Analyzing the Setup
Welcome, student. Today, we are not just solving a matrix problem; we are uncovering a hidden symmetry. Many students look at a matrix equation like AB−1=A−1 and immediately reach for the inverse formula, ready to grind through rows and columns.
But stop. Take a breath. In JEE Advanced, the most elegant path is rarely the one that requires the most arithmetic. Let us walk through this together.
The Algebraic Anchor
We start with the equation AB−1=A−1. Our goal is to simplify this into something meaningful by isolating the relationship between A and B.
By pre-multiplying both sides by A, we get A(AB−1)=A(A−1). Since A(A−1)=I, the right side simplifies to the identity matrix I.
Now we have
A2B−1=I. To clear that
B−1, we post-multiply by
B. The result is a beautiful, clean anchor:
A2=B
The Transformation of C
Now, we turn our attention to the matrix C, defined by BCB−1=A. We need to understand C2 to solve the polynomial equation.
Let us isolate C. By pre-multiplying by B−1 and post-multiplying by B, we find C=B−1AB.
Now, let us square it:
C2=(B−1AB)(B−1AB)
Look closely at the center of this expression. We have B(B−1), which is just I. The expression collapses to B−1A2B.
And here is the magic—we already know that
A2=B! Substituting this in, we get:
C2=B−1BB=B
The complexity vanishes, leaving us with the simple truth that
C2=B.
The Cayley-Hamilton Revelation
We are left with the polynomial C4+αC2+βI=O. Since C2=B, then C4=B2.
Our equation becomes B2+αB+βI=O. This is the moment to invoke the Cayley-Hamilton Theorem.
This theorem is the bridge between the abstract matrix and its characteristic polynomial. For our matrix B=[1135], the characteristic equation is λ2−Tr(B)λ+∣B∣=0.
Calculating the trace,
Tr(B)=1+5=6, and the determinant,
∣B∣=(1)(5)−(3)(1)=2, we get:
λ2−6λ+2=0
By the Cayley-Hamilton theorem, it follows that:
B2−6B+2I=O
Final Calculation
Comparing B2+αB+βI=O with B2−6B+2I=O, we see that α=−6 and β=2.
The question asks for
2β−α. Substituting our values:
2(2)−(−6)=4+6=10
We did not just calculate; we navigated the structure of the matrices. The final answer is 10.