Q.If the value of a third order determinant is 12, then the value of the determinant formed by replacing each element by its co-factor will be 144.
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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: Determinant Evaluation Using Identities — specifically, the relation between a determinant and its cofactor matrix.
For a square matrix A of order n, if C is the cofactor matrix, then ∣C∣=∣A∣n−1. Here n=3, so ∣C∣=∣A∣2.
Step 1: The given determinant is ∣A∣=12. …
The key idea is that the determinant of the cofactor matrix equals the square of the original determinant for a square matrix. For a third-order determinant with value 12, the cofactor determinant is 122=144.
The problem asks: if a third-order determinant has value 12, what is the value of the determinant formed by replacing each element by its cofactor? This is a classic result in determinant theory, and the answer follows directly from a fundamental property relating a matrix and its adjoint.
Let’s understand why this works. For any square matrix A of order n, the matrix of cofactors (often denoted C) has a determinant that is related to det(A) by a simple power law. Specifically, if A is n×n, then det(cofactor matrix of A)=(detA)n−1. For n=3, this becomes (detA)2.
Why? Because the cofactor matrix is intimately linked to the adjoint (adjugate) of A. The adjoint of A, written adj(A), is the transpose of the cofactor matrix. A well-known identity is:
A⋅adj(A)=det(A)⋅In
Taking determinants on both sides gives:
det(A)⋅det(adj(A))=(detA)n
Since det(adj(A))=det(cofactor matrix) (transpose doesn’t change determinant), we get:
det(cofactor matrix)=(detA)n−1
Now apply this to the given problem.
- Identify the order: The determinant is third order, so n=3. The original determinant value is Δ=12. …
Method: Finding the Determinant of the Cofactor (or Adjoint) Matrix
Use this method whenever a question gives ∣A∣ for an n×n matrix and asks for the determinant of the matrix formed by its cofactors (or its adjoint).
Steps
Step 1: Recall the defining identity linking A and adj(A)
A⋅adj(A)=∣A∣In
where adj(A) is the transpose of the cofactor matrix.
Step 2: Take determinants of both sides
∣A∣⋅∣adj(A)∣=∣A∣In=∣A∣n
using ∣kIn∣=kn for a scalar matrix of order n.
Step 3: Solve for ∣adj(A)∣
Since A is non-singular (∣A∣=0), divide both sides by ∣A∣:
∣adj(A)∣=∣A∣n−1
Step 4: Relate the adjoint's determinant to the cofactor matrix's determinant …
Common Mistakes
Mistake 1: Assuming the cofactor-matrix determinant equals ∣A∣ itself
Why it's wrong: it's tempting to think replacing entries with cofactors "shouldn't change" the determinant, but the correct relationship is a POWER law, ∣A∣n−1, not equality — for n>2 these give very different numbers. Correct approach: always derive from A⋅adj(A)=∣A∣In rather than assuming equality.
Mistake 2: Using the wrong exponent (forgetting it's n−1, not n) …
Showing the 12 most recent of 19 on this concept.
- COMEDK 2026Set 2026-A1 markMCQQ.Matrix A=1111−2022−1, Given M22 and A32 are the minor and cofactor of the adjoint matrix of A respectively then the value of the expression M22+A32−∣adj∣ is: (A) −729 (B) −117 (C) −81 (D) −99
›Reveal solutionSolution
detA=9⇒∣adjA∣=92=81. On the adjoint matrix, M22=−18 and A32=18, so M22+A32−∣adjA∣=−18+18−81=−81. The correct option is (C).
Concept
The minor and cofactor referred to are those of the adjoint matrix, so the adjoint must be built explicitly. Also, for an n×n matrix ∣adjA∣=(detA)n−1, which here gives ∣adjA∣=(detA)2.
Solution
- Determinant. detA=1(2)−1(−3)+2(2)=9.
- ∣adjA∣. (detA)2=81.
- Adjoint. Transposing the cofactor matrix of A, adjA=2321−3160−3. …
- COMEDK 2026Set 2026-M1 markMCQQ.Given P=211α23123 is the adjoint of a 3×3 matrix A and ∣A∣=3, then the value of α is: (A) 7 (B) -25 (C) -8 (D) -26
›Reveal solutionSolution
The key idea is that for any square matrix A, we have A⋅adj(A)=∣A∣I. Given P=adj(A) and ∣A∣=3, we can multiply A by P and equate to 3I to solve for α. The value is α=−8, so option (C) is correct.
We start with the fundamental relationship between a matrix and its adjoint. For any 3×3 matrix A,
A⋅adj(A)=∣A∣I
where I is the identity matrix. Here we are told P=adj(A) and ∣A∣=3, so
A⋅P=3I.
This means P is essentially the inverse of A scaled by 3. But we don't know A directly — we only know P. However, we can use the fact that the determinant of P is related to ∣A∣:
∣P∣=∣adj(A)∣=∣A∣n−1=32=9.
That gives us an equation in α directly, without needing A at all.
- Compute ∣P∣ in terms of α.
P=211α23123
Expand along the first row:
∣P∣=2⋅2323−α⋅1123+1⋅1123.
Compute each minor:
- 2323=(2)(3)−(2)(3)=0.
- 1123=(1)(3)−(2)(1)=1.
So:
∣P∣=2⋅0−α⋅1+1⋅1=−α+1. …
- KCET 2026Set UNKNOWN1 markMCQQ.If A and B are invertible matrices of same order, then which of the following is not correct? (A) A⋅(adjA)=(adjA)⋅A=∣A∣I (B) A⋅adjA=adjA⋅A=∣A∣ (C) (AB)−1=B−1A−1 (D) ∣A∣=0,∣B∣=0
›Reveal solutionSolution
Check each identity against the standard results for invertible matrices; the one missing the identity matrix I on the right side is incorrect.
Step 1 — Check option (A)
For any square matrix A, the standard identity is A⋅(adjA)=(adjA)⋅A=∣A∣I, where I is the identity matrix of the same order. This is a correct, standard result.
Step 2 — Check option (B)
Option (B) states A⋅adjA=adjA⋅A=∣A∣. The right-hand side here is just the scalar ∣A∣, not ∣A∣I. But A⋅(adjA) is a matrix (of the same order as A), and a matrix can never equal a bare scalar unless trivially 1×1. This statement is incorrect as written — it drops the identity matrix I. …
- COMEDK 2025Set 2025-A1 markMCQQ.If A(adjA)=500050005, then the value of ∣A∣+∣adjA∣ is equal to : (A) 5 (B) 25 (C) 125 (D) 30
›Reveal solutionSolution
The key idea is that for any square matrix A, A(adjA)=∣A∣I. Here that gives ∣A∣=5, and since ∣adjA∣=∣A∣n−1 for an n×n matrix, we get ∣adjA∣=52=25. Their sum is 5+25=30, so the answer is (D).
The problem gives us A(adjA)=5I, where I is the 3×3 identity matrix. This is a classic property: for any square matrix A, the product A times its adjugate equals the determinant times the identity. So the scalar on the diagonal is exactly ∣A∣. That means ∣A∣=5 immediately.
Now, we also need ∣adjA∣. There's a neat formula: for an n×n matrix, ∣adjA∣=∣A∣n−1. Here n=3, so ∣adjA∣=52=25.
Thus the sum is 5+25=30.
Let's walk through it step by step.
- Recall the defining property of the adjugate. For any square matrix A, we have
A(adjA)=(adjA)A=∣A∣I.
This is the fundamental relation. The problem gives us the left-hand side explicitly as 5I, so we can directly compare:
∣A∣I=5I⇒∣A∣=5.
- Find ∣adjA∣ using the determinant of both sides. Take determinants of the equation A(adjA)=∣A∣I:
∣A∣⋅∣adjA∣=∣A∣I.
The right-hand side is a scalar matrix: ∣A∣I is ∣A∣ times the identity, so its determinant is (∣A∣)n for an n×n matrix. Here n=3, so
∣A∣I=(∣A∣)3.
Thus
- COMEDK 2025Set 2025-E1 markMCQQ.Kiran purchased 3 pencils, 2 notebooks and one pen for ₹41. From the same shop Manasa purchased 2 pencils, one notebook and 2 pens for ₹ 29 , while Shreya purchased 3 pencils, 2 notebooks and 2 pens for ₹ 44. The above situation can be represented in matrix form as AX=B. Then ∣adjA∣ is equal to (A) 9 (B) −9 (C) −1 (D) 1
›Reveal solutionSolution
The coefficient matrix has detA=−1, and for a 3×3 matrix ∣adjA∣=∣A∣2=1 — option (D).
Set up the system. Let pencil =x, notebook =y, pen =z:
3x+2y+z=41,2x+y+2z=29,3x+2y+2z=44.
So
A=323212122.
Determinant (expand along the first row):
detA=3(1⋅2−2⋅2)−2(2⋅2−2⋅3)+1(2⋅2−1⋅3)
=3(−2)−2(−2)+1(1)=−6+4+1=−1. …
- COMEDK 2025Set 2025-E1 markMCQQ.Value of the determinant of a matrix A of order 3×3 is 7 . Then the value of the determinant formed by the cofactors of matrix A is (A) 7 (B) 49 (C) 14 (D) 343
›Reveal solutionSolution
The determinant of the cofactor matrix (the adjugate) of a 3×3 matrix A equals (detA)n−1=(detA)2. Given detA=7, the answer is 72=49, so option (B).
The key idea is that the matrix of cofactors is intimately linked to the inverse of A. For any square matrix A, the product A⋅(adj A)=(detA)I, where adj A is the transpose of the cofactor matrix. Taking determinants on both sides gives a direct relationship between det(cofactor matrix) and detA.
For an n×n matrix, the determinant of the cofactor matrix (strictly, of the adjugate) is (detA)n−1. Here n=3, so the exponent is 2.
Let’s walk through it carefully.
- Define the cofactor matrix and adjugate. For a 3×3 matrix A, let Cij be the cofactor of entry aij. The cofactor matrix is C=[Cij]. The adjugate (or classical adjoint) is the transpose: adj(A)=CT. The fundamental property is:
A⋅adj(A)=adj(A)⋅A=(detA)I3.
This holds for any square matrix.
- Take determinants of both sides. From A⋅adj(A)=(detA)I3, we have:
det(A⋅adj(A))=det((detA)I3).
The left side, by the product rule, is detA⋅det(adj(A)).
The right side: multiplying a 3×3 identity matrix by the scalar detA gives a diagonal matrix with detA on each diagonal entry. Its determinant is (detA)3.
- Set up the equation.
detA⋅det(adj(A))=(detA)3.
Since detA=7=0, we can divide both sides by detA:
- COMEDK 2025Set 2025-M1 markMCQQ.The sum of three numbers is 6 . Twice the third number, when added to the first number gives 7 , On adding the sum of the second and third numbers to thrice the first number, we get 12 . The above situation can be represented in matrix form as AX=B. Then the ∣adjA∣ is equal to (A) −4 (B) 4 (C) −64 (D) 16
›Reveal solutionSolution
We translate the word problem into a system of three linear equations, write it in matrix form AX=B, compute the determinant of A, and then use the property ∣adjA∣=∣A∣n−1 with n=3 to get the answer ∣adjA∣=16.
We start by turning the story into equations.
Let the three numbers be x, y, and z.
-
Translate the conditions
- “The sum of three numbers is 6” → x+y+z=6.
- “Twice the third number, when added to the first number gives 7” → x+2z=7.
- “On adding the sum of the second and third numbers to thrice the first number, we get 12” → 3x+(y+z)=12, i.e. 3x+y+z=12.
So the system is:
⎩⎨⎧x+y+z=6x+0y+2z=73x+y+z=12
- Write in matrix form AX=B
A=113101121,X=xyz,B=6712
- Find ∣A∣ Compute the determinant:
∣A∣=1⋅0121−1⋅1321+1⋅1301
=1⋅(−2)−1⋅(1−6)+1⋅(1)…=1⋅(0⋅1−2⋅1)−1⋅(1⋅1−2⋅3)+1⋅(1⋅1−0⋅3)
-
- COMEDK 2024Set 2024-A1 markMCQQ.
[!FORMULA] If A (adjA)=5I, where I is the identity matrix of order 3, then ∣adjA∣=
(A) 5 (B) 125 (C) 25 (D) 10›Reveal solutionSolution
The key idea is that for a square matrix, A(adjA)=∣A∣I. Given A(adjA)=5I and the order is 3, we find ∣A∣=5 and then use ∣adjA∣=∣A∣n−1=52=25. The correct option is (C).
We start with a fundamental property of adjugates: for any square matrix A of order n,
A(adjA)=(adjA)A=∣A∣I.
This is the definitional relationship — the adjugate is the transpose of the cofactor matrix, and multiplying by A yields a diagonal matrix where every diagonal entry is the determinant ∣A∣.
Here we are told A(adjA)=5I and the order is 3. That means n=3. Comparing with the property, we immediately see that ∣A∣I=5I, so ∣A∣=5.
Now we need ∣adjA∣. There is a well-known formula: for an n×n matrix,
∣adjA∣=∣A∣n−1.
Why? Because from A(adjA)=∣A∣I, take determinants of both sides:
∣A∣⋅∣adjA∣=∣A∣n.
If ∣A∣=0 (which it is, since 5 ≠ 0), divide both sides by ∣A∣ to get ∣adjA∣=∣A∣n−1.
Applying this with n=3 and ∣A∣=5:
∣adjA∣=53−1=52=25. …
- COMEDK 2024Set 2024-E1 markMCQQ.
[!FORMULA] If A=[5a3−b2] and AadjA=AAt, then 5a+b is equal to
(A) 5 (B) −1 (C) 4 (D) 13›Reveal solutionSolution
The key idea is to use the property AadjA=∣A∣I and equate it to AAt, then compare entries to solve for a and b. The result is 5a+b=5.
We are given
A=(5a3−b2)
and the condition
AadjA=AAt.
We need 5a+b.
Concept and Intuition
For any square matrix A, a fundamental identity is
AadjA=∣A∣I,
where ∣A∣ is the determinant and I is the identity matrix. This is often faster than computing the adjugate explicitly. The right-hand side AAt is a product we can compute directly. So we set
∣A∣I=AAt,
which gives us a system of equations by comparing entries.
Step-by-step solution
- Compute ∣A∣
∣A∣=(5a)(2)−(−b)(3)=10a+3b.
- Write the left-hand side
AadjA=∣A∣I=(10a+3b)(1001)=(10a+3b0010a+3b).
- Compute AAt First, At=(5a−b32). Then
AAt=(5a3−b2)(5a−b32)=((5a)(5a)+(−b)(−b)(3)(5a)+(2)(−b)(5a)(3)+(−b)(2)(3)(3)+(2)(2)).
Simplify each entry:
- Top-left: 25a2+b2
- Top-right: 15a−2b
- Bottom-left: 15a−2b (same)
- Bottom-right: 9+4=13
So
AAt=(25a2+b215a−2b15a−2b13).
- Equate the two matrices From AadjA=AAt we have:
(10a+3b0010a+3b)=(25a2+b215a−2b15a−2b13).
This gives three equations (the off-diagonals give the same condition):
- (1) 10a+3b=25a2+b2
- (2) 0=15a−2b → 15a=2b → b=215a
- (3) 10a+3b=13
- Solve the system From (2): b=215a. …
- COMEDK 2024Set 2024-M1 markMCQQ.
[!FORMULA] If P=112α34334 is the adjoint of a 3×3 matrix A and ∣A∣=4 then α is equal to
(A) 11 (B) 4 (C) 0 (D) 5›Reveal solutionSolution
The key idea is that for a 3×3 matrix A, adj(A)=∣A∣A−1, so P must satisfy P=4A−1. Taking determinants gives ∣P∣=42=16, which yields an equation for α. Solving gives α=11, so the correct option is (A).
We are told that P is the adjoint of A, and ∣A∣=4. For any invertible square matrix A, the fundamental relation is
A⋅adj(A)=∣A∣I.
Thus adj(A)=∣A∣A−1. Here P=adj(A), so
P=4A−1.
Taking determinants on both sides:
∣P∣=∣4A−1∣=43∣A−1∣=64⋅∣A∣1=464=16.
So we must have ∣P∣=16. This gives an equation for α.
Now compute ∣P∣:
P=112α34334.
- Expand along the first row:
∣P∣=1⋅3434−α⋅1234+3⋅1234.
- Compute the 2×2 determinants:
3434=3⋅4−3⋅4=0,
1234=1⋅4−3⋅2=4−6=−2.
- Substitute:
- KCET 2023Set A-21 markMCQQ.If A=[2−k123−k] is singular matrix, then the value of 5k−k2 is equal to (A) −6 (B) −4 (C) 6 (D) 4
›Reveal solutionSolution
"Singular" means the determinant is zero; expand it, and the resulting quadratic is k2−5k+4=0 — read 5k−k2 straight off it without ever solving for k.
Step 1 — Condition for a singular matrix.
A square matrix is singular exactly when it has no inverse, i.e. when
detA=0.
Step 2 — Expand the determinant.
detA=2−k123−k=(2−k)(3−k)−(2)(1)
=(6−2k−3k+k2)−2=k2−5k+4
Step 3 — Set it to zero.
k2−5k+4=0⟹k2−5k=−4
Step 4 — Read off the required expression.
5k−k2=−(k2−5k)=−(−4)=4 …
- COMEDK 2023Set 2023-M1 markMCQQ.If A is a matrix of order 4such that A(adjA)=10 I, then ∣adjA∣ is equal to (A) 10 (B) 100 (C) 1000 (D) 10000
›Reveal solutionSolution
Since A(adj A)=∣A∣I=10I, we get ∣A∣=10; then ∣adj A∣=∣A∣n−1=103=1000 for order 4.
Property: A(adj A)=∣A∣I. Comparing with A(adj A)=10I gives ∣A∣=10. …
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