Null Space of a Matrix Calculator

Enter a numeric matrix, reduce it to RREF, and compute a basis for Null(A).

Matrix

Input

Result

Enter a matrix and press Solve.

Formula

Null(A) = { x : Ax = 0 }

nullity(A) = n - rank(A)

Steps

  1. Read A as an m x n matrix.
  2. Row-reduce A to RREF.
  3. Identify pivot and free columns.
  4. Solve Ax = 0.
  5. Build the null space basis.

RREF

RREF will appear here after solving.

Matrix Analysis

What the Null Space of a Matrix Calculator Helps You Find

A null space calculator turns row reduction into a clear result, showing the vectors that satisfy Ax = 0 and helping you understand the solution space behind a matrix.

Clear RREF Workflow

See how the matrix is reduced into row echelon form so the pivot columns, free variables, and dependent relationships are easier to follow.

Basis Vector Results

Get the null space expressed as a basis, which is the most useful format for homework, engineering work, and linear algebra review.

Homogeneous System Support

The calculator focuses on solutions to Ax = 0, making it ideal when you need to solve a homogeneous system without manually tracking every row operation.

Rank and Free Variable Insight

Understand how the rank of a matrix affects the number of free variables and why that determines the dimension of the null space.

Helpful Learning Companion

Use the result to check your own row-reduction work, compare basis vectors, and build confidence before exams or assignments.

Fast Error Checking

Quickly confirm whether a nonzero null space exists, whether the matrix has only the trivial solution, or whether a calculation needs another look.

Simple Process

How to Use the Null Space Calculator

Enter your matrix, review the reduction, and read the null space result in a form that is ready to use in your solution or notes.

01

Enter the Matrix Values

Start with the coefficients from your matrix. Keep each entry in the correct row and column so the row operations reflect the original system accurately.

02

Review the Row Reduction

The calculator identifies pivots and free variables by reducing the matrix. This step explains why the final null space has its particular dimension.

03

Use the Basis for Ax = 0

Read the final vectors as a basis for the null space. Any linear combination of those basis vectors is a solution to the homogeneous system.

Practical Uses

Where Null Space Results Are Useful

The null space is more than a classroom topic. It appears anywhere linear relationships, constraints, transformations, and systems of equations need to be understood.

Study

Linear Algebra Homework

Check the basis of a null space, confirm your free variables, and make your written solution easier to explain step by step.

Systems

Homogeneous Equations

Find every solution to Ax = 0 by expressing the answer as a span of vectors instead of a long list of separate equations.

Geometry

Vector Space Interpretation

Understand whether the null space forms a line, plane, higher-dimensional subspace, or only the zero vector.

Models

Engineering Constraints

Analyze systems where certain outputs must equal zero, such as balanced forces, circuit relationships, or constrained design equations.

Data

Dependence Detection

Use null space behavior to spot dependent columns and understand when a matrix transformation loses information.

Review

Exam Preparation

Practice interpreting pivots, rank, nullity, and basis vectors so the underlying concepts feel less mechanical and more connected.

Reliable Support

A Cleaner Way to Check Matrix Work

Use the calculator as a fast, focused companion when you need accurate null space results without unnecessary friction.

Free and Accessible

Work through null space problems whenever you need to verify a result, review a concept, or prepare a solution without creating an account.

Built for Quick Review

The layout keeps the important details easy to scan, from the row-reduced matrix to the final basis vectors and nullity.

Works on Any Screen

Whether you are studying from a laptop, tablet, or phone, the content stays readable and the matrix explanation remains easy to follow.

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