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MathematicsAlgebraTop Priority (3-4 Qs in JEE)

Matrices & Determinants Formulas

Matrix algebra, determinant expansion, adjoint properties, inverse, Cramer's rule, and systems of linear equations.

9 Formulas•1,015+ Questions in Bank

Core Formulas & Mathematical Identities

9
01

Determinant Properties

∣AT∣=∣A∣,∣AB∣=∣A∣∣B∣,∣kA∣=kn∣A∣(n×n matrix)|A^T| = |A|, \quad |AB| = |A||B|, \quad |kA| = k^n |A| \quad (n \times n \text{ matrix})

Scalar multiplication pulls out factor k raised to the dimension power n.

Examiner Tip: |A⁻¹| = 1 / |A|.
02

Adjoint Properties

A⋅adj(A)=∣A∣In,∣adj(A)∣=∣A∣n−1,∣adj(adj(A))∣=∣A∣(n−1)2A \cdot \text{adj}(A) = |A| I_n, \quad |\text{adj}(A)| = |A|^{n-1}, \quad |\text{adj}(\text{adj}(A))| = |A|^{(n-1)^2}

Crucial adjoint determinant power formulas tested almost every year in JEE Main.

Examiner Tip: For 3x3 matrix (n = 3): |adj(A)| = |A|² and |adj(adj(A))| = |A|⁴.
03

Matrix Inverse Formula

A−1=1∣A∣adj(A)(∣A∣≠0)A^{-1} = \frac{1}{|A|} \text{adj}(A) \quad (|A| \ne 0)

Inverse exists if and only if matrix A is non-singular (|A| ≠ 0).

Examiner Tip: (AB)⁻¹ = B⁻¹ A⁻¹ (reversal law).
04

Cramer's Rule for Linear Systems

x=ΔxΔ,y=ΔyΔ,z=ΔzΔx = \frac{\Delta_x}{\Delta}, \quad y = \frac{\Delta_y}{\Delta}, \quad z = \frac{\Delta_z}{\Delta}

Determinant method for solving system of linear equations.

Examiner Tip: Δ ≠ 0: Unique solution. Δ = 0 with any Δ_i ≠ 0: Inconsistent (No solution).
05

Symmetric & Skew-Symmetric Matrices

A=A+AT2+A−AT2,Skew-Symmetric: AT=−A  ⟹  aii=0A = \frac{A + A^T}{2} + \frac{A - A^T}{2}, \quad \text{Skew-Symmetric: } A^T = -A \implies a_{ii} = 0

Every square matrix is uniquely decomposable into symmetric and skew-symmetric parts.

Examiner Tip: Determinant of odd-order skew-symmetric matrix is ALWAYS zero.
06

Orthogonal Matrix Property

A⋅AT=I  ⟹  ∣A∣=±1,A−1=ATA \cdot A^T = I \implies |A| = \pm 1, \quad A^{-1} = A^T

Orthogonal matrices preserve lengths and angles.

Examiner Tip: Rows and columns form orthonormal vectors.
07

Cayley-Hamilton Theorem & Matrix Powers

det⁡(A−λI)=0  ⟹  P(A)=O,A2−tr(A)A+∣A∣I=O  (2×2)\det(A - \lambda I) = 0 \implies P(A) = O, \quad A^2 - \text{tr}(A)A + |A|I = O \; (2 \times 2)

Every square matrix satisfies its own characteristic polynomial equation. Enables computing high powers and inverses.

Examiner Tip: To find A⁻¹, multiply the characteristic equation throughout by A⁻¹.
08

Special Matrix Types (Idempotent, Involutory, Nilpotent)

A2=A  (Idempotent),A2=I  (Involutory),Ak=O  (Nilpotent),tr(AB)=tr(BA)A^2 = A \; (\text{Idempotent}), \quad A^2 = I \; (\text{Involutory}), \quad A^k = O \; (\text{Nilpotent}), \quad \text{tr}(AB) = \text{tr}(BA)

Key algebraic matrix classes frequently tested in eigenvalue and matrix polynomial questions.

Examiner Tip: Eigenvalues of idempotent matrices can only be 0 or 1. Determinant of involutory matrix is ±1.
09

Homogeneous System of Linear Equations (AX = 0)

∣A∣≠0  ⟹  X=O  (Trivial Unique Solution),∣A∣=0  ⟹  Infinitely Many Non-Trivial Solutions|A| \ne 0 \implies X = O \; (\text{Trivial Unique Solution}), \quad |A| = 0 \implies \text{Infinitely Many Non-Trivial Solutions}

Criterion for existence of non-zero solutions to homogeneous linear equations.

Examiner Tip: If a homogeneous system has a non-trivial solution, its determinant MUST equal 0.

Top Examiner Traps & Pitfalls

Frequently tested misconceptions in Matrices & Determinants

  • •Confusing det(kA) with k*det(A): det(kA) = k^n * det(A) where n is matrix order.
  • •Cramer's rule: if Δ = 0 and at least one Δ_i ≠ 0, NO solution. If all Δ = Δ_x = Δ_y = Δ_z = 0, can be infinite OR no solution.