Eigenvalue of Matrix Calculator

Enter square matrix values and get eigenvalues fast. Check trace, determinant, vectors, exports, and graphs. Study characteristic equations with clear stepwise outputs for learning.

Calculator

Example Data Table

Matrix Trace Determinant Expected Eigenvalues
[[4, 1], [1, 4]] 8 15 5, 3
[[2, 0], [0, 7]] 9 14 2, 7
[[4, 1, 0], [1, 4, 0], [0, 0, 2]] 10 30 5, 3, 2
[[0, -1], [1, 0]] 0 1 i, -i

Formula Used

Eigenvalue equation: A v = λ v, where v is a nonzero eigenvector.

Characteristic equation: det(A - λI) = 0.

2 x 2 matrix: λ² - trace(A)λ + det(A) = 0.

3 x 3 matrix: λ³ - trace(A)λ² + c₂λ - det(A) = 0.

3 x 3 c₂: ae + ai + ei - bd - cg - fh for matrix rows [a,b,c], [d,e,f], [g,h,i].

How to Use This Calculator

  1. Select a 2 x 2 or 3 x 3 matrix.
  2. Enter every matrix entry in the visible fields.
  3. Choose decimal places and eigenvector options.
  4. Press the calculate button.
  5. Read the eigenvalues, graph, polynomial, trace, and determinant.
  6. Use CSV or PDF export for saving results.

What This Tool Does

An eigenvalue describes a scale change caused by a matrix. Some vectors keep their direction after multiplication. Those vectors are eigenvectors. Their scale factors are eigenvalues. This calculator finds them for two by two and three by three square matrices. It also shows trace, determinant, characteristic equation, and optional real eigenvectors.

Why Eigenvalues Matter

Eigenvalues appear in many topics. They help with linear transformations, stability, vibrations, data reduction, Markov chains, and differential equations. A large eigenvalue often shows a strong stretching direction. A negative eigenvalue shows reversal with scaling. A complex pair shows rotation and stretching together. These ideas make matrices easier to understand.

How The Calculator Works

The tool first reads the matrix entries. It computes the trace from the main diagonal. It computes the determinant using the selected matrix size. Then it builds the characteristic polynomial. For a two by two matrix, it solves a quadratic equation. For a three by three matrix, it solves a cubic equation. Results may be real or complex.

Reading The Results

Each eigenvalue is listed with its real and imaginary parts. Real eigenvalues may include a direction vector. The graph places eigenvalues on the complex plane. Points on the horizontal axis are real. Points above or below the axis have imaginary parts. The CSV button exports result rows. The PDF button saves a quick report.

Best Practices

Enter exact integers when possible. Use more decimal places for close roots. Check the determinant to understand zero eigenvalues. A zero determinant means at least one eigenvalue is zero. Repeated roots can have limited eigenvectors. Small rounding errors may appear for cubic equations. Use the tolerance field when the matrix has nearly repeated values.

Study Benefits

This calculator is useful for homework checks and review. It does not hide the method. It shows the polynomial used for solving. It gives enough detail for manual comparison. You can test diagonal, triangular, symmetric, or rotation matrices. Try changing one entry and watch the roots move. This helps connect algebra with geometry. It also supports classroom demonstrations during lessons. Teachers can prepare examples, compare outputs, and explain why similar matrices share the same eigenvalues.

FAQs

What is an eigenvalue?

An eigenvalue is a scalar that shows how much a matrix stretches or reverses an eigenvector during multiplication.

What matrix sizes are supported?

This page supports two by two and three by three square matrices, which cover many classroom and practical examples.

Can eigenvalues be complex?

Yes. Some real matrices have complex eigenvalues, especially matrices that represent rotation or combined rotation and scaling.

What is the characteristic polynomial?

It is the polynomial formed from det(A - λI). Its roots are the eigenvalues of the matrix.

Why is determinant shown?

The determinant equals the product of eigenvalues. It also shows whether zero is an eigenvalue.

Why is trace shown?

The trace equals the sum of eigenvalues, counted with multiplicity. It helps verify the calculation quickly.

Why are some eigenvectors missing?

The page expands real eigenvectors. Complex eigenvectors need complex component arithmetic, so they are not expanded here.

Can I export the results?

Yes. Use the CSV button for spreadsheet data or the PDF button for a quick printable report.

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Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.