Null Space Calculator

Have you ever wondered how to find the null space of any matrix? If yes then use the null space calculator and see how powerful it is!

Table of Contents:

Introduction to Null Space Calculator:

Null space calculator is an online tool that helps you to find the null space of a given matrix in a few seconds. Our tool evaluates different orders of the matrix, whether it is 2 by 2 order or 3 by 4 matrix, which makes the process of null space matrix to get a solution.

Null Space Calculator

The null space of a matrix calculator is a beneficial tool for students or professionals because when you deal with a higher-order matrix, you may get confused while solving its solution. Our tool is specially designed to provide accurate solutions to null space problems.

What is Null Space?

The null space of a square matrix is a fundamental concept in linear algebra. It refers to the set of all vectors x in the domain of A that span the zero vector under the linear transformation in vector space. It is also known as the kernel of a given matrix.

The null space Null(A) can be denoted as:

$$ Null\;(A) \;=\; \{x∈R^n ∣ Ax=0 \} $$

Where:

  • A is a m×n matrix, A vector map from Rn (the domain) to Rm (the codomain).
  • x is a vector in Rn.
  • 0 is the zero vector in Rm.

The null space provides insight into the behavior of linear transformations in vector spaces.

How to Calculate the Null Space of a Matrix?

For the calculation of the null space (kernel) of a matrix, the null space calculator finds all vectors x such that Ax=0, as A is the given matrix. Let us see how you compute the null space matrix with the help of an example.

Example: Find the Null Space of the following Matrix:

$$ \left[ \begin{matrix} 2 & 4 & 3 \\ 6 & 3 & 1 \\ 2 & 5 & 0 \\ \end{matrix} \right] $$

Solution for step-by-step calculation:

  • Combine the matrix A with the zero vector on the right-hand side to form an augmented matrix [Ax∣0]. $$ \left[ \begin{matrix} 2 & 4 & 3 \\ 6 & 3 & 1 \\ 2 & 5 & 0 \\ \end{matrix} \right], \left[ \begin{matrix} x_1 \\ x_2 \\ x_3 \\ \end{matrix} \right] \;=\; \left[ \begin{matrix} 0 \\ 0 \\ 0 \\ \end{matrix} \right] $$
  • Use the Gaussian elimination method on the augmented matrix to get a reduced row echelon form (RREF). $$ R_1 \leftarrow R_1 \div 2 $$ $$ =\; \left[ \begin{matrix} 1 & 2 & 1.5 \\ 6 & 3 & 1 \\ 2 & 5 & 0 \\ \end{matrix} \right] $$ $$ R_2 \leftarrow R_2 - 6 \times R_1 $$ $$ =\; \left[ \begin{matrix} 1 & 2 & 1.5 \\ 0 & -9 & -8 \\ 2 & 5 & 0 \\ \end{matrix} \right] $$

$$ =\; \left[ \begin{matrix} 1 & 2 & 1.5 \\ 0 & -9 & -8 \\ 0 & 1 & -3 \\ \end{matrix} \right] $$

$$ R_2 \leftarrow R_2 \div -9 $$

$$ =\; \left[ \begin{matrix} 1 & 2 & 1.5 \\ 0 & 1 & 0.88888889 \\ 0 & 1 & -3 \\ \end{matrix} \right] $$

$$ R_1 \leftarrow R_1 - 2 \times R_2 $$

$$ =\; \left[ \begin{matrix} 1 & 0 & -0.27777778 \\ 0 & 1 & 0.88888889 \\ 0 & 0 & -3.88888889 \\ \end{matrix} \right] $$

$$ R_3 \leftarrow R_3 - R_2 $$

$$ =\; \left[ \begin{matrix} 1 & 0 & -0.27777778 \\ 0 & 1 & 0.88888889 \\ 0 & 0 & -3.88888889 \\ \end{matrix} \right] $$

$$ R_3 \leftarrow R_3 \times -0.25714286 $$

$$ =\; \left[ \begin{matrix} 1 & 0 & -0.277777778 \\ 0 & 1 & 0.88888889 \\ 0 & 0 & 1 \\ \end{matrix} \right] $$

$$ R_1 \leftarrow R_1 + 0.27777778 \times R_3 $$

$$ =\; \left[ \begin{matrix} 1 & 0 & 0 \\ 0 & 1 & 0.88888889 \\ 0 & 0 & 1 \\ \end{matrix} \right] $$

$$ R_2 \leftarrow R_2 - 0.88888889 \times R_3 $$

$$ =\; \left[ \begin{matrix} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \\ \end{matrix} \right] $$

  • After getting the reduced echelon form using gauss elimination method, write the basis vectors of the null space such as,

Now solve the matrix equation,

$$ \left[ \begin{matrix} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \\ \end{matrix} \right] \left[ \begin{matrix} x_1 \\ x_2 \\ x_3 \\ \end{matrix} \right] \;=\; \left[ \begin{matrix} 0 \\ 0 \\ 0 \\ \end{matrix} \right] $$

$$ x_1 \;=\; 0 $$

$$ x_2 \;=\; 0 $$

$$ x_3 \;=\; 0 $$

  • Write the null space as the span of the basis vectors that get after finding the value of variables.

Add equation for each free variable,

$$ x_1 \;=\; 0 $$

$$ x_2 \;=\; 0 $$

$$ x_3 \;=\; 0 $$

Solve for each variable in terms of the free variables,

$$ x_1 \;=\; 0 $$

$$ x_2 \;=\; 0 $$

$$ x_3 \;=\; 0 $$

Convert this into vectors,

$$ \left[ \begin{matrix} x_1 \\ x_2 \\ x_3 \\ \end{matrix} \right] \;=\; \left[ \begin{matrix} 0 \\ 0 \\ 0 \\ \end{matrix} \right] $$

If you need to solve null space problems quickly and accurately, try our null space calculator. It's advanced, easy to use, and completely free.

How to Use a Null Space of a Matrix Calculator?

The nullity calculator has a simple layout that helps everyone easily get the solutions to a given null space matrix problem. You just need to put your problem in this matrix nullity calculator and immediately get the result. These steps are:

  • Add the size of the matrix in the input field.
  • Enter the elements of the matrix in the input field.
  • Check your input matrix values before clicking on the calculate button to get the result of the null space question.
  • Click the “Calculate” button to solve the null space problems.
  • Click the “Recalculate” button to evaluate more examples of the null space calculator working method used to get the solution.

Outcome of Null Space Basis Calculator:

Matrix kernel calculator provides you with the solution of null space questions when you click on the calculate button. It may include as:

In the Result Box

When you click on the result button you get the solution of the null space matrix using the reduced echelon form

Possible Steps Box

Click on the steps option so that you get the solution to the null space matrix in steps.

Advantages of Using Nullity Calculator:

It has millions of advantages that you avail when you use it to calculate the given null space problem with a solution. These advantages are:

  • A matrix nullity calculator is a trustworthy tool that always provides you with an accurate solution for various types of null space matrix problems.
  • It is a swift tool that helps you evaluate null space problems with solutions in a few seconds without any difficulty.
  • Our matrix null space calculator is a learning tool that helps you to enhance your knowledge about null space in linear algebra without going to any teacher.
  • It is a manageable tool that can solve null space problems of different order without taking any external effort.
  • Null space basis calculator is a free tool that allows you to use it for the calculation of null space problems.
  • The kernel of matrix calculator can handle null space problems of varying complexities and matrix sizes, making it adaptable to different academic or professional needs without requiring additional tools or resources.
Related References
Frequently Ask Questions

What is the dimension of null space?

The dimension of the null space of a matrix A represents the number of independent vectors that span the null space of A, denoted as dim(Null(A)) or nullity(A) in linear algebra.

To determine the dimension of the null space, first, calculate the rank of the matrix A. The rank is the maximum number of linearly independent row vectors in A with the help of the Gauss elimination method to find the reduced row echelon form (RREF).

After finding the rank of the matrix A, use this formula nullity(A) = n−r where n is the number of columns in A and r is the rank and you get the dimension of a null space.

What is the null space if there is no free variable?

If the null space of matrix A has no free variables, it means that the only solution to the equation Ax = 0 is the trivial solution where x = 0.

However, if there are no free variables after performing the row reduction method it means that all variables are pivot variables, and they must all be zero in order for Ax = 0 to hold true. This solution x = 0 becomes trivial.

What is the significance of the null space?

The null space of a matrix A is significant in several aspects of linear algebra and mathematical applications such as

The null space provides solutions to the homogeneous system of linear equations Ax = 0 dimension and rank using the rank and nullity theorem, linear independence, and span of a set of vectors that are mapped to zero under A.

In short, the null space of a matrix is not only a fundamental concept in linear algebra but also holds practical significance in various mathematical disciplines and applications, ranging from solving equations to analyzing transformations and structures in data and systems.

What is the null space of a nonsingular matrix?

The null space of a nonsingular matrix A is trivial, meaning it consists only of the zero vector 0. If a matrix A is nonsingular, then it has an inverse A-1, such that A−1 = I, where I is the identity matrix.

The null space of A, denoted as Null(A) or ker⁡(A), consists of all vectors x such that Ax = 0. Therefore, the null space of matrix A is Null(A) = 0, which tells that the null space is trivial when A is nonsingular.

What is the relationship between null space and column space?

The relationship between the null space and the column space of matrix A provides insights into the properties of matrix A.

  • Null Space (Nullity): The null space Null(A) of a matrix A or the kernel of A, consists of all vectors x such that Ax = 0.The dimension of the null space dim(Null(A)) is related to the rank of A. Specifically, dim (Null(A)) = n − rank(A), where n is the number of columns of A.
  • Column Space (Range): The column space Col(A) of a matrix A is the span of its column vectors. The dimension of the column space dim(Col(A)) is equal to the rank of A, denoted as rank(A).

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