Algebra Calculators

##### Related Content

- Adding and Subtracting Scientific Notation
- Adding Fractions
- Algebra Calculators
- Arithmetic Sequence
- Average Rate of Change
- Change of Base Formula
- Cm to M
- Commutative Property of Addition
- Completing the Square
- Cross Product Calculator
- Determinant Calculator
- Determinant of a Matrix
- Difference of Squares
- Discriminant
- Divisibility Rule for 7
- Dot Product Calculator
- Eigenvalue Calculator
- Eigenvector Calculator
- Equation of a Circle
- Even Numbers
- Exponent Rules
- Factorial Calculator
- Fractional Exponents
- How to Find the Median
- Interval Notation
- Matrix Addition
- Matrix Subtraction
- Midpoint Formula
- Multiplying Negative Numbers
- Negative Exponents
- Odd Numbers
- One to One Function
- Partial Fraction Decomposition Calculator
- Point Slope Form
- Properties of Multiplication
- Rationalize the Denominator
- Rectangular to Polar Calculator
- Reflexive Property
- Round to the Nearest Tenth
- RREF Calculator
- Slope Calculator
- Slope Intercept Form
- Standard Form
- Summation Calculator
- Vertex Form

Programmers and Teachers:

# Eigenvector Calculator

## Eigenvector Lesson

#### Lesson Contents

### What is an Eigenvector?

Eigenvectors are a set of vectors associated with a system of linear equations/matrix. The combination of the eigenvalues and eigenvalues of a system of equations/matrix is very useful in various mathematics, physics, and engineering problems.

“Eigen” is German for “own”. These semantics describe the relationship between the eigenvalues and eigenvectors; each eigenvalue has a corresponding eigenvector, and vice versa. The eigenvalues and eigenvectors of any linear system of equations/matrix can be found if the matrix is square. A square matrix is one that has an equal number of columns and rows. Non-square matrices will have complex/imaginary eigenvalues and eigenvectors.

### How to Find the Eigenvectors

The basic representation of the relationship between an eigenvector and its corresponding eigenvalue is given as Av = λv, where *A* is a matrix of *m* rows and *m* columns, *λ* is a scalar, and *v* is a vector of *m* columns. In this relation, true values of *v* are the eigenvectors, and true values of *λ* are the eigenvalues.

For the value of a variable to be true, it must satisfy the equation such that the left and right sides of the equation are equal. Since we will solve for the eigenvalues first, the eigenvectors will satisfy the equation for each given eigenvalue. There may be more eigenvectors than eigenvalues, so each value of *λ* may have multiple values of *v* that satisfy the equation. It is possible for there to be an infinite number of eigenvectors for an eigenvalue, but usually there will only be a few distinct eigenvectors.

The equation Av = λv can be rearranged to A – I = 0 where *I* is the identity matrix. Then, we can proceed to carrying out the matrix multiplication and subtraction operations which will result in a polynomial. This polynomial is set equal to zero. Then, the roots of the terms can be solved for. The roots of these terms are the eigenvalues. When the eigenvalues are known, we can plug them into the equation Av = λv and find out eigenvectors.

In a matrix of *m* columns and rows, there can be as few as zero eigenvalues, and as many as *m* eigenvalues. As stated earlier, each of these eigenvalues could have any number of eigenvectors associated with it. This means that we can expect the number of eigenvectors of a system to be anywhere from zero to infinity. Now, that’s not a particularly small range of values, but we can expect the number of eigenvectors to be less than twenty when working with standard 3×3 and 4×4 matrices.

## How the Calculator Works

The calculator on this page uses numerical routines to find the eigenvalues and eigenvectors. These numerical routines are approximated calculations that are performed very many times until convergence to an accurate solution is reached. It then returns the eigenvalues and their respective unit eigenvectors to this page.

Because computer processors are so much more capable of fast, simple calculations than a human, the calculator can go through these routines in the blink of an eye and return you a result that is **accurate to a minimum of the fourth decimal place.**

This calculator finds the eigenvectors and eigenvalues simultaneously, which can get messy for large systems/matrices. If you would like to only see the eigenvalues of your matrix, visit our eigenvalue calculator.

Result :

Worksheet 1

Download.pdf

Cheat sheet

Download.pdf