Properties Of Determinants

In linear algebra, a determinant is a special number that can be determined from a square matrix. The determinant of a matrix, denoted as det(P), |P| or det P, has some useful properties which allow us to obtain the same results with different and simpler entries (elements). There are 10 main properties of determinants, namely: reflection property, all-zero property, proportionality or repetition property, switching property, scalar multiple properties, sum property, invariance property, factor property, triangle property, and co-factor matrix property. All these properties are covered in detail below, along with solved examples.

Determinants: All Topics

Introduction to Determinants

Minors and Cofactors

Properties of Determinants

System of Linear Equations Using Determinants

Differentiation and Integration of Determinants

Standard Determinants

Important Properties of Determinants

  1. The determinant of a matrix is equal to the product of its eigenvalues.
  2. The determinant of a matrix is equal to the sum of its principal minors.
  3. The determinant of a triangular matrix is equal to the product of its diagonal entries.
  4. The determinant of a matrix is invariant under row and column operations.
  5. The determinant of a matrix is invariant under transposition.
  6. The determinant of a matrix is zero if and only if the matrix is singular.
  7. The determinant of a product of matrices is equal to the product of their determinants.

1. Reflection Property:

The determinant remains unaltered if its columns are changed into rows and the rows into columns. This is known as the property of reflection.

2. All-Zero Property:

If all the elements of a row (or column) are zero, then the determinant is zero.

3. Proportionality (Repetition) Property:

If all elements of a row (or column) are proportional (identical) to the elements of some other row (or column), then the determinant is zero.

4. Property Switching:

The sign of a determinant is changed when any two rows (or columns) are interchanged.

5. Scalar Multiple Property:

The determinant of a row (or column) multiplied by a non-zero constant will result in the determinant being multiplied by the same constant.

6. Sum Property:

(\left| a1c1d1 a2c2d2 a3c3d3  \right| + \left| b1c1d1 b2c2d2 b3c3d3  \right| = \left| a1+b1c1d1 a2+b2c2d2 a3+b3c3d3  \right|)

Property of Invariance:

(\left| a1b1c1 a2b2c2 a3b3c3  \right|=\left| a1+αb1+βc1b1c1 a2+αb2+βc2b2c2 a3+αb3+βc3b3c3  \right|)

That is, a determinant remains unaltered under an operation of the form.

Ci Ci + αCj + βCk, where j, k i

Either

An operation of the form R_i \rightarrow R_i + \alpha R_j + \beta R_k, where j, k \neq i.

Factor Property:

(x - α) is a factor of Δ if Δ becomes zero when x = α.

Triangle Property:

The determinant is equal to the product of diagonal elements if all elements above or below the main diagonal are zeros. That is,

(\left| a100 a2b20 a3b3c3  \right|={{a}_{1}}{{b}_{2}}{{c}_{3}})

10. Finding the Determinant of a Cofactor Matrix:

(Δ=|a11a12a13 a21a22a23 a31a32a33 |;then;Δ1=|C11C12C13 C21C22C23 C31C32C33 |)

Where ΔCij denotes the cofactor of the element aij in Δ.

Properties of Determinants: Example Problems

Question 1: Prove that using properties of determinants?

(\left| abc bca cab  \right| = (a+b+c)(ab+bc+ca - a^2 - b^2 - c^2))

Given:

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Solution:

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We can prove the given problem by utilizing the invariance and scalar multiple properties of determinants.

(Δ=|abc bca cab |\=|a+b+cbc b+c+aca c+a+bab |Operating C1C1+C2+C3)

(=(a+b+c)|1bc 0cbac 0abbc |\=(a+b+c)|100 0cbac 0abbc |[Operating(R2R2R1,and,R3R3R1)] )

=(a + b + c) \[(c - b) \cdot (b - c) - (a - b) \cdot (a - c)\]

$$\left( a+b+c \right)\left( ab+bc+ca-{{a}^{2}}-{{b}^{2}}-{{c}^{2}} \right)$$

Answer:

Using the Laplace Expansion for a 3x3 matrix, we can expand the determinant as:

|α2βαγα αββ2γβ αγβγγ2 |=(α2)|β2γβ βγγ2 |+(βα)|αββ2 αγβγ |+(γα)|αβγβ αγγ2 |

Using the Laplace Expansion for a 2x2 matrix, we can expand the determinants in the above equation as:

|α2βαγα αββ2γβ αγβγγ2 |=(α2)(β2(γ2)(γβ)(βγ))+(βα)(αβ(γ2)(αγ)(βγ))+(γα)(αβ(γβ)(αγ)(β2))

Simplifying the above equation, we get

|α2βαγα αββ2γβ αγβγγ2 |=4α2β2γ2

Given:

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Solution:

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Take common (α,β,γ) from the left-hand side and then use scalar multiple properties and the invariance property of the determinant to prove the given problem.

(\Delta = \left|α2βαγα αββ2γβ αγβγγ2\right|)

(\Delta =\alpha \beta \gamma \left| ααα βββ γγγ  \right|) taken from ({{C}_{1}},{{C}_{2}},{{C}_{3}} ; ;with ;\alpha ,\beta ,\gamma ;common;respectively)

(Now;taking;[α,β,γ];common;from;R1,R2,R3;respectively;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;Taking;[α,β,γ];common;from;R1,R2,R3;respectively)

(\Delta = \alpha^2 \beta^2 \gamma^2 \left| 111 111 111  \right|)

Now applying and R3R3+R1;we;have;Δ=α2β2γ2|111 002 020 |

(Now;expanding;along;C1,Δα2×β2(1)×γ2(1)|02 20 |=;;4α2β2γ2)

Therefore, it is proven.

Answer 3:

Using Laplace Expansion along the first column:

|αβγ θϕψ λμv |=α|ϕψ μv |β|θψ λv |+γ|θϕ λμ | =α|μv ϕψ |β|λv θψ |+γ|λμ θϕ | =|βμϕ αλθ γvψ |

Given:

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Solution:

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Reflecting across the diagonal and then switching the rows and columns using the determinant’s switching property, we can obtain the desired result.

L.H.S. = (|αβγ θϕψ λμv | = |αθλ βϕμ γψv | )

Interchanging rows and columns across the diagonal

(=|βμϕ αλθ γvψ |)

R.H.S.

Question 4: If (a), (b), and (c) are all different and (\left| aa21+a3 bb21+b3 cc21+c3  \right|=0), then what is the value of (a), (b), and (c)?

Proof:

Let a, b, and c be real numbers.

Then, abc = a(bc) = a(-1) = -a

Therefore, abc = -1

Given:

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Solution:

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Split the given determinant using the sum property. Then, by using scalar multiple, switching and invariance properties of determinants, we can prove the given equation.

(D=|aa21 bb21 cc21 |+abc|1aa2 1bb2 1cc2 |\=|aa21 bb21 cc21 |+abc|1aa2 1bb2 1cc2 |)

(=(1)1|1a2c 1b2b 1c2a |+abc|1aa2 1bb2 1cc2 |;[C1C3,in,,1st,,det.] )

\(\begin{array}{l}={{\left( -1 \right)}^{2}}\left| \begin{matrix} 1 & a & {{a}^{2}} \\ 1 & c & {{c}^{2}} \\ 1 & b & {{b}^{2}} \\ \end{matrix} \right|+abc\left| \begin{matrix} 1 & a & {{a}^{2}} \\ 1 & c & {{c}^{2}} \\ 1 & b & {{b}^{2}} \\ \end{matrix} \right| \;\;\left[ {{C}\_{2}}\leftrightarrow {{C}\_{3}}\,in\,\,1st\,\,\det . \right]\end{array} \)

(\begin{array}{l}=\left( 1+abc \right)\left| 1aa2 1bb2 1cc2  \right|\end{array})

(=(1+abc)|1aa2 0bab2a2a2 0cac2a2a2 |;;[R2R2aR1,,and,,R3R3aR1] )

(=(1+abc)|bab2a2 cac2a2 |;(expanding ;along ;1st ;row)\=(1+abc)(ba)(ca)|1b+a 1c+a | )

(=(1+abc)(bc)(ca)(c+aba)\=(1+abc)(ba)(ca)(cb) )

(0=(1+abc)(ab)(bc)(ca);)

((1+abc)(ab)(bc)(ca)=0)

(abc + 1) = 0

Since a, b, and c are different (i.e. ab, bc, and ca), hence, abc=1.

Question 5: Prove that |a+b+2cab cb+c+2ab cac+a+2b |=2(a+b+c)3

Given:

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Solution:

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We can expand the L.H.S. simply by using switching and scalar multiple properties.

(|a+b+2cab cb+c+2ab cac+a+2b |)

Applying C1C1+(C2+C3), we obtain

|2(a+b+c)ab 2(a+b+c)b+c+2ab 2(a+b+c)ac+a+2b | =2(a+b+c)|1ab 1b+c+2ab 1ac+a+2b |

(R2R1+R1;;and;;R3R3+R1;;(given))

(Missing or unrecognized delimiter for \left )

Therefore, it has been proven.

Answer 6:

Let (A = |a2+1abac abb2+1bc acbcc2+1 |).

Expanding along the first row, we have

(A = ({{a}^{2}}+1)({{b}^{2}}+{{c}^{2}}+1-bc)-ab(ac-bc)+ac(ab-ac) )

Simplifying, we have

(A = {{a}^{2}}({{b}^{2}}+{{c}^{2}}+1)+1-{{b}^{2}}-{{c}^{2}}-bc+ac(bc-ab))

Since (bc = ab), we have

(A = {{a}^{2}}({{b}^{2}}+{{c}^{2}}+1)+1-{{b}^{2}}-{{c}^{2}}+ac(ab-bc))

But (ac = bc), so

(A = {{a}^{2}}({{b}^{2}}+{{c}^{2}}+1)+1-{{b}^{2}}-{{c}^{2}} )

(A = 1+{{a}^{2}}+{{b}^{2}}+{{c}^{2}} )

Therefore, (\left| a2+1abac abb2+1bc acbcc2+1  \right|=1+{{a}^{2}}+{{b}^{2}}+{{c}^{2}})

Given:

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Solution:

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(|a2+1abac abb2+1bc acbcc2+1 | =a2+b2+c2+1+2abc)

By utilizing scalar multiplicative and invariance properties.

L.H.S.= (|a2+aa2ba2c abb2+bb2c acbcc2+c |; ) Multiplying C1,C2,C3 by a, b, c respectively

(=1abc|a(a2+1)ab2ac2 a2bb(b2+1)bc2 a2cb2cc(c2+1) ||abc abc abc |; ) Now taking a, b, c common from R1,R2,R3 respectively

(=abcabc|a2+1b2c2 a2+1b2+1c2 a2+1b2c2+1 |\=|1+a2+b2+c2b2c2 1+a2+b2+c2b2+1c2 1+a2+b2+c2b2c2+1 |;;;[C1C1+C2+C3] )

(=(1+a2+b2+c2)|1b2c2 010 001 |\=(1+a2+b2+c2)|100 010 001 |;;[R1R1R2,R3] )

(R.H.S.=1+a2+b2+c2 (1+a2+b2+c2)(1)=R.H.S.)

Hence Proved

Matrices and Determinants: Important Topics

JEE Maths - Matrices and Determinants - Important Topics

Important Questions on Matrices and Determinants

JEE Maths: Matrices and Determinants - Important Questions

Top 10 Most Important and Expected JEE Main Questions on Matrices and Determinants

Matrices and Determinants Top 10 Most Important and Expected JEE Main Questions

Frequently Asked Questions

The reflection property of determinants states that the determinant of a matrix is equal to the determinant of its transpose.

The determinant remains unchanged if the columns are changed into rows and the rows into columns. This is known as the property of reflection.

What happens if two rows or columns of a determinant are interchanged?

The sign of the determinant changes when two rows or columns are swapped.

The proportionality property of determinants states that the value of a determinant is unchanged when any row or column is multiplied by a non-zero constant.

The determinant of a matrix is zero if any row or column is proportional or identical to another row or column; this is referred to as the repetition property.

The triangle property of determinants states that the determinant of a triangular matrix is equal to the product of the elements on the main diagonal of the matrix.

The determinant is equal to the product of diagonal elements if all the elements of the determinant above or below the main diagonal are zeros.

Yes, a determinant can be zero.

Yes. A determinant can be zero, negative or positive.

Yes, the determinant of an identity matrix is equal to 1.

Yes. The determinant of an identity matrix is always 1.

The All Zero Property of Determinants states that if all elements of a determinant are zero, then the value of the determinant is also zero.

According to the all-zero property of determinants, if all the elements of a row/column are zero, then the determinant is equal to zero.

The determinant of A-1 is equal to the reciprocal of the determinant of A.

If $\mathbf{A^{-1}}$ is the inverse of matrix $\mathbf{A}$, then $\det(\mathbf{A^{-1}}) = \frac{1}{\det(\mathbf{A})}$.



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