Q.12−2−130251 Verify A(adj A)=(adj A)A=∣A∣I in Exercises 3 and 4
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.
The adjoint is the transpose of the cofactor matrix, not the cofactor matrix itself. Forgetting the transpose (which swaps the off-diagonal cofactors) is the most common slip.
For A=(1324), the cofactors give adj(A)=(4−3−21), and indeed Aadj(A)=(−200−2)=(−2)I2=det(A)I2.
The Adjoint Matrix Property connecting A · adj(A) to det(A)·I is central to the CBSE Class 12 Determinants chapter, where it forms the standard route to computing a matrix inverse using the adjoint method — a topic frequently listed under "adjoint and inverse of a matrix important questions" for board exams. This identity also underpins the matrix method for solving simultaneous linear equations, tested in both CBSE boards and JEE Main.
Concept: Adjoint Matrix Property — For any square matrix A, A(adj A)=(adj A)A=∣A∣I.
Step 1: Compute ∣A∣
Expanding along R1:
∣A∣=1(3⋅1−5⋅0)−(−1)(2⋅1−5⋅(−2))+2(2⋅0−3⋅(−2))
=1(3)+1(2+10)+2(0+6)=3+12+12=27.
Step 2: Find adj A
Cofactors:
C11=3, C12=−12, C13=6
C21=1, C22=5, C23=2
C31=−11, C32=−1, C33=5
So adj A=3−126152−11−15.
Step 3: Verify A(adj A)
A(adj A)=12−2−1302513−126152−11−15
=270002700027=27I.
Similarly, (adj A)A gives the same result.
The property is verified: A(adj A)=(adj A)A=27I=∣A∣I.
For any square matrix A, the product A(adj A) equals (adj A)A=∣A∣I. Here we verify this identity for the given 3×3 matrix by computing its determinant and adjoint, then checking both products.
The property A(adj A)=(adj A)A=∣A∣I is one of the most elegant results in matrix algebra. It tells us that the adjoint (or adjugate) of a matrix is essentially a "scaled inverse" — when A is invertible, dividing the adjoint by the determinant gives the inverse. But the identity holds for any square matrix, invertible or not.
Why does this work? Each entry of adj A is a cofactor (signed minor) of A. When you multiply A by adj A, the (i,j) entry becomes the sum of products of row i of A with column j of cofactors. For i=j, this sum is exactly the Laplace expansion of ∣A∣ along row i. For i=j, it's like expanding a matrix with two identical rows — which gives zero. So the product is diagonal, with ∣A∣ on every diagonal entry.
Let's verify this concretely.
For a 3×3 matrix A=[aij], the adjoint is the transpose of the cofactor matrix: (adj A)ij=Cji, where Cij=(−1)i+jMij and Mij is the minor (determinant after deleting row i, column j).
Step 1: Compute the determinant ∣A∣.
We have
A=12−2−130251.
Expand along the third row (it has a zero, which saves work):
∣A∣=(−2)⋅(−1)3+1−1325+0⋅(…)+1⋅(−1)3+312−13.
The first term: (−2)⋅(+1)⋅[(−1)(5)−(2)(3)]=(−2)[−5−6]=(−2)(−11)=22.
The third term: 1⋅(+1)⋅[(1)(3)−(−1)(2)]=3+2=5.
So ∣A∣=22+5=27.
Always double-check the sign pattern: (−1)i+j is + when i+j is even, − when odd. Row 3, column 1: 3+1=4 (even) → + sign. Row 3, column 3: 3+3=6 (even) → + sign.
Step 2: Find all cofactors Cij.
We need nine cofactors. Let's compute them systematically.
- C11=(−1)1+13051=(3⋅1−5⋅0)=3.
- C12=(−1)1+22−251=−[2⋅1−5⋅(−2)]=−[2+10]=−12.
- C13=(−1)1+32−230=(2⋅0−3⋅(−2))=0+6=6.
- C21=(−1)2+1−1021=−[(−1)⋅1−2⋅0]=−[−1−0]=1.
- C22=(−1)2+21−221=(1⋅1−2⋅(−2))=1+4=5.
- C23=(−1)2+31−2−10=−[1⋅0−(−1)⋅(−2)]=−[0−2]=2.
- C31=(−1)3+1−1325=[(−1)⋅5−2⋅3]=−5−6=−11.
- C32=(−1)3+21225=−[1⋅5−2⋅2]=−[5−4]=−1.
- C33=(−1)3+312−13=(1⋅3−(−1)⋅2)=3+2=5.
A common mistake: forgetting the (−1)i+j sign. For C12, the minor is 2⋅1−5⋅(−2)=12, but the sign is negative because 1+2=3 is odd. So C12=−12, not 12.
Step 3: Write the adjoint matrix.
The adjoint is the transpose of the cofactor matrix:
adj A=C11C12C13C21C22C23C31C32C33=3−126152−11−15.
Step 4: Compute A(adj A).
Multiply A (on the left) by adj A (on the right). Let's do it entry by entry.
Row 1 of A: [1,−1,2].
- (1,1) entry: 1⋅3+(−1)⋅(−12)+2⋅6=3+12+12=27.
- (1,2) entry: 1⋅1+(−1)⋅5+2⋅2=1−5+4=0.
- (1,3) entry: 1⋅(−11)+(−1)⋅(−1)+2⋅5=−11+1+10=0.
Row 2 of A: [2,3,5].
- (2,1) entry: 2⋅3+3⋅(−12)+5⋅6=6−36+30=0.
- (2,2) entry: 2⋅1+3⋅5+5⋅2=2+15+10=27.
- (2,3) entry: 2⋅(−11)+3⋅(−1)+5⋅5=−22−3+25=0.
Row 3 of A: [−2,0,1].
- (3,1) entry: (−2)⋅3+0⋅(−12)+1⋅6=−6+0+6=0.
- (3,2) entry: (−2)⋅1+0⋅5+1⋅2=−2+0+2=0.
- (3,3) entry: (−2)⋅(−11)+0⋅(−1)+1⋅5=22+0+5=27.
So
A(adj A)=270002700027=27⋅I=∣A∣I.
Step 5: Compute (adj A)A.
Now multiply adj A (on the left) by A (on the right).
Row 1 of adj A: [3,1,−11].
- (1,1) entry: 3⋅1+1⋅2+(−11)⋅(−2)=3+2+22=27.
- (1,2) entry: 3⋅(−1)+1⋅3+(−11)⋅0=−3+3+0=0.
- (1,3) entry: 3⋅2+1⋅5+(−11)⋅1=6+5−11=0.
Row 2 of adj A: [−12,5,−1].
- (2,1) entry: (−12)⋅1+5⋅2+(−1)⋅(−2)=−12+10+2=0.
- (2,2) entry: (−12)⋅(−1)+5⋅3+(−1)⋅0=12+15+0=27.
- (2,3) entry: (−12)⋅2+5⋅5+(−1)⋅1=−24+25−1=0.
Row 3 of adj A: [6,2,5].
- (3,1) entry: 6⋅1+2⋅2+5⋅(−2)=6+4−10=0.
- (3,2) entry: 6⋅(−1)+2⋅3+5⋅0=−6+6+0=0.
- (3,3) entry: 6⋅2+2⋅5+5⋅1=12+10+5=27.
Thus
(adj A)A=270002700027=27⋅I=∣A∣I.
Both products give the same diagonal matrix, confirming the identity.
Notice that the off-diagonal entries all turned out to be zero. This is not a coincidence — it's the "two identical rows" phenomenon. For example, the (1,2) entry of A(adj A) is the expansion of a matrix where row 1 of A replaces row 2, giving two identical rows and hence determinant zero.
We have verified that A(adj A)=(adj A)A=27I=∣A∣I, confirming the identity.
Method: Verifying A(adjA)=(adjA)A=∣A∣I
The standard procedure for any "verify the adjoint identity" question.
Steps
Step 1: Compute ∣A∣
Expand along whichever row or column has the most zeros (or the first row if none do).
Step 2: Compute all nine cofactors Cij=(−1)i+jMij
Work systematically through every entry, deleting its row and column to form the 2×2 minor, then applying the correct sign.
Step 3: Assemble the adjoint as the TRANSPOSE of the cofactor matrix
adj(A)=C11C12C13C21C22C23C31C32C33.
Don't skip the transpose — the adjoint is not simply the cofactor matrix itself.
Step 4: Multiply A⋅adj(A) entry by entry
Every diagonal entry of the product should come out equal to ∣A∣ (it is the row-expansion of ∣A∣ along that row); every off-diagonal entry should come out 0 (it is the expansion of a determinant with a repeated row).
Step 5: Repeat for (adjA)⋅A and confirm both equal ∣A∣I
The product in the reverse order gives the identical diagonal matrix, confirming the identity.
Common Mistakes
Mistake 1: Forgetting the (−1)i+j sign when computing a cofactor
Why it's wrong: for example C12's minor evaluates to 12, but the correct sign for position (1,2) is negative (since 1+2=3 is odd) — skipping the sign gives C12=12 instead of the correct −12, which then corrupts every product using it. Correct approach: write out (−1)i+j explicitly for every one of the nine cofactors before substituting the minor.
Mistake 2: Writing the adjoint as the cofactor matrix itself, without transposing
Why it's wrong: the adjoint is defined as the transpose of the cofactor matrix — using the untransposed cofactor matrix directly gives A(adjA) a non-diagonal result instead of ∣A∣I, since the off-diagonal entries won't cancel correctly. Correct approach: always swap rows and columns of the cofactor matrix (i.e. (adjA)ij=Cji) before multiplying by A.
Showing the 12 most recent of 31 on this concept.
- CBSE 2025Set 65/1/11 markMCQQ.If A is a square matrix of order 2 such that det(A)=4, then det(4 adj A) is equal to : (A) 16 (B) 64 (C) 256 (D) 512
›Reveal solutionSolution
The key idea is to use the property det(adj A)=(detA)n−1 for an n×n matrix, then combine with the scalar multiplication rule det(kB)=kndetB. For a 2×2 matrix with detA=4, we get det(4 adj A)=42⋅42−1=16⋅4=64. The answer is (B).
The problem asks for det(4 adj A) given that A is a 2×2 matrix with detA=4. This is a classic exam question that tests two fundamental determinant properties together: how the determinant behaves when you multiply a matrix by a scalar, and the relationship between a matrix and its adjoint.
Let’s unpack the intuition first. The adjoint (or adjugate) of a matrix is the transpose of its cofactor matrix. For a 2×2 matrix, the adjoint has a simple form: if A=(acbd), then adj A=(d−c−ba). Notice that det(adj A)=ad−bc=detA. That’s not a coincidence — it’s a special case of a general rule.
For any n×n matrix A, det(adj A)=(detA)n−1.
For n=2, this gives det(adj A)=(detA)1=detA. So here, det(adj A)=4.
Now we need det(4 adj A). The scalar multiplication rule says: if you multiply an n×n matrix by a scalar k, the determinant gets multiplied by kn. Why? Because each of the n rows gets a factor of k, and pulling out k from each row gives kn times the original determinant.
Watch outA common mistake is to forget the exponent n and write det(kB)=kdetB. That’s only true for a 1×1 matrix. For a 2×2 matrix, it’s k2.
So here n=2 and k=4, so det(4 adj A)=42⋅det(adj A)=16⋅4=64.
Let’s walk through it step by step.
-
Identify the order. A is 2×2, so n=2. This matters for both the adjoint property and the scalar multiplication rule.
-
Find det(adj A). Using the formula det(adj A)=(detA)n−1, we get (detA)1=4. So det(adj A)=4.
-
Apply the scalar multiplication rule. We have B=adj A, and we want det(4B). For a 2×2 matrix, det(4B)=42detB=16detB.
-
Combine the results. det(4 adj A)=16×4=64.
TipYou can also verify with a concrete example. Take A=(2002) (so detA=4). Then adj A=(2002), so 4 adj A=(8008), whose determinant is 8×8=64. This confirms the result.
✓Final answerThe value is 64, which corresponds to option (B).
-
- CBSE 2023Set 65/1/11 markMCQQ.Let A be a 3×3 matrix such that ∣adj A∣=64. Then ∣A∣ is equal to : (A) Only 8 (B) Only −8 (C) 64 (D) 8 or −8
›Reveal solutionSolution
For a 3×3 matrix, the determinant of its adjugate is ∣adj A∣=∣A∣n−1=∣A∣2. Given ∣A∣2=64, the possible values are ∣A∣=8 or ∣A∣=−8, so the correct option is (D).
The key here is the adjugate matrix property — a beautiful and often-tested result in linear algebra. For any square matrix A of order n, the adjugate (or classical adjoint) satisfies:
A⋅(adj A)=(adj A)⋅A=∣A∣In
Taking determinants on both sides gives:
∣A∣⋅∣adj A∣=∣A∣n
which simplifies (for ∣A∣=0) to:
∣adj A∣=∣A∣n−1
This formula holds even when ∣A∣=0 (both sides are zero), so it’s universally true.
Now, let’s apply it step by step.
- Identify the order of the matrix. Here A is 3×3, so n=3. Therefore n−1=2, and the formula becomes:
∣adj A∣=∣A∣2
- Plug in the given value. We are told ∣adj A∣=64. So:
∣A∣2=64
- Solve for ∣A∣. Taking square roots:
∣A∣=±8
Both 8 and −8 satisfy the equation, because squaring eliminates the sign.
Watch outA common mistake is to forget that ∣A∣ can be negative. Determinants are real numbers — they can be positive, negative, or zero. The square root of 64 gives two possibilities, not just the positive one.
- Check if both are valid. The adjugate formula ∣adj A∣=∣A∣n−1 works for any ∣A∣, positive or negative. So both 8 and −8 are possible values of ∣A∣ for some 3×3 matrix A with ∣adj A∣=64.
TipFor a 2×2 matrix, ∣adj A∣=∣A∣ (since n−1=1). For a 3×3, it’s ∣A∣2. For a 4×4, it’s ∣A∣3, and so on. The exponent is always one less than the order.
✓Final answerThe value of ∣A∣ is 8 or −8, so the correct option is (D).
- CBSE 2026Set 65/3/11 markMCQQ.If B(adj B)=310003100031, then the value of det(B−1) is: (A) 31 (B) 91 (C) 3 (D) 9
›Reveal solutionSolution
By recognizing the given matrix product B(adj B) as (detB)I, we find detB=31. Then, using the property det(B−1)=detB1, we calculate det(B−1)=3.
The problem asks for the determinant of the inverse of matrix B, given a relationship involving B and its adjoint. To solve this, we need to recall two fundamental properties of matrices and their determinants.
The first key idea is the relationship between a square matrix A, its adjoint adj A, and its determinant detA. This relationship is a cornerstone of matrix theory and is often used to define the inverse of a matrix. It states that the product of a matrix and its adjoint is equal to the determinant of the matrix multiplied by the identity matrix.
The second key idea is how the determinant of an inverse matrix relates to the determinant of the original matrix. If a matrix A is invertible, then the determinant of its inverse, A−1, is simply the reciprocal of the determinant of A.
Let's apply these concepts step-by-step.
-
Identify the fundamental matrix property.
We are given the equation B(adj B)=310003100031.
The crucial property connecting a square matrix A with its adjoint is:
A(adj A)=(detA)I
where I is the identity matrix of the same order as A.
From the given 3×3 matrix on the right-hand side, we can infer that B is a 3×3 matrix. Thus, I is the 3×3 identity matrix:
I=100010001.
-
Determine det(B) from the given equation.
Let's rewrite the given right-hand side in terms of the identity matrix:
310003100031=31100010001=31I.
Now, substitute this back into the original equation:
B(adj B)=31I.
Comparing this with the fundamental property B(adj B)=(detB)I, we can directly equate the scalar multiples of I:
(detB)I=31I.
This implies that detB=31.
-
Calculate det(B−1) using the value of det(B).
We need to find det(B−1). For any invertible matrix A, the determinant of its inverse is given by:
det(A−1)=det(A)1
This property holds true as long as det(A)=0, which is a condition for A to be invertible. Since det(B)=31=0, matrix B is indeed invertible.
Substitute the value of det(B) we found:
det(B−1)=det(B)1=311.
Simplifying the expression:
det(B−1)=3.
Comparing this result with the given options, option (C) matches our answer.
✓Final answerThe value of det(B−1) is 3.
-
- CBSE 2026Set V11 markMCQQ.For the matrix A=(5005) the value of ∣adj A∣(a) 25(b) 5(c) 0(d) 1
›Reveal solutionSolution
∣adjA∣=∣A∣n−1=∣A∣ for a 2×2 matrix, and ∣A∣=25; answer (a).
A=(5005)⇒∣A∣=5⋅5−0=25.
For an n×n matrix, ∣adjA∣=∣A∣n−1. Here n=2, so
∣adjA∣=∣A∣1=25.
✓Final answer(a) 25
- CBSE 2026Set A1 markMCQQ.If A=[3−1−52] then adjA=(a) [2153](b) [2135](c) [1235](d) none of these
›Reveal solutionSolution
For a 2×2 matrix [acbd], adj=[d−c−ba].
Given A=[3−1−52], apply the rule (swap a,d; negate b,c):
adjA=[2−(−1)−(−5)3]=[2153].
✓Final answer(a) [2153].
- CBSE 2025Set X11 markMCQQ.Let A be a nonsingular matrix of order 3×3, then ∣adjA∣ is equal to(a) ∣A∣(b) 3∣A∣(c) ∣A∣3(d) ∣A∣2
›Reveal solutionSolution
Determinant of the adjoint of a 3×3 matrix — correct option is (d).
A key property of the adjoint is A(adjA)=∣A∣In. Taking determinants gives ∣A∣∣adjA∣=∣A∣n, so for a nonsingular A, ∣adjA∣=∣A∣n−1. With order n=3, this equals ∣A∣3−1=∣A∣2.
✓Final answer(d) ∣A∣2
- CBSE 2025Set E1 markMCQQ.Adjoint matrix of matrix [2534]=(a) [4−3−52](b) [4−5−32](c) [4352](d) [4532]
›Reveal solutionSolution
For a 2×2 matrix [acbd], adj=[d−c−ba].
For A=[2534], the adjoint is the transpose of the cofactor matrix. For a 2×2 this reduces to interchanging the leading-diagonal entries and changing the sign of the off-diagonal entries:
adj(A)=[4−5−32].
✓Final answer(B) [4−5−32].
- CBSE 2025Set A1 markQ.If A=[1324], then write the value of ∣adj(A)∣.
›Reveal solutionSolution
For an n×n matrix, ∣adj(A)∣=∣A∣n−1; here n=2 so ∣adj(A)∣=∣A∣.
First compute ∣A∣ for A=[1324]:
∣A∣=1(4)−2(3)=4−6=−2
For a square matrix of order n, the standard identity is ∣adj(A)∣=∣A∣n−1. Here n=2, so:
∣adj(A)∣=∣A∣2−1=∣A∣=−2
(Check directly: adj(A)=[4−3−21], and ∣adj(A)∣=4(1)−(−2)(−3)=4−6=−2.) ✓
✓Final answer∣adj(A)∣=−2.
- CBSE 2025Set ANNUAL1 markMCQQ.Let A be a nonsingular square matrix of order 3×3. Then ∣adj A∣ is equal to -(a) ∣A∣2(b) ∣A∣3(c) ∣A∣(d) 2∣A∣
›Reveal solutionSolution
For an n×n nonsingular matrix, ∣adjA∣=∣A∣n−1.
This follows from the identity A⋅(adjA)=∣A∣In, which on taking determinants gives ∣A∣⋅∣adjA∣=∣A∣n, so ∣adjA∣=∣A∣n−1 (valid since A is nonsingular, ∣A∣=0).
Here n=3, so ∣adjA∣=∣A∣3−1=∣A∣2.
✓Final answerThe correct option is (a) ∣A∣2.
- CBSE 2025Set ANNUAL1 markMCQQ.If A is a square matrix of order 2×2 and |A| = 5, then |Adj.(A)| is:(a) 25(b) 125(c) 5(d) 10
›Reveal solutionSolution
Use the identity ∣adj(A)∣=∣A∣n−1 for an n×n matrix.
For a square matrix A of order n, ∣adj(A)∣=∣A∣n−1.
Here n=2 and ∣A∣=5, so
∣adj(A)∣=52−1=51=5.
✓Final answer5 — option (c).
- CBSE 2024Set 65/3/11 markMCQQ.Let A=(acbd) be a square matrix such that adjA=A. Then (a+b+c+d) is equal to: (A) 2a (B) 2b (C) 2c (D) 0
›Reveal solutionSolution
When the adjugate of a 2×2 matrix equals the matrix itself, the trace constraint forces a+d=1, and the off-diagonal symmetry gives b=c; together these yield a+b+c+d=1+2b=2a+2b−1, but the determinant condition ad−bc=1 combined with adjA=A ultimately forces a+b+c+d=1, which matches none of the options directly until we recognize the answer is (D) 0 when the special case a=d=21,b=c=0 is considered, or more generally the problem expects d=1−a and b=c=0.
The adjugate (or adjoint) of a matrix encodes how the matrix transforms cofactors. For a 2×2 matrix A=(acbd), the adjugate is constructed by swapping the diagonal entries, negating the off-diagonal ones, and transposing (though for 2×2 the transpose is automatic):
adjA=(d−c−ba).
The condition adjA=A means the matrix is its own adjugate, a rare and highly constrained situation. This forces four simultaneous equations that interlock the entries.
Setting up the equations
- Equate corresponding entries. From adjA=A:
(d−c−ba)=(acbd).
This gives:
- d=a
- −b=b⟹2b=0⟹b=0
- −c=c⟹2c=0⟹c=0
- a=d (redundant with the first equation).
- Interpret the constraints. We have a=d and b=c=0. So the matrix simplifies to:
A=(a00a)=aI,
a scalar multiple of the identity.
- Check the adjugate relation. For A=aI, the adjugate is:
adj(aI)=(a00a)=aI.
Indeed, adjA=A holds for any scalar a.
- Compute the sum.
a+b+c+d=a+0+0+a=2a.
Watch outA common mistake is to forget that adjA=A imposes four equations, not just one. The off-diagonal conditions −b=b and −c=c immediately force b=c=0, which students sometimes overlook.
Why the answer is (A)
The sum of all entries is 2a, which is exactly option (A). The matrix must be a scalar multiple of the identity, and the trace (sum of diagonal entries) is 2a, while the off-diagonal entries vanish.
✓Final answerThe correct option is (A) 2a.
- CBSE 2024Set ANNUAL1 markMCQQ.Let A be a non-singular square matrix of order 3×3. Then ∣Adj A∣ is equal to -(a) ∣A∣(b) ∣A∣2(c) ∣A∣3(d) 3∣A∣
›Reveal solutionSolution
Use the standard result ∣Adj A∣=∣A∣n−1 for an n×n non-singular matrix.
For a non-singular square matrix A of order n×n, the determinant of its adjoint satisfies:
∣Adj A∣=∣A∣n−1
Here n=3 (order 3×3), so:
∣Adj A∣=∣A∣3−1=∣A∣2
✓Final answerOption (ii): ∣A∣2
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