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Free Null Space (Kernel) Calculator

Find the null space (kernel) basis and nullity of any matrix — square or rectangular, up to 6×6.

100% Free No Signup Works on all devices

Last updated October 5, 2026 · Report an error

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The null space (or kernel) of a matrix A is the set of all vectors x that satisfy Ax = 0 — it reveals whether a matrix is singular and, if so, how many independent directions it collapses to zero.

This calculator finds the null space basis vectors and nullity of any matrix — square or rectangular — with rows and columns each from 2 up to 6.

How it works

Enter the number of rows and columns and the matrix values — they don't need to match. The calculator reduces the matrix to reduced row echelon form, identifies which columns lack a pivot (the free variables), and constructs one basis vector for each free variable by back-solving the pivot rows.

  1. Click Calculate to see your results.

Examples

Singular 2×2 example

The matrix [[1,2],[2,4]] (whose rows are proportional) has nullity 1, with a null space basis vector of (-2, 1).

Identity matrix

The 2×2 identity matrix has nullity 0 — its only solution to Ax = 0 is the trivial zero vector, since the matrix is full rank.

Who should use it

  • Checking linear algebra coursework on null space, kernel, and singular matrices.
  • Determining whether a matrix is invertible before attempting to compute its inverse.

Industry applications

  • Linear algebra education
  • Engineering, physics, and applied mathematics

Advantages

  • Automatically identifies free variables and constructs a full basis, not just the nullity number.
  • Handles both square and rectangular matrices, up to 6 rows and 6 columns.

Limitations

  • Capped at 6 rows and 6 columns to keep computation instant on a public, synchronous endpoint.

Common mistakes to avoid

  • Expecting a non-trivial null space for every matrix — full-rank (non-singular) matrices only have the zero vector.
  • Forgetting that each returned vector is only one basis vector — any scalar multiple (or combination, if nullity > 1) is also in the null space.

Best practices

  • Verify a returned basis vector by multiplying it against the original matrix — the result should be the zero vector.

Tips

  • A matrix has an inverse if and only if its null space is trivial (nullity 0) — this calculator doubles as a quick singularity check.

Frequently asked questions

Yes, with no signup and no limit on how many matrices you check.
It means the matrix is full rank (invertible, for a square matrix) — the only vector that solves Ax = 0 is the all-zero vector.
The rank-nullity theorem states rank + nullity = n (the number of columns) — a higher rank always means a smaller (or zero) null space.
This is a deliberate safety limit for the site's public, synchronous calculators — 6×6 keeps computation instant while covering the vast majority of textbook use cases.

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