Rank and Nullity of a Matrix Calculator

Calculate rank, nullity, pivots, dimensions, and reduced forms. Review row steps with clear result tables. Use exact matrix results for reliable homework study checks.

Matrix Calculator

Use one row per line. Separate entries with spaces or commas. Fractions like 3/4 are accepted.

Formula Used

The calculator uses row reduction to convert matrix A into reduced row echelon form. Pivot columns are counted after reduction.

Rank(A) = number of pivot columns

Nullity(A) = number of columns − Rank(A)

Rank(A) + Nullity(A) = number of columns

Left nullity is also shown as number of rows minus rank. It describes the dimension of the left null space.

Example Data Table

Matrix Rows Columns Rank Nullity Meaning
[1 2 3; 2 4 6] 2 3 1 2 Rows are dependent.
[1 0; 0 1] 2 2 2 0 Full rank square matrix.
[1 2 0; 0 1 3] 2 3 2 1 One free variable exists.

How to Use This Calculator

  1. Enter the number of rows and columns.
  2. Click the grid button to build input cells.
  3. Type each matrix entry into the cells.
  4. Set tolerance and decimal places if needed.
  5. Press the calculate button.
  6. Review rank, nullity, pivots, free columns, and RREF.
  7. Use the CSV or PDF option to save the result.

Rank and Nullity Guide

A rank and nullity calculator helps you study a matrix through its pivot structure. The rank tells how many independent columns or rows remain after row reduction. The nullity tells how many free variables appear in the homogeneous system Ax equals zero. Together, these values describe the size of the column space and the kernel.

Why Rank Matters

Rank shows the dimension of the image of a matrix. A high rank means the matrix carries more independent information. For a square matrix, full rank often means the related linear system has a unique solution. For a rectangular matrix, rank still measures independent direction count. It also helps detect redundant equations, dependent columns, and possible compression.

Why Nullity Matters

Nullity is the dimension of the solution space for Ax equals zero. A nullity of zero means only the zero vector solves the homogeneous equation. A larger nullity means the matrix has free directions. Those directions form the null space. This is useful in algebra, engineering, graphics, statistics, and optimization.

How The Tool Works

The calculator reduces the matrix into reduced row echelon form. It searches for pivot entries column by column. Each pivot row is normalized. Other rows are cleared above and below the pivot. The resulting matrix reveals pivot columns and free columns. The number of pivot columns is the rank. The number of non-pivot columns is the nullity.

Practical Uses

Students can check homework steps. Teachers can prepare examples. Engineers can inspect constraint systems. Data analysts can discover linear dependence in features. The tool also lists row operations, so the result is easier to review. Decimals and tolerance settings help when entries contain measured values.

Tips For Better Results

Enter one matrix row per line. Separate values with spaces or commas. Use fractions such as 3/4 when exact entry is easier. Choose a smaller tolerance for clean integer matrices. Choose a larger tolerance for noisy decimal data. Always review the RREF table before using the answer in work.

Interpreting The Answer

If rank equals the number of columns, the nullity is zero. If rank is smaller, free variables exist. The rank nullity theorem confirms that rank plus nullity equals the total number of columns.

FAQs

What is the rank of a matrix?

Rank is the number of independent columns or rows in a matrix. It equals the number of pivot columns found after row reduction.

What is the nullity of a matrix?

Nullity is the number of free variables in Ax equals zero. It also equals the number of columns minus the rank.

What does RREF mean?

RREF means reduced row echelon form. It is a simplified matrix form that shows pivots, free variables, and linear dependence clearly.

Can I enter fractions?

Yes. You can enter values such as 1/2, -3/4, or 5/8. The calculator converts them before row reduction.

Why does tolerance matter?

Tolerance decides when a very small value should be treated as zero. It helps handle decimal rounding and measured data.

What are pivot columns?

Pivot columns contain leading entries in the reduced matrix. They identify independent columns in the original matrix.

What are free variable columns?

Free variable columns are non-pivot columns. They increase nullity and create directions inside the null space.

Does rank plus nullity always equal columns?

Yes. For any matrix, rank plus nullity equals the number of columns. This is the rank nullity theorem.

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