36⋅3)⋅(2⋅23)
The 2s cancel, and 3⋅3 becomes 3. We are left with 36⋅3=37.
The problem asks for n where the trace is 3n. By comparing our result, we see clearly that n=7.
We did not multiply the matrix once. We used the power of eigenvalues, the beauty of Euler's formula, and the symmetry of complex conjugates to solve a problem that would have taken others twenty minutes of painful arithmetic. This is the JEE Advanced mindset: think first, calculate later.