Let $ X = \left\{ \begin{bmatrix} a & b \\ c & d \end{bmatrix} \middle| a, b, c, d \in \mathbb{R} \right\} $. If $ f: X \to \mathbb{R} $ is defined by $ f(A) = \det(A) $ for all $ A \in X $, then $ f $ is
one-one but not onto
onto but not one-one
one-one and onto
neither one-one nor onto
To solve the problem, we need to analyze the function \( f : X \rightarrow \mathbb{R} \) defined by \( f(A) = \det(A) \), where \( A \in X \) and \( X \) is the set of all 2x2 matrices of the form:
\[ A = \begin{bmatrix} a & b \\ c & d \end{bmatrix}, \quad \text{with } a, b, c, d \in \mathbb{R} \]
1. Understanding the Function:
The function maps each 2x2 real matrix to a real number which is the determinant of the matrix:
\[ \det(A) = ad - bc \]
2. Determine If the Function Is Onto:
We want to see if for every real number \( r \), there exists a matrix \( A \in X \) such that \( \det(A) = r \).
Take a matrix \( A = \begin{bmatrix} 1 & 0 \\ 0 & r \end{bmatrix} \). Then, \( \det(A) = 1 \cdot r - 0 \cdot 0 = r \).
Hence, any real number \( r \) can be obtained as the determinant of some matrix. So, \( f \) is onto.
3. Determine If the Function Is One-One:
If \( f \) were one-one, then different matrices would have different determinants.
But consider matrices:
\( A_1 = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} \) and \( A_2 = \begin{bmatrix} 2 & 0 \\ 0 & 0.5 \end{bmatrix} \).
Both have \( \det(A_1) = \det(A_2) = 1 \), but \( A_1 \neq A_2 \).
So, \( f \) is not one-one.
Final Answer:
The function is onto but not one-one.
Match the following:
A determinant can be defined in many ways for a square matrix.
The first and most simple way is to formulate the determinant by taking into account the top-row elements and the corresponding minors. Take the first element of the top row and multiply it by its minor, then subtract the product of the second element and its minor. Continue to alternately add and subtract the product of each element of the top row with its respective min or until all the elements of the top row have been considered.
For example let us consider a 1×1 matrix A.
A=[a1…….an]
Read More: Properties of Determinants
Second Method to find the determinant:
The second way to define a determinant is to express in terms of the columns of the matrix by expressing an n x n matrix in terms of the column vectors.
Consider the column vectors of matrix A as A = [ a1, a2, a3, …an] where any element aj is a vector of size x.
Then the determinant of matrix A is defined such that
Det [ a1 + a2 …. baj+cv … ax ] = b det (A) + c det [ a1+ a2 + … v … ax ]
Det [ a1 + a2 …. aj aj+1… ax ] = – det [ a1+ a2 + … aj+1 aj … ax ]
Det (I) = 1
Where the scalars are denoted by b and c, a vector of size x is denoted by v, and the identity matrix of size x is denoted by I.
Read More: Minors and Cofactors
We can infer from these equations that the determinant is a linear function of the columns. Further, we observe that the sign of the determinant can be interchanged by interchanging the position of adjacent columns. The identity matrix of the respective unit scalar is mapped by the alternating multi-linear function of the columns. This function is the determinant of the matrix.