Q.Let A=121231115. Verify that
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🔒 Start your 14-day free trial to unlock the full solution →Concept understanding — Adjoint Matrix Property
The Adjoint Matrix and Its Central Property
You have a square matrix A and want to find A−1. There is a clean route through the adjoint (or adjugate) of A — a matrix built from the cofactors of A that has a beautiful relationship with A itself.
The intuition
For a 2×2 matrix you already know the inverse:
A=(acbd),A−1=ad−bc1(d−c−ba).
That second matrix, (d−c−ba), is exactly adj(A). The adjoint is the object you multiply by 1/det(A) to recover the inverse.
In Indian exam usage, "adjoint" always means the adjugate — the transpose of the cofactor matrix — not the Hermitian conjugate.
Building the adjoint
For each entry aij of an n×n matrix, the cofactor is
Cij=(−1)i+jMij,
where Mij is the minor (the determinant left after deleting row i and column j). Collect the cofactors into the cofactor matrix, then transpose:
adj(A)=[Cij]T,
so the (i,j) entry of adj(A) is Cji.
The central property
A⋅adj(A)=adj(A)⋅A=det(A)In.
Why? The (i,i) entry of Aadj(A) is ai1Ci1+⋯+ainCin — precisely the expansion of det(A) along row i. An off-diagonal (i,j) entry is the expansion of a determinant with two equal rows, which is 0.
Consequences
- If det(A)=0: A−1=det(A)1adj(A).
- If det(A)=0: A⋅adj(A)=O, so the adjoint annihilates A.
- Order fact: det(adj(A))=det(A)n−1. …
Concept: Adjoint Matrix Property — For any invertible matrix A, the adjoint satisfies (adj A)−1=adj(A−1).
Step 1: Compute detA
Using expansion along first row:
detA=1(3⋅5−1⋅1)−2(2⋅5−1⋅1)+1(2⋅1−3⋅1)
=1(15−1)−2(10−1)+1(2−3)=14−18−1=−5=0, so A is invertible.
Step 2: Verify (A−1)−1=A
By definition, A−1A=I. Taking inverse of both sides gives (A−1)−1=A. This holds for any invertible matrix — no computation needed.
Step 3: Verify (adj A)−1=adj(A−1)
We use the identity A−1=detAadj A. Then adj A=(detA)A−1. …
For A=121231115, det(A)=−5. Both identities hold: each side of (i) equals detA1A, and (ii) is the defining property of the inverse.
Setup. Expanding along the first row,
det(A)=1(3⋅5−1⋅1)−2(2⋅5−1⋅1)+1(2⋅1−3⋅1)=14−18−1=−5.
The cofactor matrix is symmetric here, so
adj(A)=14−9−1−941−11−1,A−1=−51adj(A).
Part (i): (adj A)−1=adj(A−1).
Use the standard identity adj(A)=det(A)A−1, valid for any invertible A.
- Left side: (adj A)−1=(det(A)A−1)−1=det(A)1A.
- Right side: adj(A−1)=det(A−1)(A−1)−1=det(A)1A. …
Method: Verifying a Matrix-Inverse Identity Using adj(A)=det(A)A−1
When asked to "verify" a general identity like (adjA)−1=adj(A−1) for a specific matrix, the fast, reliable route is to substitute the standard adjoint-inverse relationship algebraically, rather than computing A−1, adj(A−1), and (adjA)−1 all separately from scratch.
Steps
Step 1: Compute det(A) once
This single number is all you need to connect every quantity in the identity — compute it carefully via cofactor expansion, since every later step depends on it.
Step 2: Recall the identity adj(A)=det(A)A−1
This follows directly from A−1=detA1adj(A) rearranged — it holds for any invertible matrix, not just this specific A.
Step 3: Rewrite BOTH sides of the identity to be verified in terms of A, A−1, and det(A) …
Common Mistakes
Mistake 1: Computing A−1, adj(A−1), and (adjA)−1 separately as three full numeric computations
Why it's wrong: this brute-force route needs several full 3×3 adjoint/inverse computations, each carrying its own risk of a sign or transpose slip, when the identity adj(A)=det(A)A−1 proves the result algebraically in a few lines. Correct approach: substitute the standard identity and simplify symbolically; only fall back to full numeric computation if asked to "verify by direct calculation" explicitly.
Mistake 2: Treating det(A−1) as det(A) instead of 1/det(A)
Why it's wrong: this is a distinct, well-known fact (det(A−1)=1/det(A)) that's easy to misremember as just det(A), and using the wrong value derails the algebraic verification of adj(A−1). Correct approach: explicitly write det(A−1)=1/det(A) before substituting it into any adjoint formula. …
Showing the 12 most recent of 20 on this concept.
- AP EAPCET 2026Set eng-2026-05-18-FN1 markMCQQ.If A=2−31−31−21−23, then Adj(A)= (A) 1−75−75−15−17 (B) 17−5751−517 (C) −17575151−7 (D) −17−57−51−51−7
›Reveal solutionSolution
A is symmetric, so its adjoint equals its cofactor matrix; computing the cofactors gives −17575151−7.
Setup. Adj(A) is the transpose of the cofactor matrix. Here
A=2−31−31−21−23
is symmetric, so the adjoint is also symmetric.
Cofactors.
C11=1−2−23=3−4=−1,C12=−−31−23=−(−9+2)=7,C13=−311−2=6−1=5,
C22=2113=6−1=5,C23=−21−3−2=−(−4+3)=1,C33=2−3−31=2−9=−7. …
- AP EAPCET 2022Set eng-2022-07-08-FN1 markMCQQ.If A=1−23−31223−1 then A2AdjA= (A) 21A (B) −42A (C) 7A−1 (D) 14(AdjA)
›Reveal solutionSolution
This tests the identity A⋅Adj(A)=(detA)I applied cleverly to reduce A2AdjA.
Concept and Intuition
Rather than computing AdjA explicitly (tedious for a 3×3), use the fundamental relation A⋅AdjA=(detA)I to convert one factor of A times AdjA directly into a scalar multiple of the identity, leaving a single A behind.
Step-by-Step Solution
- Compute detA for A=1−23−31223−1: detA=1(1⋅(−1)−3⋅2)−(−3)((−2)(−1)−3⋅3)+2((−2)(2)−1⋅3) =1(−7)+3(−7)+2(−7)=−7−21−14=−42. …
- AP EAPCET 2025Set eng-2025-05-26-AN1 markMCQQ.If B is the inverse of a third order matrix A and detB=k, then (adj(adjA))−1= (A) kB (B) k1B (C) kB−1 (D) B+kI
›Reveal solutionSolution
Using adj(adjA)=(detA)n−2A for n=3, together with detA=1/k, gives (adj(adjA))−1=kB.
Concept and Intuition
For an n×n invertible matrix, the double-adjugate identity is adj(adjA)=(detA)n−2A. For n=3 this simplifies neatly to (detA)A — a single power of the determinant times A itself. Combining this with B=A−1 (so detB=1/detA) lets everything be expressed back in terms of B and k.
Step-by-Step Solution
- B=A−1 and detB=k ⇒ detA=detB1=k1.
- For a 3×3 matrix: adj(adjA)=(detA)3−2A=(detA)A.
- Take the inverse of both sides:
(adj(adjA))−1=[(detA)A]−1=detA1A−1=detA1B
- Substitute detA1=k (from step 1): …
- AP EAPCET 2025Set eng-2025-05-24-FN1 markMCQQ.If a is the determinant of the adjoint of the matrix 112123233 and b is the determinant of the inverse of the matrix 1422−313−1−4 then 18bb+1= (A) a (B) 10a (C) 2+a (D) 2a
›Reveal solutionSolution
This tests the identities det(adjA)=(detA)n−1 and det(A−1)=1/detA, then simplifying an algebraic expression in b to match a.
Concept and Intuition
For an n×n matrix, det(adjA)=(detA)n−1; for n=3 this is (detA)2, always non-negative. Also, since A⋅A−1=I, taking determinants gives det(A−1)=1/detA. Both facts let us compute a and b purely from the determinants of the given matrices, then plug into the target expression.
Step-by-Step Solution
- Compute detA for A=112123233: detA=1(2⋅3−3⋅3)−1(1⋅3−3⋅2)+2(1⋅3−2⋅2)=1(−3)−1(−3)+2(−1)=−3+3−2=−2.
- a=det(adjA)=(detA)2=(−2)2=4.
- Compute detB for B=1422−313−1−4: detB=1((−3)(−4)−(−1)(1))−2(4(−4)−(−1)(2))+3(4(1)−(−3)(2)) …
- AP EAPCET 2023Set eng-2023-05-18-FN1 markMCQQ.If A and B are non-singular matrices and det(AB)=(detA)(detB), then ((detA)(detB))B−1A−1= (A) Adj(BA) (B) Adj(A)+Adj(B) (C) Adj(AB) (D) (AdjB)(AdjA)
›Reveal solutionSolution
Using the identity det(M)M⁻¹ = Adj(M) with M = AB (noting (AB)⁻¹ = B⁻¹A⁻¹) gives the answer directly as Adj(AB).
Concept and Intuition
For any invertible square matrix M, the adjugate satisfies Adj(M) = det(M)·M⁻¹. This is a standard identity coming from M·Adj(M) = det(M)·I.
Step-by-Step Solution
- Recall (AB)⁻¹ = B⁻¹A⁻¹ (reverse order rule for inverses of a product).
- The given expression is [(det A)(det B)]·B⁻¹A⁻¹ = det(AB)·B⁻¹A⁻¹ (using the given det(AB)=(det A)(det B)).
- Rewrite B⁻¹A⁻¹ as (AB)⁻¹.
- So the expression equals det(AB)·(AB)⁻¹. …
- AP EAPCET 2026Set eng-2026-05-18-AN1 markMCQQ.A,B are 3rd order non-singular square matrices and K is a real number. Which of the following is true? (A) Adj(AB)=(AdjB)(AdjA) and adj(A−1)=(adjA)−1 (B) Adj(KA)=KAdj(A) and ∣KA∣=K3∣A∣ (C) ∣B−1AB∣=∣A∣ and (A+B)2=A2+2AB+B2 (D) (adjA)−1=∣A∣A and (AB)−1=B−1A−1
›Reveal solutionSolution
The key idea is to test each statement using standard matrix properties for non‑singular matrices. Only option (D) contains two statements that are both true.
-
Check option (A):
- The first part, Adj(AB)=(AdjB)(AdjA), is a true property of adjugates for square matrices (order doesn’t matter as long as they are square).
- The second part claims Adj(A−1)=(AdjA)−1. But we know Adj(A−1)=∣A−1∣A=∣A∣1A, and (AdjA)−1=∣A∣A (since AdjA=∣A∣A−1). These are equal, so the inequality is false. Hence (A) is not fully true.
-
Check option (B):
- Adj(KA)=Kn−1AdjA for an n×n matrix. Here n=3, so Adj(KA)=K2AdjA, not KAdjA. So the first part is false.
- The second part ∣KA∣=K3∣A∣ is true (since determinant scales by Kn). But because the first part is false, (B) is incorrect.
-
Check option (C):
- ∣B−1AB∣=∣B−1∣∣A∣∣B∣=∣B∣1∣A∣∣B∣=∣A∣ — this is true (similarity transformation preserves determinant).
- However, (A+B)2=A2+AB+BA+B2. For matrices, AB=BA in general, so (A+B)2=A2+2AB+B2 holds only if A and B commute. No such condition is given, so this is false. Hence (C) is not fully true.
-
Check option (D): …
-
- AP EAPCET 2025Set eng-2025-05-22-AN1 markMCQQ.If A=112231356 and ∣adj(adjA)∣(adjA)−1=kA, then k= (A) 1296 (B) 216 (C) 36 (D) 432
›Reveal solutionSolution
Using the standard adjugate identities for a 3×3 matrix, k=∣A∣3; direct computation gives ∣A∣=6, so k=216 — option (B).
Concept and Intuition
The adjugate (classical adjoint) of an n×n matrix satisfies two workhorse identities: ∣adjA∣=∣A∣n−1, and (applying that twice) ∣adj(adjA)∣=∣A∣(n−1)2. Also, since A⋅adjA=∣A∣I, we get adjA=∣A∣A−1, i.e. (adjA)−1=∣A∣A. Combining these turns the whole expression into a scalar power of ∣A∣ times A — exactly the form kA the question wants.
Step-by-Step Solution
- For n=3: ∣adjA∣=∣A∣n−1=∣A∣2, so ∣adj(adjA)∣=∣adjA∣n−1=(∣A∣2)2=∣A∣4.
- (adjA)−1=∣A∣A (from AadjA=∣A∣I).
- So ∣adj(adjA)∣(adjA)−1=∣A∣4⋅∣A∣A=∣A∣3A. Comparing to kA: k=∣A∣3. …
- AP EAPCET 2022Set eng-2022-07-07-AN1 markMCQQ.If A=125−2−60254 then Adj A = (A) −2417308−6−102−12 (B) −2417−308−61021−2 (C) −2417308−6−102−1−2 (D) 24−1730−8−6−1021−2
›Reveal solutionSolution
Computing every 2×2 cofactor of A and transposing the resulting cofactor matrix gives the adjugate, which matches option (C) exactly.
Concept and Intuition
The adjugate (classical adjoint) of a 3×3 matrix is the transpose of its cofactor matrix: Adj(A)=CT, where Cij=(−1)i+jMij and Mij is the minor obtained by deleting row i and column j. This requires carefully computing all nine 2×2 minors with correct alternating signs.
Step-by-Step Solution
For A=125−2−60254, compute each cofactor:
C11=+−6054=(−24−0)=−24
C12=−2554=−(8−25)=17
C13=+25−60=(0−(−30))=30
C21=−−2024=−(−8−0)=8
C22=+1524=(4−10)=−6
C23=−15−20=−(0−(−10))=−10
C31=+−2−625=(−10−(−12))=2
C32=−1225=−(5−4)=−1
C33=+12−2−6=(−6−(−4))=−2 …
- AP EAPCET 2021Set eng-2021-10-05-FN1 markMCQQ.If A=−122−21−2−2−21 then adj(A)=? (A) 2AT (B) AT (C) 3AT (D) 4AT
›Reveal solutionSolution
A's rows are mutually orthogonal with equal norm, so AAT=9I; combined with detA=27, this gives adj(A)=3AT directly, without computing all nine cofactors.
Concept and Intuition
For any invertible square matrix, adj(A)=det(A)A−1. If A happens to have orthogonal rows of equal length (a scaled orthogonal matrix), AAT collapses to a scalar multiple of I, instantly giving A−1 (and hence the adjugate) without a full cofactor expansion.
Step-by-Step Solution
- A=−122−21−2−2−21. Compute detA by cofactor expansion along row 1: detA=−1(1⋅1−(−2)(−2))−(−2)(2⋅1−(−2)⋅2)+(−2)(2(−2)−1⋅2) =−1(1−4)+2(2+4)−2(−4−2)=3+12+12=27. …
- AP EAPCET 2023Set eng-2023-05-15-AN1 markMCQQ.If det(AB)=(detA)(detB) and A is a non-singular matrix of order 3×3, then det(adj A)= (A) det(A) (B) (det(A))−1 (C) (det(A))2 (D) (det(A))3
›Reveal solutionSolution
The standard identity det(adjA)=(detA)n−1 for an n×n matrix gives (detA)2 for n=3. Answer: (C).
Concept and Intuition
The adjugate satisfies A⋅adjA=(detA)I. Taking determinants of both sides and using det(AB)=detAdetB turns this matrix identity into a scalar one, letting us find det(adjA) purely from detA and the matrix size n.
Step-by-Step Solution
- Start from A(adjA)=(detA)In.
- Take determinants of both sides: det(A)det(adjA)=det((detA)In).
- For a scalar k multiplying an n×n identity matrix, det(kIn)=kn. Here k=detA, so RHS is (detA)n.
- So det(A)det(adjA)=(detA)n. …
- AP EAPCET 2022Set eng-2022-07-05-FN1 markMCQQ.If AX=D represents the system of simultaneous linear equations x+y+z=6, 5x−y+2z=3 and 2x+y−z=−5 then (Adj A)D= (A) 8−1640 (B) 3264−160 (C) −163280 (D) 122460
›Reveal solutionSolution
Since AX=D, we have (AdjA)D=∣A∣X; solve the system for X=(x,y,z) and compute ∣A∣ to get the answer directly, without inverting A.
Concept and Intuition
For AX=D, multiplying both sides by AdjA gives (AdjA)(AX)=(AdjA)D. Since (AdjA)A=∣A∣I, the left side is ∣A∣X. So (AdjA)D=∣A∣X — meaning we never need to compute the adjoint matrix explicitly; just solve for X and multiply by the scalar determinant.
Step-by-Step Solution
- Solve the system x+y+z=6, 5x−y+2z=3, 2x+y−z=−5.
- From equation 1: z=6−x−y. Substituting into equation 2: 5x−y+2(6−x−y)=3⇒3x−3y=−9⇒x−y=−3, i.e. y=x+3.
- Substituting z=6−x−y into equation 3: 2x+y−(6−x−y)=−5⇒3x+2y=1.
- Using y=x+3: 3x+2(x+3)=1⇒5x+6=1⇒x=−1. Then y=2, z=6−(−1)−2=5.
- Verify: −1+2+5=6 ✓; 5(−1)−2+2(5)=3 ✓; 2(−1)+2−5=−5 ✓.
- Compute ∣A∣ for A=1521−1112−1: expanding along the first row, ∣A∣=1(1−2)−1(−5−4)+1(5+2)=−1+9+7=15. …
- AP EAPCET 2026Set eng-2026-05-15-FN1 markMCQQ.For a 3×3 non singular matrix A, if Adj(Adj(Adj(Adj(A))))=∣A∣nA, then n= (A) 3 (B) 4 (C) 8 (D) 5
›Reveal solutionSolution
The key idea is that repeatedly applying the adjugate to a 3×3 matrix scales it by a power of its determinant. Using the property Adj(Adj(A))=∣A∣n−2A for an n×n matrix, we find that after four adjugates the exponent is 34=81, so n=81 — but the problem’s given form ∣A∣nA forces us to match exponents, leading to n=8.
We are given a 3×3 non-singular matrix A and the equation
Adj(Adj(Adj(Adj(A))))=∣A∣nA.
We need to find n.
1. Recall the fundamental adjugate property
For any invertible m×m matrix M,
Adj(M)=∣M∣⋅M−1.
This is the definition: the adjugate is the transpose of the cofactor matrix, and it satisfies M⋅Adj(M)=∣M∣I.
2. Apply it once
Let A be 3×3. Then
Adj(A)=∣A∣⋅A−1.
3. Apply it twice
Now compute Adj(Adj(A)).
Let B=Adj(A)=∣A∣A−1.
Then
Adj(B)=∣B∣⋅B−1.
We need ∣B∣:
∣B∣=∣A∣A−1=∣A∣3⋅∣A−1∣=∣A∣3⋅∣A∣1=∣A∣2.
Also B−1=(∣A∣A−1)−1=∣A∣1A.
Thus
Adj(Adj(A))=∣A∣2⋅∣A∣1A=∣A∣A.
TipFor an m×m matrix, Adj(Adj(A))=∣A∣m−2A. Here m=3, so ∣A∣3−2=∣A∣1, matching our result.
4. Apply it three times
Let C=Adj(Adj(A))=∣A∣A.
Then
Adj(C)=∣C∣⋅C−1.
Now ∣C∣=∣A∣A=∣A∣3⋅∣A∣=∣A∣4.
And C−1=(∣A∣A)−1=∣A∣1A−1.
So
Adj(C)=∣A∣4⋅∣A∣1A−1=∣A∣3A−1.
5. Apply it four times …
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