Animated Solution for Mathematics - Matrices and Determinants: Let x,y,z>1 and A=1logyxlogzxlogxy2logzylogxzlogyz3. Then ∣adj(adjA2)∣ is equal to
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Visualized Solution
Introduction to Matrix A
Given matrix A=1logyxlogzxlogxy2logzylogxzlogyz3
We need to find ∣adj(adjA2)∣
Change of Base Property
Using the property: logab=lnalnb
Rewrite each logarithmic element in the determinant ∣A∣
Factor out lnx from C1, lny from C2, and lnz from C3
The logarithmic terms cancel out: ∣A∣=111121113
Evaluating the Determinant
Expand along R1: ∣A∣=1(2×3−1×1)−1(1×3−1×1)+1(1×1−1×2)
∣A∣=1(5)−1(2)+1(−1)=5−2−1=2
Finding ∣A2∣
Using the property: ∣Mk∣=∣M∣k
∣A2∣=∣A∣2=22=4
The Double Adjoint Property
Property: ∣adj(adjM)∣=∣M∣(n−1)2 for an n×n matrix
Here M=A2 and n=3
Applying the Property
∣adj(adjA2)∣=∣A2∣(3−1)2
Substitute ∣A2∣=4 and simplify the exponent: ∣A2∣4=44
Final Computation
44=(22)4=22×4=28
28=256
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The Sigma Insight: Adjoint and Inverse of a Matrix
Analyzing the Setup
Welcome, future engineers. Today, we are going to dismantle a problem that, at first glance, looks like a nightmare of logarithms and matrices. You see a matrix A filled with terms like logxy and logzx, and your instinct might be to panic.
But I want you to take a deep breath. In the world of JEE Advanced, complexity is often just a mask for hidden simplicity. Our job is to peel back that mask.
Phase 1
The Change of Base
Look at the matrix:
A=1logyxlogzxlogxy2logzylogxzlogyz3
The bases are all over the place: x,y,z. This is the primary source of our confusion. We cannot operate on a matrix where the language of the elements is inconsistent.
We need a common tongue. That language is the natural logarithm. Using the change of base property, logab=lnalnb, we can rewrite every single element.
Suddenly, the matrix transforms into a beautiful, structured array of ratios:
Now, look at the rows. The first row is dominated by lnx1, the second by lny1, and the third by lnz1. This is not a coincidence; it is a design.
Let us factor these out. When we pull lnx1 from R1, lny1 from R2, and lnz1 from R3, we are left with a matrix where the numerators are lnx,lny,lnz.
But wait—the columns also have these terms! If we factor lnx from C1, lny from C2, and lnz from C3, the denominators and numerators cancel out perfectly. The logarithms vanish entirely.
We are left with the simple, elegant integer matrix:
∣A∣=111121113
Phase 3
The Determinant Reveal
Evaluating this is a breath of fresh air. Expanding along the first row, we get:
∣A∣=1(2×3−1×1)−1(1×3−1×1)+1(1×1−1×2)
This simplifies to:
∣A∣=1(5)−1(2)+1(−1)=5−2−1=2
The determinant of A is 2. This is the moment where the hard work pays off. We have tamed the beast.
Phase 4
The Adjoint Power Play
We are asked for ∣adj(adjA2)∣. First, we handle the square. Using the property ∣Mk∣=∣M∣k, we find:
∣A2∣=∣A∣2=22=4
Now, we apply the property of the double adjoint: ∣adj(adjM)∣=∣M∣(n−1)2. With n=3, the exponent becomes (3−1)2=4.
Thus, we need to calculate 44:
44=(22)4=28=256
We have arrived at the destination. The complexity was an illusion, and through systematic application of properties, we found the truth. The final answer is 256.