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Reduced Row Echelon Form (RREF) Calculator

Transform any matrix to reduced row echelon form (RREF) with our free online calculator. Perfect for solving systems of linear equations, determining matrix rank, and more.

Matrix Input

Reduced Row Echelon Form Result

Error

Understanding Reduced Row Echelon Form (RREF)

The Reduced Row Echelon Form (RREF) is a fundamental concept in linear algebra that simplifies matrices to their most basic structure while preserving essential information about the linear system they represent.

Key Characteristics of RREF:

  • Leading ones: The first non-zero number in each row (called the leading coefficient) is always 1
  • Zero rows at bottom: All rows consisting entirely of zeros appear below rows with non-zero entries
  • Staircase pattern: Each leading 1 is positioned to the right of the leading 1 in the row above it
  • Column simplification: All entries above and below each leading 1 are zero

Practical Applications of RREF:

Academic Uses

  • • Solving systems of linear equations
  • • Determining linear independence of vectors
  • • Finding the rank of a matrix
  • • Calculating matrix inverses

Real-World Applications

  • • Computer graphics transformations
  • • Economic modeling
  • • Engineering system analysis
  • • Data science and machine learning

RREF Example

Original Matrix:

[ 1  2  3 ]
[ 4  5  6 ]
[ 7  8  9 ]

RREF Form:

[ 1  0 -1 ]
[ 0  1  2 ]
[ 0  0  0 ]

This example shows how our RREF calculator simplifies matrices to reveal fundamental properties like rank and solution sets for linear systems.

How to Use This RREF Calculator

  1. Set matrix dimensions: Adjust the rows and columns to match your matrix size
  2. Enter matrix values: Fill in all elements of your matrix
  3. Click "Calculate RREF": Our tool will instantly compute the reduced row echelon form
  4. Analyze results: The simplified matrix reveals key information about your linear system

This RREF calculator handles matrices up to 6×6, making it suitable for most classroom and homework problems in linear algebra.