Matrices add, subtract, multiply and scale much like numbers (except AB=BA in general), so we can substitute a matrix into a polynomial. For p(x)=x2−3x+2, replacing x by a square matrix A gives
p(A)=A2−3A+2I,
where the constant 2 becomes 2I so it can be added to matrices.
The Cayley–Hamilton theorem makes a striking claim: every square matrix satisfies its own characteristic equation.
The characteristic polynomial
Every n×n matrix A has a characteristic polynomial
p(λ)=det(λI−A),
a degree-n polynomial whose roots are the eigenvalues. For a 2×2 matrix it is λ2−(trA)λ+detA. For A=(1324) this is p(λ)=λ2−5λ−2.
The statement
Important
If p(λ)=λn+cn−1λn−1+⋯+c1λ+c0 is the characteristic polynomial of A, then
p(A)=An+cn−1An−1+⋯+c1A+c0I=0,
the n×n zero matrix.
For the example, A2−5A−2I=(0000).
Why it is surprising, and a quick check
The polynomial is built from det(λI−A), yet feeding A back into it annihilates it — and this holds for any A, invertible or not. You can verify it on the general 2×2 matrix A=(acbd), where p(λ)=λ2−(a+d)λ+(ad−bc): a short computation of A2−(a+d)A+(ad−bc)I gives the zero matrix.
Why it matters
Cayley–Hamilton lets you rewrite any high power Ak (for k≥n) as a combination of I,A,…,An−1, which speeds up computing powers, exponentials and inverses. …
Using the Cayley-Hamilton theorem, we find the characteristic equation of A and use it to express A−1 as a polynomial in A. The inverse is A−1=21(A2−3I).
The problem asks us to find A−1 and then verify a given expression. The direct approach — computing the inverse via cofactors or row reduction — would work, but the problem is clearly designed to illustrate a deeper idea: the Cayley-Hamilton theorem. This theorem says that every square matrix satisfies its own characteristic equation. That means we can replace the matrix A in its characteristic polynomial and get the zero matrix. Once we have that polynomial, we can rearrange it to solve for A−1 as a polynomial in A — no messy fractions or cofactor expansions needed.
Let’s walk through it.
1. Find the characteristic polynomial of A.
The characteristic polynomial is p(λ)=det(A−λI). For
A=011101110,
we have
A−λI=−λ111−λ111−λ.
Compute the determinant. A neat trick: add all rows to the first row, or notice the pattern. Let’s do it systematically:
The theorem states that A satisfies its own characteristic equation:
A3−3A−2I=0.
So
A3−3A=2I.
We want A−1. Multiply both sides of A3−3A=2I by A−1 (which exists because detA=0 — we’ll check later). That gives:
A2−3I=2A−1.
Therefore
A−1=21(A2−3I).
That’s exactly the expression we needed to show. So the second part is done — it follows directly from Cayley-Hamilton.
Tip
You don’t need to compute A−1 by row reduction at all if you only need to verify the given formula. But the problem also asks to findA−1, so we should compute A2 and then plug in.
Method: Finding a Matrix Inverse via the Adjoint (and Verifying a Given Identity Directly)
Use this method whenever you're asked to find A−1 for a 3×3 matrix and then confirm it matches some other expression built from A (such as 21(A2−3I)). The CBSE Class 12 syllabus route is the adjoint method — not the Cayley–Hamilton theorem, which is a useful shortcut but sits outside the core syllabus (it's a JEE-Advanced-level extension topic).
Steps
Step 1: Confirm A is invertible
Compute ∣A∣ by cofactor expansion along any row or column. If ∣A∣=0, the inverse exists and can be found.
Step 2: Build the cofactor matrix, then the adjoint
For each entry aij, compute the cofactor Cij=(−1)i+jMij, where Mij is the determinant left after deleting row i and column j. Collect all nine cofactors into the cofactor matrix, then transpose it to get the adjoint:
adj(A)=(Cij)T.
Step 3: Assemble the inverse
A−1=∣A∣1adj(A).
Step 4 (Applying to this problem): Verify a claimed identity by direct computation, not by invoking a shortcut theorem …
Why it's wrong: with a matrix full of 0s, 1s and −λs, it's easy to drop a minus sign in one of the three 2×2 cofactors, producing a wrong characteristic polynomial (e.g. −λ3−3λ+2 instead of −λ3+3λ+2) — which then gives a completely wrong Cayley–Hamilton relation and a wrong A−1.
Mistake 2: Multiplying the Cayley–Hamilton equation by A−1 without checking invertibility first …